#include "allheaders.h"
/*
*
* This data structure is used for pixOctreeColorQuant(),
* a color octree that adjusts to the color distribution
* in the image that is being quantized. The best settings
* are with CqNLevels = 6 and DITHERING set on.
*
* Notes:
* (1) the CTE (color table entry) index is sequentially
* assigned as the tree is pruned back
* (2) if 'bleaf' == 1, all pixels in that cube have been
* assigned to one or more CTEs. But note that if
* all 8 subcubes have 'bleaf' == 1, it will have no
* pixels left for assignment and will not be a CTE.
* (3) 'nleaves', the number of leaves contained at the next
* lower level is some number between 0 and 8, inclusive.
* If it is zero, it means that all colors within this cube
* are part of a single growing cluster that has not yet
* been set aside as a leaf. If 'nleaves' > 0, 'bleaf'
* will be set to 1 and all pixels not assigned to leaves
* at lower levels will be assigned to a CTE here.
* (However, as described above, if all pixels are already
* assigned, we set 'bleaf' = 1 but do not create a CTE
* at this level.)
* (4) To keep the maximum color error to a minimum, we
* prune the tree back to level 2, and require that
* all 64 level 2 cells are CTEs.
* (5) We reserve an extra set of colors to prevent running out
* of colors during the assignment of the final 64 level 2 cells.
* This is more likely to happen with small images.
* (6) When we run out of colors, the dithered image can be very
* poor, so we additionally prevent dithering if the image
* is small.
* (7) The color content of the image is measured, and if there
* is very little color, it is quantized in grayscale.
*
*/
struct ColorQuantCell
{
l_int32 rc, gc, bc; /* center values */
l_int32 n; /* number of samples in this cell */
l_int32 index; /* CTE (color table entry) index */
l_int32 nleaves; /* # of leaves contained at next lower level */
l_int32 bleaf; /* boolean: 0 if not a leaf, 1 if so */
};
typedef struct ColorQuantCell CQCELL;
/* Constants for pixOctreeColorQuant() */
static const l_int32 CqNLevels = 5; /* only 4, 5 and 6 are allowed */
static const l_int32 CqReservedColors = 64; /* to allow for level 2 */
/* remainder CTEs */
static const l_int32 ExtraReservedColors = 25; /* to avoid running out */
static const l_int32 TreeGenWidth = 350; /* big enough for good stats */
static const l_int32 MinDitherSize = 250; /* don't dither if smaller */
/*
*
* This data structure is used for pixOctreeQuantNumColors(),
* a color octree that adjusts in a simple way to the to the color
* distribution in the image that is being quantized. It outputs
* colormapped images, either 4 bpp or 8 bpp, depending on the
* max number of colors and the compression desired.
*
* The number of samples is saved as a float in the first location,
* because this is required to use it as the key that orders the
* cells in the priority queue.
*
* */
struct OctcubeQuantCell
{
l_float32 n; /* number of samples in this cell */
l_int32 octindex; /* octcube index */
l_int32 rcum, gcum, bcum; /* cumulative values */
l_int32 rval, gval, bval; /* average values */
};
typedef struct OctcubeQuantCell OQCELL;
/*
*
* This data structure is using for heap sorting octcubes
* by population. Sort order is decreasing.
*
*/
struct L_OctcubePop
{
l_float32 npix; /* parameter on which to sort */
l_int32 index; /* octcube index at assigned level */
l_int32 rval; /* mean red value of pixels in octcube */
l_int32 gval; /* mean green value of pixels in octcube */
l_int32 bval; /* mean blue value of pixels in octcube */
};
typedef struct L_OctcubePop L_OCTCUBE_POP;
/*
*
* In pixDitherOctindexWithCmap(), we use these default values.
To get the max value of 'dif' in the dithering color transfer,
divide these "DIF_CAP" values by 8. However, a value of
0 means that there is no cap (infinite cap). A very small
value is used for POP_DIF_CAP because dithering on the population
generated colormap can be unstable without a tight cap.
*
*/
static const l_int32 FIXED_DIF_CAP = 0;
static const l_int32 POP_DIF_CAP = 40;
/* Static octree helper function */
static l_int32 octreeFindColorCell(l_int32 octindex, CQCELL ***cqcaa,
l_int32 *pindex, l_int32 *prval,
l_int32 *pgval, l_int32 *pbval);
/* Static cqcell functions */
static CQCELL ***octreeGenerateAndPrune(PIX *pixs, l_int32 colors,
l_int32 reservedcolors,
PIXCMAP **pcmap);
static PIX *pixOctreeQuantizePixels(PIX *pixs, CQCELL ***cqcaa,
l_int32 ditherflag);
static CQCELL ***cqcellTreeCreate(void);
static void cqcellTreeDestroy(CQCELL ****pcqcaa);
/* Static helper octcube index functions */
static void getRGBFromOctcube(l_int32 cubeindex, l_int32 level,
l_int32 *prval, l_int32 *pgval, l_int32 *pbval);
static l_int32 getOctcubeIndices(l_int32 rgbindex, l_int32 level,
l_int32 *pbindex, l_int32 *psindex);
static l_int32 octcubeGetCount(l_int32 level, l_int32 *psize);
/* Static function to perform octcube-indexed dithering */
static l_int32 pixDitherOctindexWithCmap(PIX *pixs, PIX *pixd, l_uint32 *rtab,
l_uint32 *gtab, l_uint32 *btab,
l_int32 *carray, l_int32 difcap);
/* Static function to perform octcube-based quantizing from colormap */
static PIX *pixOctcubeQuantFromCmapLUT(PIX *pixs, PIXCMAP *cmap,
l_int32 mindepth, l_int32 *cmaptab,
l_uint32 *rtab, l_uint32 *gtab,
l_uint32 *btab);
#ifndef NO_CONSOLE_IO
#define DEBUG_COLORQUANT 0
#define DEBUG_OCTINDEX 0
#define DEBUG_OCTCUBE_CMAP 0
#define DEBUG_POP 0
#define DEBUG_FEW_COLORS 0
#define PRINT_OCTCUBE_STATS 0
#endif /* ~NO_CONSOLE_IO */
/*-------------------------------------------------------------------------*
* Two-pass adaptive octree color quantization *
*-------------------------------------------------------------------------*/
/*!
* \brief pixOctreeColorQuant()
*
* \param[in] pixs 32 bpp; 24-bit color
* \param[in] colors in colormap; some number in range [128 ... 256];
* the actual number of colors used will be smaller
* \param[in] ditherflag 1 to dither, 0 otherwise
* \return pixd 8 bpp with colormap, or NULL on error
*
*
* I found one description in the literature of octree color
* quantization, using progressive truncation of the octree,
* by M. Gervautz and W. Purgathofer in Graphics Gems, pp.
* 287-293, ed. A. Glassner, Academic Press, 1990.
* Rather than setting up a fixed partitioning of the color
* space ab initio, as we do here, they allow the octree to be
* progressively truncated as new pixels are added. They
* need to set up some data structures that are traversed
* with the addition of each 24 bit pixel, in order to decide
* either 1) in which cluster (sub-branch of the octree to put
* the pixel, or 2 whether to truncate the octree further
* to place the pixel in an existing cluster, or 3 which
* two existing clusters should be merged so that the pixel
* can be left to start a truncated leaf of the octree. Such dynamic
* truncation is considerably more complicated, and Gervautz et
* al. did not explain how they did it in anywhere near the
* detail required to check their implementation.
*
* The simple method in pixFixedOctcubeQuant256 is very
* fast, and with dithering the results are good, but you
* can do better if the color clusters are selected adaptively
* from the image. We want a method that makes much better
* use of color samples in regions of color space with high
* pixel density, while also fairly representing small numbers
* of color pixels in low density regions. Such adaptation
* requires two passes through the image: the first for generating
* the pruned tree of color cubes and the second for computing the index
* into the color table for each pixel.
*
* A relatively simple adaptive method is pixOctreeQuantByPopulation.
* That function first determines if the image has very few colors,
* and, if so, quantizes to those colors. If there are more than
* 256 colors, it generates a histogram of octcube leaf occupancy
* at level 4, chooses the 192 most populated such leaves as
* the first 192 colors, and sets the remaining 64 colors to the
* residual average pixel values in each of the 64 level 2 octcubes.
* This is a bit faster than pixOctreeColorQuant, and does very
* well without dithering, but for most images with dithering it
* is clearly inferior.
*
* We now describe pixOctreeColorQuant. The first pass is done
* on a subsampled image, because we do not need to use all the
* pixels in the image to generate the tree. Subsampling
* down to 0.25 1/16 of the pixels makes the program run
* about 1.3 times faster.
*
* Instead of dividing the color space into 256 equal-sized
* regions, we initially divide it into 2^12 or 2^15 or 2^18
* equal-sized octcubes. Suppose we choose to use 2^18 octcubes.
* This gives us 6 octree levels. We then prune back,
* starting from level 6. For every cube at level 6, there
* are 8 cubes at level 5. Call the operation of putting a
* cube aside as a color table entry CTE a "saving."
* We use a in general level-dependent threshold, and save
* those level 6 cubes that are above threshold.
* The rest are combined into the containing level 5 cube.
* If between 1 and 7 level 6 cubes within a level 5
* cube have been saved by thresholding, then the remaining
* level 6 cubes in that level 5 cube are automatically
* saved as well, without applying a threshold. This greatly
* simplifies both the description of the CTEs and the later
* classification of each pixel as belonging to a CTE.
* This procedure is iterated through every cube, starting at
* level 5, and then 4, 3, and 2, successively. The result is that
* each CTE contains the entirety of a set of from 1 to 7 cubes
* from a given level that all belong to a single cube at the
* level above. We classify the CTEs in terms of the
* condition in which they are made as either being "threshold"
* or "residual." They are "threshold" CTEs if no subcubes
* are CTEs that is, they contain every pixel within the cube
* and the number of pixels exceeds the threshold for making
* a CTE. They are "residual" CTEs if at least one but not more
* than 7 of the subcubes have already been determined to be CTEs;
* this happens automatically -- no threshold is applied.
* If all 8 subcubes are determined to be CTEs, the cube is
* marked as having all pixels accounted for 'bleaf' = 1 but
* is not saved as a CTE.
*
* We stop the pruning at level 2, at which there are 64
* sub-cubes. Any pixels not already claimed in a CTE are
* put in these cubes.
*
* As the cubes are saved as color samples in the color table,
* the number of remaining pixels P and the number of
* remaining colors in the color table N are recomputed,
* along with the average number of pixels P/N ppc to go in
* each of the remaining colors. This running average number is
* used to set the threshold at the current level.
*
* Because we are going to very small cubes at levels 6 or 5,
* and will dither the colors for errors, it is not necessary
* to compute the color center of each cluster; we can simply
* use the center of the cube. This gives us a minimax error
* condition: the maximum error is half the width of the
* level 2 cubes -- 32 color values out of 256 -- for each color
* sample. In practice, most of the pixels will be very much
* closer to the center of their cells. And with dithering,
* the average pixel color in a small region will be closer still.
* Thus with the octree quantizer, we are able to capture
* regions of high color pdf probability density function in small
* but accurate CTEs, and to have only a small number of pixels
* that end up a significant distance with a guaranteed maximum
* from their true color.
*
* How should the threshold factor vary? Threshold factors
* are required for levels 2, 3, 4 and 5 in the pruning stage.
* The threshold for level 5 is actually applied to cubes at
* level 6, etc. From various experiments, it appears that
* the results do not vary appreciably for threshold values near 1.0.
* If you want more colors in smaller cubes, the threshold
* factors can be set lower than 1.0 for cubes at levels 4 and 5.
* However, if the factor is set much lower than 1.0 for
* levels 2 and 3, we can easily run out of colors.
* We put aside 64 colors in the calculation of the threshold
* values, because we must have 64 color centers at level 2,
* that will have very few pixels in most of them.
* If we reduce the factor for level 5 to 0.4, this will
* generate many level 6 CTEs, and consequently
* many residual cells will be formed up from those leaves,
* resulting in the possibility of running out of colors.
* Remember, the residual CTEs are mandatory, and are formed
* without using the threshold, regardless of the number of
* pixels that are absorbed.
*
* The implementation logically has four parts:
*
* 1 accumulation into small, fixed cells
* 2 pruning back into selected CTE cubes
* 3 organizing the CTEs for fast search to find
* the CTE to which any image pixel belongs
* 4 doing a second scan to code the image pixels by CTE
*
* Step 1 is straightforward; we use 2^15 cells.
*
* We've already discussed how the pruning step 2 will be performed.
*
* Steps 3) and (4 are related, in that the organization
* used by step 3 determines how the search actually
* takes place for each pixel in step 4.
*
* There are many ways to do step 3. Let's explore a few.
*
* a The simplest is to order the cubes from highest occupancy
* to lowest, and traverse the list looking for the deepest
* match. To make this more efficient, so that we know when
* to stop looking, any cube that has separate CTE subcubes
* would be marked as such, so that we know when we hit a
* true leaf.
*
* b Alternatively, we can order the cubes by highest
* occupancy separately each level, and work upward,
* starting at level 5, so that when we find a match we
* know that it will be correct.
*
* c Another approach would be to order the cubes by
* "address" and use a hash table to find the cube
* corresponding to a pixel color. I don't know how to
* do this with a variable length address, as each CTE
* will have 3*n bits, where n is the level.
*
* d Another approach entirely is to put the CTE cubes into
* a tree, in such a way that starting from the root, and
* using 3 bits of address at a time, the correct branch of
* each octree can be taken until a leaf is found. Because
* a given cube can be both a leaf and also have branches
* going to sub-cubes, the search stops only when no
* marked subcubes have addresses that match the given pixel.
*
* In the tree method, we can start with a dense infrastructure,
* and place the leaves corresponding to the N colors
* in the tree, or we can grow from the root only those
* branches that end directly on leaves.
*
* What we do here is to take approach d, and implement the tree
* "virtually", as a set of arrays, one array for each level
* of the tree. Initially we start at level 5, an array with
* 2^15 cubes, each with 8 subcubes. We then build nodes at
* levels closer to the root; at level 4 there are 2^12 nodes
* each with 8 subcubes; etc. Using these arrays has
* several advantages:
*
* ~ We don't need to keep track of links between cubes
* and subcubes, because we can use the canonical
* addressing on the cell arrays directly to determine
* which nodes are parent cubes and which are sub-cubes.
*
* ~ We can prune directly on this tree
*
* ~ We can navigate the pruned tree quickly to classify
* each pixel in the image.
*
* Canonical addressing guarantees that the i-th node at level k
* has 8 subnodes given by the 8*i ... 8*i+7 nodes at level k+1.
*
* The pruning step works as follows. We go from the lowest
* level up. At each level, the threshold is found from the
* product of a factor near 1.0 and the ratio of unmarked pixels
* to remaining colors minus the 64. We march through
* the space, sequentially considering a cube and its 8 subcubes.
* We first check those subcubes that are not already
* marked as CTE to see if any are above threshold, and if so,
* generate a CTE and mark them as such.
* We then determine if any of the subcubes have been marked.
* If so, and there are subcubes that are not marked,
* we generate a CTE for the cube from the remaining unmarked
* subcubes; this is mandatory and does not depend on how many
* pixels are in the set of subcubes. If none of the subcubes
* are marked, we aggregate their pixels into the cube
* containing them, but do not mark it as a CTE; that
* will be determined when iterating through the next level up.
*
* When all the pixels in a cube are accounted for in one or more
* colors, we set the boolean 'bleaf' to true. This is the
* flag used to mark the cubes in the pruning step. If a cube
* is marked, and all 8 subcubes are marked, then it is not
* itself given a CTE because all pixels have already been
* accounted for.
*
* Note that the pruning of the tree and labelling of the CTEs
* step 2 accomplishes step 3 implicitly, because the marked
* and pruned tree is ready for use in labelling each pixel
* in step 4. We now, for every pixel in the image, traverse
* the tree from the root, looking for the lowest cube that is a leaf.
* At each level we have a cube and subcube. If we reach a subcube
* leaf that is marked 0, we know that the color is stored in the
* cube above, and we've found the CTE. Otherwise, the subcube
* leaf is marked 1. If we're at the last level, we've reached
* the final leaf and must use it. Otherwise, continue the
* process at the next level down.
*
* For robustness, efficiency and high quality output, we do the following:
*
* (1) Measure the color content of the image. If there is very little
* color, quantize in grayscale.
* (2) For efficiency, build the octree with a subsampled image if the
* image is larger than some threshold size.
* (3) Reserve an extra set of colors to prevent running out of colors
* when pruning the octree; specifically, during the assignment
* of those level 2 cells out of the 64 that have unassigned
* pixels. The problem of running out is more likely to happen
* with small images, because the estimation we use for the
* number of pixels available is not accurate.
* (4) In the unlikely event that we run out of colors, the dithered
* image can be very poor. As this would only happen with very
* small images, and dithering is not particularly noticeable with
* such images, turn it off.
*
*/
PIX *
pixOctreeColorQuant(PIX *pixs,
l_int32 colors,
l_int32 ditherflag)
{
PROCNAME("pixOctreeColorQuant");
if (!pixs)
return (PIX *)ERROR_PTR("pixs not defined", procName, NULL);
if (pixGetDepth(pixs) != 32)
return (PIX *)ERROR_PTR("pixs not 32 bpp", procName, NULL);
if (colors < 128 || colors > 240) /* further restricted */
return (PIX *)ERROR_PTR("colors must be in [128, 240]", procName, NULL);
return pixOctreeColorQuantGeneral(pixs, colors, ditherflag, 0.01f, 0.01f);
}
/*!
* \brief pixOctreeColorQuantGeneral()
*
* \param[in] pixs 32 bpp; 24-bit color
* \param[in] colors in colormap; some number in range [128 ... 240];
* the actual number of colors used will be smaller
* \param[in] ditherflag 1 to dither, 0 otherwise
* \param[in] validthresh minimum fraction of pixels neither near white
* nor black, required for color quantization;
* typically ~0.01, but smaller for images that have
* color but are nearly all white
* \param[in] colorthresh minimum fraction of pixels with color that are
* not near white or black, that are required
* for color quantization; typ. ~0.01, but smaller
* for images that have color along with a
* significant fraction of gray
* \return pixd 8 bit with colormap, or NULL on error
*
*
* Notes:
* (1) The parameters %validthresh and %colorthresh are used to
* determine if color quantization should be used on an image,
* or whether, instead, it should be quantized in grayscale.
* If the image has very few non-white and non-black pixels, or
* if those pixels that are non-white and non-black are all
* very close to either white or black, it is usually better
* to treat the color as accidental and to quantize the image
* to gray only. These parameters are useful if you know
* something a priori about the image. Perhaps you know that
* there is only a very small fraction of color pixels, but they're
* important to preserve; then you want to use a smaller value for
* these parameters. To disable conversion to gray and force
* color quantization, use %validthresh = 0.0 and %colorthresh = 0.0.
* (2) See pixOctreeColorQuant() for algorithmic and implementation
* details. This function has a more general interface.
* (3) See pixColorFraction() for computing the fraction of pixels
* that are neither white nor black, and the fraction of those
* pixels that have little color. From the documentation there:
* If pixfract is very small, there are few pixels that are
* neither black nor white. If colorfract is very small,
* the pixels that are neither black nor white have very
* little color content. The product 'pixfract * colorfract'
* gives the fraction of pixels with significant color content.
* We test against the product %validthresh * %colorthresh
* to find color in images that have either very few
* intermediate gray pixels or that have many such gray pixels.
*
*/
PIX *
pixOctreeColorQuantGeneral(PIX *pixs,
l_int32 colors,
l_int32 ditherflag,
l_float32 validthresh,
l_float32 colorthresh)
{
l_int32 w, h, minside, factor, index, rval, gval, bval;
l_float32 scalefactor;
l_float32 pixfract; /* fraction neither near white nor black */
l_float32 colorfract; /* fraction with color of the pixfract population */
CQCELL ***cqcaa;
PIX *pixd, *pixsub;
PIXCMAP *cmap;
PROCNAME("pixOctreeColorQuantGeneral");
if (!pixs)
return (PIX *)ERROR_PTR("pixs not defined", procName, NULL);
if (pixGetDepth(pixs) != 32)
return (PIX *)ERROR_PTR("pixs not 32 bpp", procName, NULL);
if (colors < 128 || colors > 240)
return (PIX *)ERROR_PTR("colors must be in [128, 240]", procName, NULL);
/* Determine if the image has sufficient color content for
* octree quantization, based on the input thresholds.
* If pixfract << 1, most pixels are close to black or white.
* If colorfract << 1, the pixels that are not near
* black or white have very little color.
* If with insufficient color, quantize with a grayscale colormap. */
pixGetDimensions(pixs, &w, &h, NULL);
if (validthresh > 0.0 && colorthresh > 0.0) {
minside = L_MIN(w, h);
factor = L_MAX(1, minside / 400);
pixColorFraction(pixs, 20, 244, 20, factor, &pixfract, &colorfract);
if (pixfract * colorfract < validthresh * colorthresh) {
L_INFO("\n Pixel fraction neither white nor black = %6.3f"
"\n Color fraction of those pixels = %6.3f"
"\n Quantizing to 8 bpp gray\n",
procName, pixfract, colorfract);
return pixConvertTo8(pixs, 1);
}
} else {
L_INFO("\n Process in color by default\n", procName);
}
/* Conditionally subsample to speed up the first pass */
if (w > TreeGenWidth) {
scalefactor = (l_float32)TreeGenWidth / (l_float32)w;
pixsub = pixScaleBySampling(pixs, scalefactor, scalefactor);
} else {
pixsub = pixClone(pixs);
}
/* Drop the number of requested colors if image is very small */
if (w < MinDitherSize && h < MinDitherSize)
colors = L_MIN(colors, 220);
/* Make the pruned octree */
cqcaa = octreeGenerateAndPrune(pixsub, colors, CqReservedColors, &cmap);
if (!cqcaa) {
pixDestroy(&pixsub);
return (PIX *)ERROR_PTR("tree not made", procName, NULL);
}
#if DEBUG_COLORQUANT
L_INFO(" Colors requested = %d\n", procName, colors);
L_INFO(" Actual colors = %d\n", procName, cmap->n);
#endif /* DEBUG_COLORQUANT */
/* Do not dither if image is very small */
if (w < MinDitherSize && h < MinDitherSize && ditherflag == 1) {
L_INFO("Small image: dithering turned off\n", procName);
ditherflag = 0;
}
/* Traverse tree from root, looking for lowest cube
* that is a leaf, and set dest pix value to its
* colortable index */
if ((pixd = pixOctreeQuantizePixels(pixs, cqcaa, ditherflag)) == NULL) {
pixDestroy(&pixsub);
cqcellTreeDestroy(&cqcaa);
return (PIX *)ERROR_PTR("pixd not made", procName, NULL);
}
/* Attach colormap and copy res */
pixSetColormap(pixd, cmap);
pixCopyResolution(pixd, pixs);
pixCopyInputFormat(pixd, pixs);
/* Force darkest color to black if each component <= 4 */
pixcmapGetRankIntensity(cmap, 0.0, &index);
pixcmapGetColor(cmap, index, &rval, &gval, &bval);
if (rval < 5 && gval < 5 && bval < 5)
pixcmapResetColor(cmap, index, 0, 0, 0);
/* Force lightest color to white if each component >= 252 */
pixcmapGetRankIntensity(cmap, 1.0, &index);
pixcmapGetColor(cmap, index, &rval, &gval, &bval);
if (rval > 251 && gval > 251 && bval > 251)
pixcmapResetColor(cmap, index, 255, 255, 255);
cqcellTreeDestroy(&cqcaa);
pixDestroy(&pixsub);
return pixd;
}
/*!
* \brief octreeGenerateAndPrune()
*
* \param[in] pixs
* \param[in] colors number of colors to use between 128 and 256
* \param[in] reservedcolors number of reserved colors
* \param[out] pcmap colormap returned
* \return octree, colormap and number of colors used, or NULL
* on error
*
*
* Notes:
* (1) The number of colors in the cmap may differ from the number
* of colors requested, but it will not be larger than 256
*
*/
static CQCELL ***
octreeGenerateAndPrune(PIX *pixs,
l_int32 colors,
l_int32 reservedcolors,
PIXCMAP **pcmap)
{
l_int32 rval, gval, bval, cindex;
l_int32 level, ncells, octindex;
l_int32 w, h, wpls;
l_int32 i, j, isub;
l_int32 npix; /* number of remaining pixels to be assigned */
l_int32 ncolor; /* number of remaining color cells to be used */
l_int32 ppc; /* ave number of pixels left for each color cell */
l_int32 rv, gv, bv;
l_float32 thresholdFactor[] = {0.01f, 0.01f, 1.0f, 1.0f, 1.0f, 1.0f};
l_float32 thresh; /* factor of ppc for this level */
l_uint32 *datas, *lines;
l_uint32 *rtab, *gtab, *btab;
CQCELL ***cqcaa; /* one array for each octree level */
CQCELL **cqca, **cqcasub;
CQCELL *cqc, *cqcsub;
PIXCMAP *cmap;
NUMA *nat; /* accumulates levels for threshold cells */
NUMA *nar; /* accumulates levels for residual cells */
PROCNAME("octreeGenerateAndPrune");
if (!pixs)
return (CQCELL ***)ERROR_PTR("pixs not defined", procName, NULL);
if (pixGetDepth(pixs) != 32)
return (CQCELL ***)ERROR_PTR("pixs must be 32 bpp", procName, NULL);
if (colors < 128 || colors > 256)
return (CQCELL ***)ERROR_PTR("colors not in [128,256]", procName, NULL);
if (!pcmap)
return (CQCELL ***)ERROR_PTR("&cmap not defined", procName, NULL);
if ((cqcaa = cqcellTreeCreate()) == NULL)
return (CQCELL ***)ERROR_PTR("cqcaa not made", procName, NULL);
/* Make the canonical index tables */
rtab = gtab = btab = NULL;
makeRGBToIndexTables(CqNLevels, &rtab, >ab, &btab);
/* Generate an 8 bpp cmap (max size 256) */
cmap = pixcmapCreate(8);
*pcmap = cmap;
pixGetDimensions(pixs, &w, &h, NULL);
npix = w * h; /* initialize to all pixels */
ncolor = colors - reservedcolors - ExtraReservedColors;
ppc = npix / ncolor;
datas = pixGetData(pixs);
wpls = pixGetWpl(pixs);
/* Accumulate the centers of each cluster at level CqNLevels */
ncells = 1 << (3 * CqNLevels);
cqca = cqcaa[CqNLevels];
for (i = 0; i < h; i++) {
lines = datas + i * wpls;
for (j = 0; j < w; j++) {
extractRGBValues(lines[j], &rval, &gval, &bval);
octindex = rtab[rval] | gtab[gval] | btab[bval];
cqc = cqca[octindex];
cqc->n++;
}
}
/* Arrays for storing statistics */
nat = numaCreate(0);
nar = numaCreate(0);
/* Prune back from the lowest level and generate the colormap */
for (level = CqNLevels - 1; level >= 2; level--) {
thresh = thresholdFactor[level];
cqca = cqcaa[level];
cqcasub = cqcaa[level + 1];
ncells = 1 << (3 * level);
for (i = 0; i < ncells; i++) { /* i is octindex at level */
cqc = cqca[i];
for (j = 0; j < 8; j++) { /* check all subnodes */
isub = 8 * i + j; /* isub is octindex at level+1 */
cqcsub = cqcasub[isub];
if (cqcsub->bleaf == 1) { /* already a leaf? */
cqc->nleaves++; /* count the subcube leaves */
continue;
}
if (cqcsub->n >= thresh * ppc) { /* make it a true leaf? */
cqcsub->bleaf = 1;
if (cmap->n < 256) {
cqcsub->index = cmap->n; /* assign the color index */
getRGBFromOctcube(isub, level + 1, &rv, &gv, &bv);
pixcmapAddColor(cmap, rv, gv, bv);
#if 1 /* save values */
cqcsub->rc = rv;
cqcsub->gc = gv;
cqcsub->bc = bv;
#endif
} else {
/* This doesn't seem to happen. Do something. */
L_ERROR("assigning pixels to wrong color\n", procName);
pixcmapGetNearestIndex(cmap, 128, 128, 128, &cindex);
cqcsub->index = cindex; /* assign to the nearest */
pixcmapGetColor(cmap, cindex, &rval, &gval, &bval);
cqcsub->rc = rval;
cqcsub->gc = gval;
cqcsub->bc = bval;
}
cqc->nleaves++;
npix -= cqcsub->n;
ncolor--;
if (ncolor > 0)
ppc = npix / ncolor;
else if (ncolor + reservedcolors > 0)
ppc = npix / (ncolor + reservedcolors);
else
ppc = 1000000; /* make it big */
numaAddNumber(nat, level + 1);
#if DEBUG_OCTCUBE_CMAP
lept_stderr("Exceeds threshold: colors used = %d, colors remaining = %d\n",
cmap->n, ncolor + reservedcolors);
lept_stderr(" cell with %d pixels, npix = %d, ppc = %d\n",
cqcsub->n, npix, ppc);
lept_stderr(" index = %d, level = %d, subindex = %d\n",
i, level, j);
lept_stderr(" rv = %d, gv = %d, bv = %d\n", rv, gv, bv);
#endif /* DEBUG_OCTCUBE_CMAP */
}
}
if (cqc->nleaves > 0 || level == 2) { /* make the cube a leaf now */
cqc->bleaf = 1;
if (cqc->nleaves < 8) { /* residual CTE cube: acquire the
* remaining pixels */
for (j = 0; j < 8; j++) { /* check all subnodes */
isub = 8 * i + j;
cqcsub = cqcasub[isub];
if (cqcsub->bleaf == 0) /* absorb */
cqc->n += cqcsub->n;
}
if (cmap->n < 256) {
cqc->index = cmap->n; /* assign the color index */
getRGBFromOctcube(i, level, &rv, &gv, &bv);
pixcmapAddColor(cmap, rv, gv, bv);
#if 1 /* save values */
cqc->rc = rv;
cqc->gc = gv;
cqc->bc = bv;
#endif
} else {
L_WARNING("possibly assigned pixels to wrong color\n",
procName);
/* This is very bad. It will only cause trouble
* with dithering, and we try to avoid it with
* ExtraReservedColors. */
pixcmapGetNearestIndex(cmap, rv, gv, bv, &cindex);
cqc->index = cindex; /* assign to the nearest */
pixcmapGetColor(cmap, cindex, &rval, &gval, &bval);
cqc->rc = rval;
cqc->gc = gval;
cqc->bc = bval;
}
npix -= cqc->n;
ncolor--;
if (ncolor > 0)
ppc = npix / ncolor;
else if (ncolor + reservedcolors > 0)
ppc = npix / (ncolor + reservedcolors);
else
ppc = 1000000; /* make it big */
numaAddNumber(nar, level);
#if DEBUG_OCTCUBE_CMAP
lept_stderr("By remainder: colors used = %d, colors remaining = %d\n",
cmap->n, ncolor + reservedcolors);
lept_stderr(" cell with %d pixels, npix = %d, ppc = %d\n",
cqc->n, npix, ppc);
lept_stderr(" index = %d, level = %d\n", i, level);
lept_stderr(" rv = %d, gv = %d, bv = %d\n", rv, gv, bv);
#endif /* DEBUG_OCTCUBE_CMAP */
}
} else { /* absorb all the subpixels but don't make it a leaf */
for (j = 0; j < 8; j++) { /* absorb from all subnodes */
isub = 8 * i + j;
cqcsub = cqcasub[isub];
cqc->n += cqcsub->n;
}
}
}
}
#if PRINT_OCTCUBE_STATS
{
l_int32 tc[] = {0, 0, 0, 0, 0, 0, 0};
l_int32 rc[] = {0, 0, 0, 0, 0, 0, 0};
l_int32 nt, nr, ival;
nt = numaGetCount(nat);
nr = numaGetCount(nar);
for (i = 0; i < nt; i++) {
numaGetIValue(nat, i, &ival);
tc[ival]++;
}
for (i = 0; i < nr; i++) {
numaGetIValue(nar, i, &ival);
rc[ival]++;
}
lept_stderr(" Threshold cells formed: %d\n", nt);
for (i = 1; i < CqNLevels + 1; i++)
lept_stderr(" level %d: %d\n", i, tc[i]);
lept_stderr("\n Residual cells formed: %d\n", nr);
for (i = 0; i < CqNLevels ; i++)
lept_stderr(" level %d: %d\n", i, rc[i]);
}
#endif /* PRINT_OCTCUBE_STATS */
numaDestroy(&nat);
numaDestroy(&nar);
LEPT_FREE(rtab);
LEPT_FREE(gtab);
LEPT_FREE(btab);
return cqcaa;
}
/*!
* \brief pixOctreeQuantizePixels()
*
* \param[in] pixs 32 bpp
* \param[in] cqcaa octree in array format
* \param[in] ditherflag 1 for dithering, 0 for no dithering
* \return pixd or NULL on error
*
*
* Notes:
* (1) This routine doesn't need to use the CTEs (colormap
* table entries) because the color indices are embedded
* in the octree. Thus, the calling program must make
* and attach the colormap to pixd after it is returned.
* (2) Dithering is performed in integers, effectively rounding
* to 1/8 sample increment. The data in the integer buffers is
* 64 times the sample values. The 'dif' is 8 times the
* sample values, and this spread, multiplied by 8, to the
* integer buffers. Because the dif is truncated to an
* integer, the dither is accurate to 1/8 of a sample increment,
* or 1/2048 of the color range.
*
*/
static PIX *
pixOctreeQuantizePixels(PIX *pixs,
CQCELL ***cqcaa,
l_int32 ditherflag)
{
l_uint8 *bufu8r, *bufu8g, *bufu8b;
l_int32 rval, gval, bval;
l_int32 octindex, index;
l_int32 val1, val2, val3, dif;
l_int32 w, h, wpls, wpld, i, j, success;
l_int32 rc, gc, bc;
l_int32 *buf1r, *buf1g, *buf1b, *buf2r, *buf2g, *buf2b;
l_uint32 *rtab, *gtab, *btab;
l_uint32 *datas, *datad, *lines, *lined;
PIX *pixd;
PROCNAME("pixOctreeQuantizePixels");
if (!pixs)
return (PIX *)ERROR_PTR("pixs not defined", procName, NULL);
if (pixGetDepth(pixs) != 32)
return (PIX *)ERROR_PTR("pixs must be 32 bpp", procName, NULL);
if (!cqcaa)
return (PIX *)ERROR_PTR("cqcaa not defined", procName, NULL);
/* Make output 8 bpp palette image */
pixGetDimensions(pixs, &w, &h, NULL);
datas = pixGetData(pixs);
wpls = pixGetWpl(pixs);
if ((pixd = pixCreate(w, h, 8)) == NULL)
return (PIX *)ERROR_PTR("pixd not made", procName, NULL);
pixCopyResolution(pixd, pixs);
pixCopyInputFormat(pixd, pixs);
datad = pixGetData(pixd);
wpld = pixGetWpl(pixd);
/* Make the canonical index tables */
rtab = gtab = btab = NULL;
makeRGBToIndexTables(CqNLevels, &rtab, >ab, &btab);
/* Traverse tree from root, looking for lowest cube
* that is a leaf, and set dest pix to its
* colortable index value. The results are far
* better when dithering to get a more accurate
* average color. */
if (ditherflag == 0) { /* no dithering */
for (i = 0; i < h; i++) {
lines = datas + i * wpls;
lined = datad + i * wpld;
for (j = 0; j < w; j++) {
extractRGBValues(lines[j], &rval, &gval, &bval);
octindex = rtab[rval] | gtab[gval] | btab[bval];
octreeFindColorCell(octindex, cqcaa, &index, &rc, &gc, &bc);
SET_DATA_BYTE(lined, j, index);
}
}
} else { /* Dither */
success = TRUE;
bufu8r = bufu8g = bufu8b = NULL;
buf1r = buf1g = buf1b = buf2r = buf2g = buf2b = NULL;
bufu8r = (l_uint8 *)LEPT_CALLOC(w, sizeof(l_uint8));
bufu8g = (l_uint8 *)LEPT_CALLOC(w, sizeof(l_uint8));
bufu8b = (l_uint8 *)LEPT_CALLOC(w, sizeof(l_uint8));
buf1r = (l_int32 *)LEPT_CALLOC(w, sizeof(l_int32));
buf1g = (l_int32 *)LEPT_CALLOC(w, sizeof(l_int32));
buf1b = (l_int32 *)LEPT_CALLOC(w, sizeof(l_int32));
buf2r = (l_int32 *)LEPT_CALLOC(w, sizeof(l_int32));
buf2g = (l_int32 *)LEPT_CALLOC(w, sizeof(l_int32));
buf2b = (l_int32 *)LEPT_CALLOC(w, sizeof(l_int32));
if (!bufu8r || !bufu8g || !bufu8b || !buf1r || !buf1g ||
!buf1b || !buf2r || !buf2g || !buf2b) {
L_ERROR("buffer not made\n", procName);
success = FALSE;
goto buffer_cleanup;
}
/* Start by priming buf2; line 1 is above line 2 */
pixGetRGBLine(pixs, 0, bufu8r, bufu8g, bufu8b);
for (j = 0; j < w; j++) {
buf2r[j] = 64 * bufu8r[j];
buf2g[j] = 64 * bufu8g[j];
buf2b[j] = 64 * bufu8b[j];
}
for (i = 0; i < h - 1; i++) {
/* Swap data 2 --> 1, and read in new line 2 */
memcpy(buf1r, buf2r, 4 * w);
memcpy(buf1g, buf2g, 4 * w);
memcpy(buf1b, buf2b, 4 * w);
pixGetRGBLine(pixs, i + 1, bufu8r, bufu8g, bufu8b);
for (j = 0; j < w; j++) {
buf2r[j] = 64 * bufu8r[j];
buf2g[j] = 64 * bufu8g[j];
buf2b[j] = 64 * bufu8b[j];
}
/* Dither */
lined = datad + i * wpld;
for (j = 0; j < w - 1; j++) {
rval = buf1r[j] / 64;
gval = buf1g[j] / 64;
bval = buf1b[j] / 64;
octindex = rtab[rval] | gtab[gval] | btab[bval];
octreeFindColorCell(octindex, cqcaa, &index, &rc, &gc, &bc);
SET_DATA_BYTE(lined, j, index);
dif = buf1r[j] / 8 - 8 * rc;
if (dif != 0) {
val1 = buf1r[j + 1] + 3 * dif;
val2 = buf2r[j] + 3 * dif;
val3 = buf2r[j + 1] + 2 * dif;
if (dif > 0) {
buf1r[j + 1] = L_MIN(16383, val1);
buf2r[j] = L_MIN(16383, val2);
buf2r[j + 1] = L_MIN(16383, val3);
} else {
buf1r[j + 1] = L_MAX(0, val1);
buf2r[j] = L_MAX(0, val2);
buf2r[j + 1] = L_MAX(0, val3);
}
}
dif = buf1g[j] / 8 - 8 * gc;
if (dif != 0) {
val1 = buf1g[j + 1] + 3 * dif;
val2 = buf2g[j] + 3 * dif;
val3 = buf2g[j + 1] + 2 * dif;
if (dif > 0) {
buf1g[j + 1] = L_MIN(16383, val1);
buf2g[j] = L_MIN(16383, val2);
buf2g[j + 1] = L_MIN(16383, val3);
} else {
buf1g[j + 1] = L_MAX(0, val1);
buf2g[j] = L_MAX(0, val2);
buf2g[j + 1] = L_MAX(0, val3);
}
}
dif = buf1b[j] / 8 - 8 * bc;
if (dif != 0) {
val1 = buf1b[j + 1] + 3 * dif;
val2 = buf2b[j] + 3 * dif;
val3 = buf2b[j + 1] + 2 * dif;
if (dif > 0) {
buf1b[j + 1] = L_MIN(16383, val1);
buf2b[j] = L_MIN(16383, val2);
buf2b[j + 1] = L_MIN(16383, val3);
} else {
buf1b[j + 1] = L_MAX(0, val1);
buf2b[j] = L_MAX(0, val2);
buf2b[j + 1] = L_MAX(0, val3);
}
}
}
/* Get last pixel in row; no downward propagation */
rval = buf1r[w - 1] / 64;
gval = buf1g[w - 1] / 64;
bval = buf1b[w - 1] / 64;
octindex = rtab[rval] | gtab[gval] | btab[bval];
octreeFindColorCell(octindex, cqcaa, &index, &rc, &gc, &bc);
SET_DATA_BYTE(lined, w - 1, index);
}
/* Get last row of pixels; no leftward propagation */
lined = datad + (h - 1) * wpld;
for (j = 0; j < w; j++) {
rval = buf2r[j] / 64;
gval = buf2g[j] / 64;
bval = buf2b[j] / 64;
octindex = rtab[rval] | gtab[gval] | btab[bval];
octreeFindColorCell(octindex, cqcaa, &index, &rc, &gc, &bc);
SET_DATA_BYTE(lined, j, index);
}
buffer_cleanup:
LEPT_FREE(bufu8r);
LEPT_FREE(bufu8g);
LEPT_FREE(bufu8b);
LEPT_FREE(buf1r);
LEPT_FREE(buf1g);
LEPT_FREE(buf1b);
LEPT_FREE(buf2r);
LEPT_FREE(buf2g);
LEPT_FREE(buf2b);
if (!success) pixDestroy(&pixd);
}
LEPT_FREE(rtab);
LEPT_FREE(gtab);
LEPT_FREE(btab);
return pixd;
}
/*!
* \brief octreeFindColorCell()
*
* \param[in] octindex
* \param[in] cqcaa
* \param[out] pindex index of CTE; returned to set pixel value
* \param[out] prval of CTE
* \param[out] pgval of CTE
* \param[out] pbval of CTE
* \return 0 if OK; 1 on error
*
*
* Notes:
* (1) As this is in inner loop, we don't check input pointers!
* (2) This traverses from the root (well, actually from level 2,
* because the level 2 cubes are the largest CTE cubes),
* and finds the index number of the cell and the color values,
* which can be used either directly or in a (Floyd-Steinberg)
* error-diffusion dithering algorithm.
*
*/
static l_int32
octreeFindColorCell(l_int32 octindex,
CQCELL ***cqcaa,
l_int32 *pindex,
l_int32 *prval,
l_int32 *pgval,
l_int32 *pbval)
{
l_int32 level;
l_int32 baseindex, subindex;
CQCELL *cqc, *cqcsub;
/* Use rgb values stored in the cubes; a little faster */
for (level = 2; level < CqNLevels; level++) {
getOctcubeIndices(octindex, level, &baseindex, &subindex);
cqc = cqcaa[level][baseindex];
cqcsub = cqcaa[level + 1][subindex];
if (cqcsub->bleaf == 0) { /* use cell at level above */
*pindex = cqc->index;
*prval = cqc->rc;
*pgval = cqc->gc;
*pbval = cqc->bc;
break;
} else if (level == CqNLevels - 1) { /* reached the bottom */
*pindex = cqcsub->index;
*prval = cqcsub->rc;
*pgval = cqcsub->gc;
*pbval = cqcsub->bc;
break;
}
}
#if 0
/* Generate rgb values for each cube on the fly; slower */
for (level = 2; level < CqNLevels; level++) {
l_int32 rv, gv, bv;
getOctcubeIndices(octindex, level, &baseindex, &subindex);
cqc = cqcaa[level][baseindex];
cqcsub = cqcaa[level + 1][subindex];
if (cqcsub->bleaf == 0) { /* use cell at level above */
getRGBFromOctcube(baseindex, level, &rv, &gv, &bv);
*pindex = cqc->index;
*prval = rv;
*pgval = gv;
*pbval = bv;
break;
} else if (level == CqNLevels - 1) { /* reached the bottom */
getRGBFromOctcube(subindex, level + 1, &rv, &gv, &bv);
*pindex = cqcsub->index;
*prval = rv;
*pgval = gv;
*pbval = bv;
break;
}
}
#endif
return 0;
}
/*------------------------------------------------------------------*
* Helper cqcell functions *
*------------------------------------------------------------------*/
/*!
* \brief cqcellTreeCreate()
*
* \return cqcell array tree
*/
static CQCELL ***
cqcellTreeCreate(void)
{
l_int32 level, ncells, i;
CQCELL ***cqcaa;
CQCELL **cqca; /* one array for each octree level */
PROCNAME("cqcellTreeCreate");
/* Make array of accumulation cell arrays from levels 1 to 5 */
if ((cqcaa = (CQCELL ***)LEPT_CALLOC(CqNLevels + 1, sizeof(CQCELL **)))
== NULL)
return (CQCELL ***)ERROR_PTR("cqcaa not made", procName, NULL);
for (level = 0; level <= CqNLevels; level++) {
ncells = 1 << (3 * level);
if ((cqca = (CQCELL **)LEPT_CALLOC(ncells, sizeof(CQCELL *))) == NULL) {
cqcellTreeDestroy(&cqcaa);
return (CQCELL ***)ERROR_PTR("cqca not made", procName, NULL);
}
cqcaa[level] = cqca;
for (i = 0; i < ncells; i++) {
if ((cqca[i] = (CQCELL *)LEPT_CALLOC(1, sizeof(CQCELL))) == NULL) {
cqcellTreeDestroy(&cqcaa);
return (CQCELL ***)ERROR_PTR("cqc not made", procName, NULL);
}
}
}
return cqcaa;
}
/*!
* \brief cqcellTreeDestroy()
*
* \param[in,out] pcqcaa will be set to null before returning
*/
static void
cqcellTreeDestroy(CQCELL ****pcqcaa)
{
l_int32 level, ncells, i;
CQCELL ***cqcaa;
CQCELL **cqca;
PROCNAME("cqcellTreeDestroy");
if (pcqcaa == NULL) {
L_WARNING("ptr address is NULL\n", procName);
return;
}
if ((cqcaa = *pcqcaa) == NULL)
return;
for (level = 0; level <= CqNLevels; level++) {
cqca = cqcaa[level];
ncells = 1 << (3 * level);
for (i = 0; i < ncells; i++)
LEPT_FREE(cqca[i]);
LEPT_FREE(cqca);
}
LEPT_FREE(cqcaa);
*pcqcaa = NULL;
return;
}
/*------------------------------------------------------------------*
* Helper index functions *
*------------------------------------------------------------------*/
/*!
* \brief makeRGBToIndexTables()
*
* \param[in] cqlevels can be 1, 2, 3, 4, 5 or 6
* \param[out] prtab, pgtab, pbtab tables
* \return 0 if OK; 1 on error
*
*
* Set up tables. e.g., for cqlevels = 5, we need an integer 0 < i < 2^15:
* rtab = 0 i7 0 0 i6 0 0 i5 0 0 i4 0 0 i3 0 0
* gtab = 0 0 i7 0 0 i6 0 0 i5 0 0 i4 0 0 i3 0
* btab = 0 0 0 i7 0 0 i6 0 0 i5 0 0 i4 0 0 i3
*
* The tables are then used to map from rbg --> index as follows:
* index = 0 r7 g7 b7 r6 g6 b6 r5 g5 b5 r4 g4 b4 r3 g3 b3
*
* e.g., for cqlevels = 4, we map to
* index = 0 0 0 0 r7 g7 b7 r6 g6 b6 r5 g5 b5 r4 g4 b4
*
* This may look a bit strange. The notation 'r7' means the MSBit of
* the r value which has 8 bits, going down from r7 to r0.
* Keep in mind that r7 is actually the r component bit for level 1 of
* the octtree. Level 1 is composed of 8 octcubes, represented by
* the bits r7 g7 b7, which divide the entire color space into
* 8 cubes. At level 2, each of these 8 octcubes is further divided into
* 8 cubes, each labeled by the second most significant bits r6 g6 b6
* of the rgb color.
*
*/
l_ok
makeRGBToIndexTables(l_int32 cqlevels,
l_uint32 **prtab,
l_uint32 **pgtab,
l_uint32 **pbtab)
{
l_int32 i;
l_uint32 *rtab, *gtab, *btab;
PROCNAME("makeRGBToIndexTables");
if (cqlevels < 1 || cqlevels > 6)
return ERROR_INT("cqlevels must be in {1,...6}", procName, 1);
if (!prtab || !pgtab || !pbtab)
return ERROR_INT("not all &tabs defined", procName, 1);
rtab = (l_uint32 *)LEPT_CALLOC(256, sizeof(l_uint32));
gtab = (l_uint32 *)LEPT_CALLOC(256, sizeof(l_uint32));
btab = (l_uint32 *)LEPT_CALLOC(256, sizeof(l_uint32));
if (!rtab || !gtab || !btab)
return ERROR_INT("calloc fail for tab", procName, 1);
*prtab = rtab;
*pgtab = gtab;
*pbtab = btab;
switch (cqlevels)
{
case 1:
for (i = 0; i < 256; i++) {
rtab[i] = (i >> 5) & 0x0004;
gtab[i] = (i >> 6) & 0x0002;
btab[i] = (i >> 7);
}
break;
case 2:
for (i = 0; i < 256; i++) {
rtab[i] = ((i >> 2) & 0x0020) | ((i >> 4) & 0x0004);
gtab[i] = ((i >> 3) & 0x0010) | ((i >> 5) & 0x0002);
btab[i] = ((i >> 4) & 0x0008) | ((i >> 6) & 0x0001);
}
break;
case 3:
for (i = 0; i < 256; i++) {
rtab[i] = ((i << 1) & 0x0100) | ((i >> 1) & 0x0020) |
((i >> 3) & 0x0004);
gtab[i] = (i & 0x0080) | ((i >> 2) & 0x0010) |
((i >> 4) & 0x0002);
btab[i] = ((i >> 1) & 0x0040) | ((i >> 3) & 0x0008) |
((i >> 5) & 0x0001);
}
break;
case 4:
for (i = 0; i < 256; i++) {
rtab[i] = ((i << 4) & 0x0800) | ((i << 2) & 0x0100) |
(i & 0x0020) | ((i >> 2) & 0x0004);
gtab[i] = ((i << 3) & 0x0400) | ((i << 1) & 0x0080) |
((i >> 1) & 0x0010) | ((i >> 3) & 0x0002);
btab[i] = ((i << 2) & 0x0200) | (i & 0x0040) |
((i >> 2) & 0x0008) | ((i >> 4) & 0x0001);
}
break;
case 5:
for (i = 0; i < 256; i++) {
rtab[i] = ((i << 7) & 0x4000) | ((i << 5) & 0x0800) |
((i << 3) & 0x0100) | ((i << 1) & 0x0020) |
((i >> 1) & 0x0004);
gtab[i] = ((i << 6) & 0x2000) | ((i << 4) & 0x0400) |
((i << 2) & 0x0080) | (i & 0x0010) |
((i >> 2) & 0x0002);
btab[i] = ((i << 5) & 0x1000) | ((i << 3) & 0x0200) |
((i << 1) & 0x0040) | ((i >> 1) & 0x0008) |
((i >> 3) & 0x0001);
}
break;
case 6:
for (i = 0; i < 256; i++) {
rtab[i] = ((i << 10) & 0x20000) | ((i << 8) & 0x4000) |
((i << 6) & 0x0800) | ((i << 4) & 0x0100) |
((i << 2) & 0x0020) | (i & 0x0004);
gtab[i] = ((i << 9) & 0x10000) | ((i << 7) & 0x2000) |
((i << 5) & 0x0400) | ((i << 3) & 0x0080) |
((i << 1) & 0x0010) | ((i >> 1) & 0x0002);
btab[i] = ((i << 8) & 0x8000) | ((i << 6) & 0x1000) |
((i << 4) & 0x0200) | ((i << 2) & 0x0040) |
(i & 0x0008) | ((i >> 2) & 0x0001);
}
break;
default:
ERROR_INT("cqlevels not in [1...6]", procName, 1);
break;
}
return 0;
}
/*!
* \brief getOctcubeIndexFromRGB()
*
* \param[in] rval, gval, bval
* \param[in] rtab, gtab, btab generated with makeRGBToIndexTables()
* \param[out] pindex found index
* \return void
*
*
* Notes:
* No error checking!
*
*/
void
getOctcubeIndexFromRGB(l_int32 rval,
l_int32 gval,
l_int32 bval,
l_uint32 *rtab,
l_uint32 *gtab,
l_uint32 *btab,
l_uint32 *pindex)
{
*pindex = rtab[rval] | gtab[gval] | btab[bval];
return;
}
/*!
* \brief getRGBFromOctcube()
*
* \param[in] cubeindex octcube index
* \param[in] level at which index is expressed
* \param[out] prval r val of this cube
* \param[out] pgval g val of this cube
* \param[out] pbval b val of this cube
* \return void
*
*
* Notes:
* (1) We can consider all octcube indices to represent a
* specific point in color space: namely, the location
* of the 'upper-left' corner of the cube, where indices
* increase down and to the right. The upper left corner
* of the color space is then 00000....
* (2) The 'rgbindex' is a 24-bit representation of the location,
* in octcube notation, at the center of the octcube.
* To get to the center of an octcube, you choose the 111
* octcube at the next lower level.
* (3) For example, if the octcube index = 110101 (binary),
* which is a level 2 expression, then the rgbindex
* is the 24-bit representation of 110101111 (at level 3);
* namely, 000110101111000000000000. The number is padded
* with 3 leading 0s (because the representation uses
* only 21 bits) and 12 trailing 0s (the default for
* levels 4-7, which are contained within each of the level3
* octcubes. Then the rgb values for the center of the
* octcube are: rval = 11100000, gval = 10100000, bval = 01100000
*
*/
static void
getRGBFromOctcube(l_int32 cubeindex,
l_int32 level,
l_int32 *prval,
l_int32 *pgval,
l_int32 *pbval)
{
l_int32 rgbindex;
/* Bring to format in 21 bits: (r7 g7 b7 r6 g6 b6 ...) */
/* This is valid for levels from 0 to 6 */
rgbindex = cubeindex << (3 * (7 - level)); /* upper corner of cube */
rgbindex |= (0x7 << (3 * (6 - level))); /* index to center of cube */
/* Extract separate pieces */
*prval = ((rgbindex >> 13) & 0x80) |
((rgbindex >> 11) & 0x40) |
((rgbindex >> 9) & 0x20) |
((rgbindex >> 7) & 0x10) |
((rgbindex >> 5) & 0x08) |
((rgbindex >> 3) & 0x04) |
((rgbindex >> 1) & 0x02);
*pgval = ((rgbindex >> 12) & 0x80) |
((rgbindex >> 10) & 0x40) |
((rgbindex >> 8) & 0x20) |
((rgbindex >> 6) & 0x10) |
((rgbindex >> 4) & 0x08) |
((rgbindex >> 2) & 0x04) |
(rgbindex & 0x02);
*pbval = ((rgbindex >> 11) & 0x80) |
((rgbindex >> 9) & 0x40) |
((rgbindex >> 7) & 0x20) |
((rgbindex >> 5) & 0x10) |
((rgbindex >> 3) & 0x08) |
((rgbindex >> 1) & 0x04) |
((rgbindex << 1) & 0x02);
return;
}
/*!
* \brief getOctcubeIndices()
*
* \param[in] rgbindex
* \param[in] level octree level 0, 1, 2, 3, 4, 5
* \param[out] pbindex base index index at the octree level
* \param[out] psindex sub index index at the next lower level
* \return 0 if OK, 1 on error
*
*
* Notes:
* for CqNLevels = 6, the full RGB index is in the form:
* index = (0[13] 0 r7 g7 b7 r6 g6 b6 r5 g5 b5 r4 g4 b4 r3 g3 b3 r2 g2 b2)
* for CqNLevels = 5, the full RGB index is in the form:
* index = (0[16] 0 r7 g7 b7 r6 g6 b6 r5 g5 b5 r4 g4 b4 r3 g3 b3)
* for CqNLevels = 4, the full RGB index is in the form:
* index = (0[19] 0 r7 g7 b7 r6 g6 b6 r5 g5 b5 r4 g4 b4)
*
* The base index is the index of the octcube at the level given,
* whereas the sub index is the index at the next level down.
*
* For level 0: base index = 0
* sub index is the 3 bit number (r7 g7 b7)
* For level 1: base index = (r7 g7 b7)
* sub index = (r7 g7 b7 r6 g6 b6)
* For level 2: base index = (r7 g7 b7 r6 g6 b6)
* sub index = (r7 g7 b7 r6 g6 b6 r5 g5 b5)
* For level 3: base index = (r7 g7 b7 r6 g6 b6 r5 g5 b5)
* sub index = (r7 g7 b7 r6 g6 b6 r5 g5 b5 r4 g4 b4)
* For level 4: base index = (r7 g7 b7 r6 g6 b6 r5 g5 b5 r4 g4 b4)
* sub index = (r7 g7 b7 r6 g6 b6 r5 g5 b5 r4 g4 b4 r3 g3 b3)
* For level 5: base index = (r7 g7 b7 r6 g6 b6 r5 g5 b5 r4 g4 b4 r3 g3 b3)
* sub index = (r7 g7 b7 r6 g6 b6 r5 g5 b5 r4 g4 b4 r3 g3 b3
* r2 g2 b2)
*
*/
static l_int32
getOctcubeIndices(l_int32 rgbindex,
l_int32 level,
l_int32 *pbindex,
l_int32 *psindex)
{
PROCNAME("getOctcubeIndex");
if (level < 0 || level > CqNLevels - 1)
return ERROR_INT("level must be in e.g., [0 ... 5]", procName, 1);
if (!pbindex)
return ERROR_INT("&bindex not defined", procName, 1);
if (!psindex)
return ERROR_INT("&sindex not defined", procName, 1);
*pbindex = rgbindex >> (3 * (CqNLevels - level));
*psindex = rgbindex >> (3 * (CqNLevels - 1 - level));
return 0;
}
/*!
* \brief octcubeGetCount()
*
* \param[in] level valid values are in [1,...6]; there are 2^level
* cubes along each side of the rgb cube
* \param[out] psize 2^(3 * level) cubes in the entire rgb cube
* \return 0 if OK, 1 on error. Caller must check!
*
*
* level: 1 2 3 4 5 6
* size: 8 64 512 4098 32784 262272
*
*/
static l_int32
octcubeGetCount(l_int32 level,
l_int32 *psize)
{
PROCNAME("octcubeGetCount");
if (!psize)
return ERROR_INT("&size not defined", procName, 1);
if (level < 1 || level > 6)
return ERROR_INT("invalid level", procName, 1);
*psize = 1 << (3 * level);
return 0;
}
/*---------------------------------------------------------------------------*
* Adaptive octree quantization based on population at a fixed level *
*---------------------------------------------------------------------------*/
/*!
* \brief pixOctreeQuantByPopulation()
*
* \param[in] pixs 32 bpp rgb
* \param[in] level significant bits for each of RGB; valid for {3,4}.
* Use 0 for default (level 4; recommended
* \param[in] ditherflag 1 to dither, 0 otherwise
* \return pixd quantized to octcubes or NULL on error
*
*
* Notes:
* (1) This color quantization method works very well without
* dithering, using octcubes at two different levels:
* (a) the input %level, which is either 3 or 4
* (b) level 2 (64 octcubes to cover the entire color space)
* (2) For best results, using %level = 4 is recommended.
* Why do we provide an option for using level 3? Because
* there are 512 octcubes at level 3, and for many images
* not more than 256 are filled. As a result, on some images
* a very accurate quantized representation is possible using
* %level = 3.
* (3) This first breaks up the color space into octcubes at the
* input %level, and computes, for each octcube, the average
* value of the pixels that are in it.
* (4) Then there are two possible situations:
* (a) If there are not more than 256 populated octcubes,
* it returns a cmapped pix with those values assigned.
* (b) Otherwise, it selects 192 octcubes containing the largest
* number of pixels and quantizes pixels within those octcubes
* to their average. Then, to handle the residual pixels
* that are not in those 192 octcubes, it generates a
* level 2 octree consisting of 64 octcubes, and within
* each octcube it quantizes the residual pixels to their
* average within each of those level 2 octcubes.
* (5) Unpopulated level 2 octcubes are represented in the colormap
* by their centers. This, of course, has no effect unless
* dithering is used for the output image.
* (6) The depth of pixd is the minimum required to support the
* number of colors found at %level; namely, 2, 4 or 8.
* (7) This function works particularly well on images such as maps,
* where there are a relatively small number of well-populated
* colors, but due to antialiasing and compression artifacts
* there may be a large number of different colors. This will
* pull out and represent accurately the highly populated colors,
* while still making a reasonable approximation for the others.
* (8) The highest level of octcubes allowed is 4. Use of higher
* levels typically results in having a small fraction of
* pixels in the most populated 192 octcubes. As a result,
* most of the pixels are represented at level 2, which is
* not sufficiently accurate.
* (9) Dithering shows artifacts on some images. If you plan to
* dither, pixOctreeColorQuant() and pixFixedOctcubeQuant256()
* usually give better results.
*
*/
PIX *
pixOctreeQuantByPopulation(PIX *pixs,
l_int32 level,
l_int32 ditherflag)
{
l_int32 w, h, wpls, wpld, i, j, depth, size, ncolors, index;
l_int32 rval, gval, bval;
l_int32 *rarray, *garray, *barray, *narray, *iarray;
l_uint32 octindex, octindex2;
l_uint32 *rtab, *gtab, *btab, *rtab2, *gtab2, *btab2;
l_uint32 *lines, *lined, *datas, *datad;
L_OCTCUBE_POP *opop;
L_HEAP *lh;
PIX *pixd;
PIXCMAP *cmap;
PROCNAME("pixOctreeQuantByPopulation");
if (!pixs)
return (PIX *)ERROR_PTR("pixs not defined", procName, NULL);
if (pixGetDepth(pixs) != 32)
return (PIX *)ERROR_PTR("pixs not 32 bpp", procName, NULL);
if (level == 0) level = 4;
if (level < 3 || level > 4)
return (PIX *)ERROR_PTR("level not in {3,4}", procName, NULL);
/* Do not dither if image is very small */
pixGetDimensions(pixs, &w, &h, NULL);
if (w < MinDitherSize && h < MinDitherSize && ditherflag == 1) {
L_INFO("Small image: dithering turned off\n", procName);
ditherflag = 0;
}
if (octcubeGetCount(level, &size)) /* array size = 2 ** (3 * level) */
return (PIX *)ERROR_PTR("size not returned", procName, NULL);
rtab = gtab = btab = NULL;
makeRGBToIndexTables(level, &rtab, >ab, &btab);
pixd = NULL;
narray = (l_int32 *)LEPT_CALLOC(size, sizeof(l_int32));
rarray = (l_int32 *)LEPT_CALLOC(size, sizeof(l_int32));
garray = (l_int32 *)LEPT_CALLOC(size, sizeof(l_int32));
barray = (l_int32 *)LEPT_CALLOC(size, sizeof(l_int32));
if (!narray || !rarray || !garray || !barray)
goto array_cleanup;
/* Place the pixels in octcube leaves. */
datas = pixGetData(pixs);
wpls = pixGetWpl(pixs);
for (i = 0; i < h; i++) {
lines = datas + i * wpls;
for (j = 0; j < w; j++) {
extractRGBValues(lines[j], &rval, &gval, &bval);
octindex = rtab[rval] | gtab[gval] | btab[bval];
narray[octindex]++;
rarray[octindex] += rval;
garray[octindex] += gval;
barray[octindex] += bval;
}
}
/* Find the number of different colors */
for (i = 0, ncolors = 0; i < size; i++) {
if (narray[i] > 0)
ncolors++;
}
if (ncolors <= 4)
depth = 2;
else if (ncolors <= 16)
depth = 4;
else
depth = 8;
pixd = pixCreate(w, h, depth);
datad = pixGetData(pixd);
wpld = pixGetWpl(pixd);
pixCopyResolution(pixd, pixs);
pixCopyInputFormat(pixd, pixs);
cmap = pixcmapCreate(depth);
pixSetColormap(pixd, cmap);
/* Average the colors in each octcube leaf. */
for (i = 0; i < size; i++) {
if (narray[i] > 0) {
rarray[i] /= narray[i];
garray[i] /= narray[i];
barray[i] /= narray[i];
}
}
/* If ncolors <= 256, finish immediately. Do not dither.
* Re-use narray to hold the colormap index + 1 */
if (ncolors <= 256) {
for (i = 0, index = 0; i < size; i++) {
if (narray[i] > 0) {
pixcmapAddColor(cmap, rarray[i], garray[i], barray[i]);
narray[i] = index + 1; /* to avoid storing 0 */
index++;
}
}
/* Set the cmap indices for each pixel */
for (i = 0; i < h; i++) {
lines = datas + i * wpls;
lined = datad + i * wpld;
for (j = 0; j < w; j++) {
extractRGBValues(lines[j], &rval, &gval, &bval);
octindex = rtab[rval] | gtab[gval] | btab[bval];
switch (depth)
{
case 8:
SET_DATA_BYTE(lined, j, narray[octindex] - 1);
break;
case 4:
SET_DATA_QBIT(lined, j, narray[octindex] - 1);
break;
case 2:
SET_DATA_DIBIT(lined, j, narray[octindex] - 1);
break;
default:
L_WARNING("shouldn't get here\n", procName);
}
}
}
goto array_cleanup;
}
/* More complicated. Sort by decreasing population */
lh = lheapCreate(500, L_SORT_DECREASING);
for (i = 0; i < size; i++) {
if (narray[i] > 0) {
opop = (L_OCTCUBE_POP *)LEPT_CALLOC(1, sizeof(L_OCTCUBE_POP));
opop->npix = (l_float32)narray[i];
opop->index = i;
opop->rval = rarray[i];
opop->gval = garray[i];
opop->bval = barray[i];
lheapAdd(lh, opop);
}
}
/* Take the top 192. These will form the first 192 colors
* in the cmap. iarray[i] holds the index into the cmap. */
iarray = (l_int32 *)LEPT_CALLOC(size, sizeof(l_int32));
for (i = 0; i < 192; i++) {
opop = (L_OCTCUBE_POP*)lheapRemove(lh);
if (!opop) break;
pixcmapAddColor(cmap, opop->rval, opop->gval, opop->bval);
iarray[opop->index] = i + 1; /* +1 to avoid storing 0 */
#if DEBUG_POP
lept_stderr("i = %d, n = %6.0f, (r,g,b) = (%d %d %d)\n",
i, opop->npix, opop->rval, opop->gval, opop->bval);
#endif /* DEBUG_POP */
LEPT_FREE(opop);
}
/* Make the octindex tables for level 2, and reuse rarray, etc. */
rtab2 = gtab2 = btab2 = NULL;
makeRGBToIndexTables(2, &rtab2, >ab2, &btab2);
for (i = 0; i < 64; i++) {
narray[i] = 0;
rarray[i] = 0;
garray[i] = 0;
barray[i] = 0;
}
/* Take the rest of the occupied octcubes, assigning the pixels
* to these new colormap indices. iarray[] is addressed
* by %level octcube indices, and it now holds the
* colormap indices for all pixels in pixs. */
for (i = 192; i < size; i++) {
opop = (L_OCTCUBE_POP*)lheapRemove(lh);
if (!opop) break;
rval = opop->rval;
gval = opop->gval;
bval = opop->bval;
octindex2 = rtab2[rval] | gtab2[gval] | btab2[bval];
narray[octindex2] += (l_int32)opop->npix;
rarray[octindex2] += (l_int32)opop->npix * rval;
garray[octindex2] += (l_int32)opop->npix * gval;
barray[octindex2] += (l_int32)opop->npix * bval;
iarray[opop->index] = 192 + octindex2 + 1; /* +1 to avoid storing 0 */
LEPT_FREE(opop);
}
lheapDestroy(&lh, TRUE);
/* To span the full color space, which is necessary for dithering,
* set each iarray element whose value is still 0 at the input
* level octcube leaves (because there were no pixels in those
* octcubes) to the colormap index corresponding to its level 2
* octcube. */
if (ditherflag) {
for (i = 0; i < size; i++) {
if (iarray[i] == 0) {
getRGBFromOctcube(i, level, &rval, &gval, &bval);
octindex2 = rtab2[rval] | gtab2[gval] | btab2[bval];
iarray[i] = 192 + octindex2 + 1;
}
}
}
LEPT_FREE(rtab2);
LEPT_FREE(gtab2);
LEPT_FREE(btab2);
/* Average the colors from the residuals in each level 2 octcube,
* and add these 64 values to the colormap. */
for (i = 0; i < 64; i++) {
if (narray[i] > 0) {
rarray[i] /= narray[i];
garray[i] /= narray[i];
barray[i] /= narray[i];
} else { /* no pixels in this octcube; use center value */
getRGBFromOctcube(i, 2, &rarray[i], &garray[i], &barray[i]);
}
pixcmapAddColor(cmap, rarray[i], garray[i], barray[i]);
}
/* Set the cmap indices for each pixel. Subtract 1 from
* the value in iarray[] because we added 1 earlier. */
if (ditherflag == 0) {
for (i = 0; i < h; i++) {
lines = datas + i * wpls;
lined = datad + i * wpld;
for (j = 0; j < w; j++) {
extractRGBValues(lines[j], &rval, &gval, &bval);
octindex = rtab[rval] | gtab[gval] | btab[bval];
SET_DATA_BYTE(lined, j, iarray[octindex] - 1);
}
}
} else { /* dither */
pixDitherOctindexWithCmap(pixs, pixd, rtab, gtab, btab,
iarray, POP_DIF_CAP);
}
#if DEBUG_POP
for (i = 0; i < size / 16; i++) {
l_int32 j;
for (j = 0; j < 16; j++)
lept_stderr("%d ", iarray[16 * i + j]);
lept_stderr("\n");
}
#endif /* DEBUG_POP */
LEPT_FREE(iarray);
array_cleanup:
LEPT_FREE(narray);
LEPT_FREE(rarray);
LEPT_FREE(garray);
LEPT_FREE(barray);
LEPT_FREE(rtab);
LEPT_FREE(gtab);
LEPT_FREE(btab);
return pixd;
}
/*!
* \brief pixDitherOctindexWithCmap()
*
* \param[in] pixs 32 bpp rgb
* \param[in] pixd 8 bpp cmapped
* \param[in] rtab, gtab, btab tables from rval to octindex
* \param[in] indexmap array mapping octindex to cmap index
* \param[in] difcap max allowed dither transfer;
* use 0 for infinite cap
* \return 0 if OK, 1 on error
*
*
* Notes:
* (1) This performs dithering to generate the colormap indices
* in pixd. The colormap has been calculated, along with
* four input LUTs that together give the inverse colormapping
* from RGB to colormap index.
* (2) For pixOctreeQuantByPopulation(), %indexmap maps from the
* standard octindex to colormap index (after subtracting 1).
* The basic pixel-level function, without dithering, is:
* extractRGBValues(lines[j], &rval, &gval, &bval);
* octindex = rtab[rval] | gtab[gval] | btab[bval];
* SET_DATA_BYTE(lined, j, indexmap[octindex] - 1);
* (3) This can be used in any situation where the general
* prescription for finding the colormap index from the rgb
* value is precisely this:
* cmapindex = indexmap[rtab[rval] | gtab[gval] | btab[bval]] - 1
* For example, in pixFixedOctcubeQuant256(), we don't use
* standard octcube indexing, the rtab (etc) LUTs map directly
* to the colormap index, and %indexmap just compensates for
* the 1-off indexing assumed to be in that table.
*
*/
static l_int32
pixDitherOctindexWithCmap(PIX *pixs,
PIX *pixd,
l_uint32 *rtab,
l_uint32 *gtab,
l_uint32 *btab,
l_int32 *indexmap,
l_int32 difcap)
{
l_uint8 *bufu8r, *bufu8g, *bufu8b;
l_int32 i, j, w, h, wpld, octindex, cmapindex, success;
l_int32 rval, gval, bval, rc, gc, bc;
l_int32 dif, val1, val2, val3;
l_int32 *buf1r, *buf1g, *buf1b, *buf2r, *buf2g, *buf2b;
l_uint32 *datad, *lined;
PIXCMAP *cmap;
PROCNAME("pixDitherOctindexWithCmap");
if (!pixs || pixGetDepth(pixs) != 32)
return ERROR_INT("pixs undefined or not 32 bpp", procName, 1);
if (!pixd || pixGetDepth(pixd) != 8)
return ERROR_INT("pixd undefined or not 8 bpp", procName, 1);
if ((cmap = pixGetColormap(pixd)) == NULL)
return ERROR_INT("pixd not cmapped", procName, 1);
if (!rtab || !gtab || !btab || !indexmap)
return ERROR_INT("not all 4 tables defined", procName, 1);
pixGetDimensions(pixs, &w, &h, NULL);
if (pixGetWidth(pixd) != w || pixGetHeight(pixd) != h)
return ERROR_INT("pixs and pixd not same size", procName, 1);
success = TRUE;
bufu8r = bufu8g = bufu8b = NULL;
buf1r = buf1g = buf1b = buf2r = buf2g = buf2b = NULL;
bufu8r = (l_uint8 *)LEPT_CALLOC(w, sizeof(l_uint8));
bufu8g = (l_uint8 *)LEPT_CALLOC(w, sizeof(l_uint8));
bufu8b = (l_uint8 *)LEPT_CALLOC(w, sizeof(l_uint8));
buf1r = (l_int32 *)LEPT_CALLOC(w, sizeof(l_int32));
buf1g = (l_int32 *)LEPT_CALLOC(w, sizeof(l_int32));
buf1b = (l_int32 *)LEPT_CALLOC(w, sizeof(l_int32));
buf2r = (l_int32 *)LEPT_CALLOC(w, sizeof(l_int32));
buf2g = (l_int32 *)LEPT_CALLOC(w, sizeof(l_int32));
buf2b = (l_int32 *)LEPT_CALLOC(w, sizeof(l_int32));
if (!bufu8r || !bufu8g || !bufu8b || !buf1r || !buf1g ||
!buf1b || !buf2r || !buf2g || !buf2b) {
L_ERROR("buffer not made\n", procName);
success = FALSE;
goto buffer_cleanup;
}
/* Start by priming buf2; line 1 is above line 2 */
pixGetRGBLine(pixs, 0, bufu8r, bufu8g, bufu8b);
for (j = 0; j < w; j++) {
buf2r[j] = 64 * bufu8r[j];
buf2g[j] = 64 * bufu8g[j];
buf2b[j] = 64 * bufu8b[j];
}
datad = pixGetData(pixd);
wpld = pixGetWpl(pixd);
for (i = 0; i < h - 1; i++) {
/* Swap data 2 --> 1, and read in new line 2 */
memcpy(buf1r, buf2r, 4 * w);
memcpy(buf1g, buf2g, 4 * w);
memcpy(buf1b, buf2b, 4 * w);
pixGetRGBLine(pixs, i + 1, bufu8r, bufu8g, bufu8b);
for (j = 0; j < w; j++) {
buf2r[j] = 64 * bufu8r[j];
buf2g[j] = 64 * bufu8g[j];
buf2b[j] = 64 * bufu8b[j];
}
/* Dither */
lined = datad + i * wpld;
for (j = 0; j < w - 1; j++) {
rval = buf1r[j] / 64;
gval = buf1g[j] / 64;
bval = buf1b[j] / 64;
octindex = rtab[rval] | gtab[gval] | btab[bval];
cmapindex = indexmap[octindex] - 1;
SET_DATA_BYTE(lined, j, cmapindex);
pixcmapGetColor(cmap, cmapindex, &rc, &gc, &bc);
dif = buf1r[j] / 8 - 8 * rc;
if (difcap > 0) {
if (dif > difcap) dif = difcap;
if (dif < -difcap) dif = -difcap;
}
if (dif != 0) {
val1 = buf1r[j + 1] + 3 * dif;
val2 = buf2r[j] + 3 * dif;
val3 = buf2r[j + 1] + 2 * dif;
if (dif > 0) {
buf1r[j + 1] = L_MIN(16383, val1);
buf2r[j] = L_MIN(16383, val2);
buf2r[j + 1] = L_MIN(16383, val3);
} else {
buf1r[j + 1] = L_MAX(0, val1);
buf2r[j] = L_MAX(0, val2);
buf2r[j + 1] = L_MAX(0, val3);
}
}
dif = buf1g[j] / 8 - 8 * gc;
if (difcap > 0) {
if (dif > difcap) dif = difcap;
if (dif < -difcap) dif = -difcap;
}
if (dif != 0) {
val1 = buf1g[j + 1] + 3 * dif;
val2 = buf2g[j] + 3 * dif;
val3 = buf2g[j + 1] + 2 * dif;
if (dif > 0) {
buf1g[j + 1] = L_MIN(16383, val1);
buf2g[j] = L_MIN(16383, val2);
buf2g[j + 1] = L_MIN(16383, val3);
} else {
buf1g[j + 1] = L_MAX(0, val1);
buf2g[j] = L_MAX(0, val2);
buf2g[j + 1] = L_MAX(0, val3);
}
}
dif = buf1b[j] / 8 - 8 * bc;
if (difcap > 0) {
if (dif > difcap) dif = difcap;
if (dif < -difcap) dif = -difcap;
}
if (dif != 0) {
val1 = buf1b[j + 1] + 3 * dif;
val2 = buf2b[j] + 3 * dif;
val3 = buf2b[j + 1] + 2 * dif;
if (dif > 0) {
buf1b[j + 1] = L_MIN(16383, val1);
buf2b[j] = L_MIN(16383, val2);
buf2b[j + 1] = L_MIN(16383, val3);
} else {
buf1b[j + 1] = L_MAX(0, val1);
buf2b[j] = L_MAX(0, val2);
buf2b[j + 1] = L_MAX(0, val3);
}
}
}
/* Get last pixel in row; no downward propagation */
rval = buf1r[w - 1] / 64;
gval = buf1g[w - 1] / 64;
bval = buf1b[w - 1] / 64;
octindex = rtab[rval] | gtab[gval] | btab[bval];
cmapindex = indexmap[octindex] - 1;
SET_DATA_BYTE(lined, w - 1, cmapindex);
}
/* Get last row of pixels; no leftward propagation */
lined = datad + (h - 1) * wpld;
for (j = 0; j < w; j++) {
rval = buf2r[j] / 64;
gval = buf2g[j] / 64;
bval = buf2b[j] / 64;
octindex = rtab[rval] | gtab[gval] | btab[bval];
cmapindex = indexmap[octindex] - 1;
SET_DATA_BYTE(lined, j, cmapindex);
}
buffer_cleanup:
LEPT_FREE(bufu8r);
LEPT_FREE(bufu8g);
LEPT_FREE(bufu8b);
LEPT_FREE(buf1r);
LEPT_FREE(buf1g);
LEPT_FREE(buf1b);
LEPT_FREE(buf2r);
LEPT_FREE(buf2g);
LEPT_FREE(buf2b);
return (success) ? 0 : 1;
}
/*---------------------------------------------------------------------------*
* Adaptive octree quantization to 4 and 8 bpp with max colors *
*---------------------------------------------------------------------------*/
/*!
* \brief pixOctreeQuantNumColors()
*
* \param[in] pixs 32 bpp rgb
* \param[in] maxcolors 8 to 256; the actual number of colors used
* may be less than this
* \param[in] subsample factor for computing color distribution;
* use 0 for default
* \return pixd 4 or 8 bpp, colormapped, or NULL on error
*
*
* pixOctreeColorQuant is very flexible in terms of the relative
* depth of different cubes of the octree. By contrast, this function,
* pixOctreeQuantNumColors is also adaptive, but it supports octcube
* leaves at only two depths: a smaller depth that guarantees
* full coverage of the color space and octcubes at one level
* deeper for more accurate colors. Its main virutes are simplicity
* and speed, which are both derived from the natural indexing of
* the octcubes from the RGB values.
*
* Before describing pixOctreeQuantNumColors, consider an even simpler
* approach for 4 bpp with either 8 or 16 colors. With 8 colors,
* you simply go to level 1 octcubes and use the average color
* found in each cube. For 16 colors, you find which of the three
* colors has the largest variance at the second level, and use two
* indices for that color. The result is quite poor, because 1 some
* of the cubes are nearly empty and 2 you don't get much color
* differentiation for the extra 8 colors. Trust me, this method may
* be simple, but it isn't worth anything.
*
* In pixOctreeQuantNumColors, we generate colormapped images at
* either 4 bpp or 8 bpp. For 4 bpp, we have a minimum of 8 colors
* for the level 1 octcubes, plus up to 8 additional colors that
* are determined from the level 2 popularity. If the number of colors
* is between 8 and 16, the output is a 4 bpp image. If the number of
* colors is greater than 16, the output is a 8 bpp image.
*
* We use a priority queue, implemented with a heap, to select the
* requisite number of most populated octcubes at the deepest level
* level 2 for 64 or fewer colors; level 3 for more than 64 colors.
* These are combined with one color for each octcube one level above,
* which is used to span the color space of octcubes that were not
* included at the deeper level.
*
* If the deepest level is 2, we combine the popular level 2 octcubes
* out of a total of 64 with the 8 level 1 octcubes. If the deepest
* level is 3, we combine the popular level 3 octcubes out of a
* total 512 with the 64 level 2 octcubes that span the color space.
* In the latter case, we require a minimum of 64 colors for the level 2
* octcubes, plus up to 192 additional colors determined from level 3
* popularity.
*
* The parameter 'maxlevel' is the deepest octcube level that is used.
* The implementation also uses two LUTs, which are employed in
* two successive traversals of the dest image. The first maps
* from the src octindex at 'maxlevel' to the color table index,
* which is the value that is stored in the 4 or 8 bpp dest pixel.
* The second LUT maps from that colormap value in the dest to a
* new colormap value for a minimum sized colormap, stored back in
* the dest. It is used to remove any color map entries that
* correspond to color space regions that have no pixels in the
* source image. These regions can be either from the higher level
* e.g., level 1 for 4 bpp, or from octcubes at 'maxlevel' that
* are unoccupied. This remapping results in the minimum number
* of colors used according to the constraints induced by the
* input 'maxcolors'. We also compute the average R, G and B color
* values in each region of the color space represented by a
* colormap entry, and store them in the colormap.
*
* The maximum number of colors is input, which determines the
* following properties of the dest image and octcube regions used:
*
* Number of colors dest image depth maxlevel
* ---------------- ---------------- --------
* 8 to 16 4 bpp 2
* 17 to 64 8 bpp 2
* 65 to 256 8 bpp 3
*
* It may turn out that the number of extra colors, beyond the
* minimum 8 and 64 for maxlevel 2 and 3, respectively, is larger
* than the actual number of occupied cubes at these levels
* In that case, all the pixels are contained in this
* subset of cubes at maxlevel, and no colormap colors are needed
* to represent the remainder pixels one level above. Thus, for
* example, in use one often finds that the pixels in an image
* occupy less than 192 octcubes at level 3, so they can be represented
* by a colormap for octcubes at level 3 only.
*
*/
PIX *
pixOctreeQuantNumColors(PIX *pixs,
l_int32 maxcolors,
l_int32 subsample)
{
l_int32 w, h, minside, bpp, wpls, wpld, i, j, actualcolors;
l_int32 rval, gval, bval, nbase, nextra, maxlevel, ncubes, val;
l_int32 *lut1, *lut2;
l_uint32 index;
l_uint32 *lines, *lined, *datas, *datad, *pspixel;
l_uint32 *rtab, *gtab, *btab;
OQCELL *oqc;
OQCELL **oqca;
L_HEAP *lh;
PIX *pixd;
PIXCMAP *cmap;
PROCNAME("pixOctreeQuantNumColors");
if (!pixs)
return (PIX *)ERROR_PTR("pixs not defined", procName, NULL);
if (pixGetDepth(pixs) != 32)
return (PIX *)ERROR_PTR("pixs not 32 bpp", procName, NULL);
if (maxcolors < 8) {
L_WARNING("max colors < 8; setting to 8\n", procName);
maxcolors = 8;
}
if (maxcolors > 256) {
L_WARNING("max colors > 256; setting to 256\n", procName);
maxcolors = 256;
}
pixGetDimensions(pixs, &w, &h, NULL);
datas = pixGetData(pixs);
wpls = pixGetWpl(pixs);
minside = L_MIN(w, h);
if (subsample <= 0) {
subsample = L_MAX(1, minside / 200);
}
if (maxcolors <= 16) {
bpp = 4;
pixd = pixCreate(w, h, bpp);
maxlevel = 2;
ncubes = 64; /* 2^6 */
nbase = 8;
nextra = maxcolors - nbase;
} else if (maxcolors <= 64) {
bpp = 8;
pixd = pixCreate(w, h, bpp);
maxlevel = 2;
ncubes = 64; /* 2^6 */
nbase = 8;
nextra = maxcolors - nbase;
} else { /* maxcolors <= 256 */
bpp = 8;
pixd = pixCreate(w, h, bpp);
maxlevel = 3;
ncubes = 512; /* 2^9 */
nbase = 64;
nextra = maxcolors - nbase;
}
pixCopyResolution(pixd, pixs);
pixCopyInputFormat(pixd, pixs);
/*----------------------------------------------------------*
* If we're using the minimum number of colors, it is *
* much simpler. We just use 'nbase' octcubes. *
* For this case, we don't eliminate any extra colors. *
*----------------------------------------------------------*/
if (nextra == 0) {
/* prepare the OctcubeQuantCell array */
if ((oqca = (OQCELL **)LEPT_CALLOC(nbase, sizeof(OQCELL *))) == NULL) {
pixDestroy(&pixd);
return (PIX *)ERROR_PTR("oqca not made", procName, NULL);
}
for (i = 0; i < nbase; i++) {
oqca[i] = (OQCELL *)LEPT_CALLOC(1, sizeof(OQCELL));
oqca[i]->n = 0.0;
}
rtab = gtab = btab = NULL;
makeRGBToIndexTables(maxlevel - 1, &rtab, >ab, &btab);
/* Go through the entire image, gathering statistics and
* assigning pixels to their quantized value */
datad = pixGetData(pixd);
wpld = pixGetWpl(pixd);
for (i = 0; i < h; i++) {
lines = datas + i * wpls;
lined = datad + i * wpld;
for (j = 0; j < w; j++) {
pspixel = lines + j;
extractRGBValues(*pspixel, &rval, &gval, &bval);
getOctcubeIndexFromRGB(rval, gval, bval,
rtab, gtab, btab, &index);
/* lept_stderr("rval = %d, gval = %d, bval = %d,"
" index = %d\n", rval, gval, bval, index); */
if (bpp == 4)
SET_DATA_QBIT(lined, j, index);
else /* bpp == 8 */
SET_DATA_BYTE(lined, j, index);
oqca[index]->n += 1.0;
oqca[index]->rcum += rval;
oqca[index]->gcum += gval;
oqca[index]->bcum += bval;
}
}
/* Compute average color values in each octcube, and
* generate colormap */
cmap = pixcmapCreate(bpp);
pixSetColormap(pixd, cmap);
for (i = 0; i < nbase; i++) {
oqc = oqca[i];
if (oqc->n != 0) {
oqc->rval = (l_int32)(oqc->rcum / oqc->n);
oqc->gval = (l_int32)(oqc->gcum / oqc->n);
oqc->bval = (l_int32)(oqc->bcum / oqc->n);
} else {
getRGBFromOctcube(i, maxlevel - 1, &oqc->rval,
&oqc->gval, &oqc->bval);
}
pixcmapAddColor(cmap, oqc->rval, oqc->gval, oqc->bval);
}
for (i = 0; i < nbase; i++)
LEPT_FREE(oqca[i]);
LEPT_FREE(oqca);
LEPT_FREE(rtab);
LEPT_FREE(gtab);
LEPT_FREE(btab);
return pixd;
}
/*------------------------------------------------------------*
* General case: we will use colors in octcubes at maxlevel. *
* We also remove any colors that are not populated from *
* the colormap. *
*------------------------------------------------------------*/
/* Prepare the OctcubeQuantCell array */
if ((oqca = (OQCELL **)LEPT_CALLOC(ncubes, sizeof(OQCELL *))) == NULL) {
pixDestroy(&pixd);
return (PIX *)ERROR_PTR("oqca not made", procName, NULL);
}
for (i = 0; i < ncubes; i++) {
oqca[i] = (OQCELL *)LEPT_CALLOC(1, sizeof(OQCELL));
oqca[i]->n = 0.0;
}
/* Make the tables to map color to the octindex,
* of which there are 'ncubes' at 'maxlevel' */
rtab = gtab = btab = NULL;
makeRGBToIndexTables(maxlevel, &rtab, >ab, &btab);
/* Estimate the color distribution; we want to find the
* most popular nextra colors at 'maxlevel' */
for (i = 0; i < h; i += subsample) {
lines = datas + i * wpls;
for (j = 0; j < w; j += subsample) {
pspixel = lines + j;
extractRGBValues(*pspixel, &rval, &gval, &bval);
getOctcubeIndexFromRGB(rval, gval, bval, rtab, gtab, btab, &index);
oqca[index]->n += 1.0;
oqca[index]->octindex = index;
oqca[index]->rcum += rval;
oqca[index]->gcum += gval;
oqca[index]->bcum += bval;
}
}
/* Transfer the OQCELL from the array, and order in a heap */
lh = lheapCreate(512, L_SORT_DECREASING);
for (i = 0; i < ncubes; i++)
lheapAdd(lh, oqca[i]);
LEPT_FREE(oqca); /* don't need this array */
/* Prepare a new OctcubeQuantCell array, with maxcolors cells */
oqca = (OQCELL **)LEPT_CALLOC(maxcolors, sizeof(OQCELL *));
for (i = 0; i < nbase; i++) { /* make nbase cells */
oqca[i] = (OQCELL *)LEPT_CALLOC(1, sizeof(OQCELL));
oqca[i]->n = 0.0;
}
/* Remove the nextra most populated ones, and put them in the array */
for (i = 0; i < nextra; i++) {
oqc = (OQCELL *)lheapRemove(lh);
oqc->n = 0.0; /* reinit */
oqc->rcum = 0;
oqc->gcum = 0;
oqc->bcum = 0;
oqca[nbase + i] = oqc; /* store it in the array */
}
/* Destroy the heap and its remaining contents */
lheapDestroy(&lh, TRUE);
/* Generate a lookup table from octindex at maxlevel
* to color table index */
lut1 = (l_int32 *)LEPT_CALLOC(ncubes, sizeof(l_int32));
for (i = 0; i < nextra; i++)
lut1[oqca[nbase + i]->octindex] = nbase + i;
for (index = 0; index < ncubes; index++) {
if (lut1[index] == 0) /* not one of the extras; need to assign */
lut1[index] = index >> 3; /* remove the least significant bits */
/* lept_stderr("lut1[%d] = %d\n", index, lut1[index]); */
}
/* Go through the entire image, gathering statistics and
* assigning pixels to their quantized value */
datad = pixGetData(pixd);
wpld = pixGetWpl(pixd);
for (i = 0; i < h; i++) {
lines = datas + i * wpls;
lined = datad + i * wpld;
for (j = 0; j < w; j++) {
pspixel = lines + j;
extractRGBValues(*pspixel, &rval, &gval, &bval);
getOctcubeIndexFromRGB(rval, gval, bval, rtab, gtab, btab, &index);
/* lept_stderr("rval = %d, gval = %d, bval = %d, index = %d\n",
rval, gval, bval, index); */
val = lut1[index];
switch (bpp) {
case 4:
SET_DATA_QBIT(lined, j, val);
break;
case 8:
SET_DATA_BYTE(lined, j, val);
break;
default:
LEPT_FREE(oqca);
LEPT_FREE(lut1);
return (PIX *)ERROR_PTR("bpp not 4 or 8!", procName, NULL);
break;
}
oqca[val]->n += 1.0;
oqca[val]->rcum += rval;
oqca[val]->gcum += gval;
oqca[val]->bcum += bval;
}
}
/* Compute averages, set up a colormap, and make a second
* lut that converts from the color values currently in
* the image to a minimal set */
lut2 = (l_int32 *)LEPT_CALLOC(ncubes, sizeof(l_int32));
cmap = pixcmapCreate(bpp);
pixSetColormap(pixd, cmap);
for (i = 0, index = 0; i < maxcolors; i++) {
oqc = oqca[i];
lut2[i] = index;
if (oqc->n == 0) /* no occupancy; don't bump up index */
continue;
oqc->rval = (l_int32)(oqc->rcum / oqc->n);
oqc->gval = (l_int32)(oqc->gcum / oqc->n);
oqc->bval = (l_int32)(oqc->bcum / oqc->n);
pixcmapAddColor(cmap, oqc->rval, oqc->gval, oqc->bval);
index++;
}
/* pixcmapWriteStream(stderr, cmap); */
actualcolors = pixcmapGetCount(cmap);
/* lept_stderr("Number of different colors = %d\n", actualcolors); */
/* Last time through the image; use the lookup table to
* remap the pixel value to the minimal colormap */
if (actualcolors < maxcolors) {
for (i = 0; i < h; i++) {
lined = datad + i * wpld;
for (j = 0; j < w; j++) {
switch (bpp) {
case 4:
val = GET_DATA_QBIT(lined, j);
SET_DATA_QBIT(lined, j, lut2[val]);
break;
case 8:
val = GET_DATA_BYTE(lined, j);
SET_DATA_BYTE(lined, j, lut2[val]);
break;
}
}
}
}
if (oqca) {
for (i = 0; i < maxcolors; i++)
LEPT_FREE(oqca[i]);
}
LEPT_FREE(oqca);
LEPT_FREE(lut1);
LEPT_FREE(lut2);
LEPT_FREE(rtab);
LEPT_FREE(gtab);
LEPT_FREE(btab);
return pixd;
}
/*-------------------------------------------------------------------------*
* Mixed color/gray quantization with specified number of colors *
*-------------------------------------------------------------------------*/
/*!
* \brief pixOctcubeQuantMixedWithGray()
*
* \param[in] pixs 32 bpp rgb
* \param[in] depth of output pix
* \param[in] graylevels graylevels (must be > 1)
* \param[in] delta threshold for deciding if a pix is color or gray
* \return pixd quantized to octcube and gray levels or NULL on error
*
*
* Notes:
* (1) Generates a colormapped image, where the colormap table values
* have two components: octcube values representing pixels with
* color content, and grayscale values for the rest.
* (2) The threshold (delta) is the maximum allowable difference of
* the max abs value of | r - g |, | r - b | and | g - b |.
* (3) The octcube values are the averages of all pixels that are
* found in the octcube, and that are far enough from gray to
* be considered color. This can roughly be visualized as all
* the points in the rgb color cube that are not within a "cylinder"
* of diameter approximately 'delta' along the main diagonal.
* (4) We want to guarantee full coverage of the rgb color space; thus,
* if the output depth is 4, the octlevel is 1 (2 x 2 x 2 = 8 cubes)
* and if the output depth is 8, the octlevel is 2 (4 x 4 x 4
* = 64 cubes).
* (5) Consequently, we have the following constraint on the number
* of allowed gray levels: for 4 bpp, 8; for 8 bpp, 192.
*
*/
PIX *
pixOctcubeQuantMixedWithGray(PIX *pixs,
l_int32 depth,
l_int32 graylevels,
l_int32 delta)
{
l_int32 w, h, wpls, wpld, i, j, size, octlevels;
l_int32 rval, gval, bval, del, val, midval;
l_int32 *carray, *rarray, *garray, *barray;
l_int32 *tabval;
l_uint32 octindex;
l_uint32 *rtab, *gtab, *btab;
l_uint32 *lines, *lined, *datas, *datad;
PIX *pixd;
PIXCMAP *cmap;
PROCNAME("pixOctcubeQuantMixedWithGray");
if (!pixs)
return (PIX *)ERROR_PTR("pixs not defined", procName, NULL);
if (pixGetDepth(pixs) != 32)
return (PIX *)ERROR_PTR("pixs not 32 bpp", procName, NULL);
if (graylevels < 2)
return (PIX *)ERROR_PTR("invalid graylevels", procName, NULL);
if (depth == 4) {
octlevels = 1;
size = 8; /* 2 ** 3 */
if (graylevels > 8)
return (PIX *)ERROR_PTR("max 8 gray levels", procName, NULL);
} else if (depth == 8) {
octlevels = 2;
size = 64; /* 2 ** 6 */
if (graylevels > 192)
return (PIX *)ERROR_PTR("max 192 gray levels", procName, NULL);
} else {
return (PIX *)ERROR_PTR("output depth not 4 or 8 bpp", procName, NULL);
}
pixd = NULL;
/* Make octcube index tables */
rtab = gtab = btab = NULL;
makeRGBToIndexTables(octlevels, &rtab, >ab, &btab);
/* Make octcube arrays for storing points in each cube */
carray = (l_int32 *)LEPT_CALLOC(size, sizeof(l_int32));
rarray = (l_int32 *)LEPT_CALLOC(size, sizeof(l_int32));
garray = (l_int32 *)LEPT_CALLOC(size, sizeof(l_int32));
barray = (l_int32 *)LEPT_CALLOC(size, sizeof(l_int32));
/* Make lookup table, using computed thresholds */
tabval = makeGrayQuantIndexTable(graylevels);
if (!rtab || !gtab || !btab ||
!carray || !rarray || !garray || !barray || !tabval) {
L_ERROR("calloc fail for an array\n", procName);
goto array_cleanup;
}
/* Make colormapped output pixd */
pixGetDimensions(pixs, &w, &h, NULL);
if ((pixd = pixCreate(w, h, depth)) == NULL) {
L_ERROR("pixd not made\n", procName);
goto array_cleanup;
}
pixCopyResolution(pixd, pixs);
pixCopyInputFormat(pixd, pixs);
cmap = pixcmapCreate(depth);
for (j = 0; j < size; j++) /* reserve octcube colors */
pixcmapAddColor(cmap, 1, 1, 1); /* a color that won't be used */
for (j = 0; j < graylevels; j++) { /* set grayscale colors */
val = (255 * j) / (graylevels - 1);
pixcmapAddColor(cmap, val, val, val);
}
pixSetColormap(pixd, cmap);
wpld = pixGetWpl(pixd);
datad = pixGetData(pixd);
/* Go through src image: assign dest pixels to colormap values
* and compute average colors in each occupied octcube */
datas = pixGetData(pixs);
wpls = pixGetWpl(pixs);
for (i = 0; i < h; i++) {
lines = datas + i * wpls;
lined = datad + i * wpld;
for (j = 0; j < w; j++) {
extractRGBValues(lines[j], &rval, &gval, &bval);
if (rval > gval) {
if (gval > bval) { /* r > g > b */
del = rval - bval;
midval = gval;
} else if (rval > bval) { /* r > b > g */
del = rval - gval;
midval = bval;
} else { /* b > r > g */
del = bval - gval;
midval = rval;
}
} else { /* gval >= rval */
if (rval > bval) { /* g > r > b */
del = gval - bval;
midval = rval;
} else if (gval > bval) { /* g > b > r */
del = gval - rval;
midval = bval;
} else { /* b > g > r */
del = bval - rval;
midval = gval;
}
}
if (del > delta) { /* assign to color */
octindex = rtab[rval] | gtab[gval] | btab[bval];
carray[octindex]++;
rarray[octindex] += rval;
garray[octindex] += gval;
barray[octindex] += bval;
if (depth == 4)
SET_DATA_QBIT(lined, j, octindex);
else /* depth == 8 */
SET_DATA_BYTE(lined, j, octindex);
} else { /* assign to grayscale */
val = size + tabval[midval];
if (depth == 4)
SET_DATA_QBIT(lined, j, val);
else /* depth == 8 */
SET_DATA_BYTE(lined, j, val);
}
}
}
/* Average the colors in each bin and reset the colormap */
for (i = 0; i < size; i++) {
if (carray[i] > 0) {
rarray[i] /= carray[i];
garray[i] /= carray[i];
barray[i] /= carray[i];
pixcmapResetColor(cmap, i, rarray[i], garray[i], barray[i]);
}
}
array_cleanup:
LEPT_FREE(carray);
LEPT_FREE(rarray);
LEPT_FREE(garray);
LEPT_FREE(barray);
LEPT_FREE(rtab);
LEPT_FREE(gtab);
LEPT_FREE(btab);
LEPT_FREE(tabval);
return pixd;
}
/*-------------------------------------------------------------------------*
* Fixed partition octcube quantization with 256 cells *
*-------------------------------------------------------------------------*/
/*!
* \brief pixFixedOctcubeQuant256()
*
* \param[in] pixs 32 bpp; 24-bit color
* \param[in] ditherflag 1 for dithering; 0 for no dithering
* \return pixd 8 bit with colormap, or NULL on error
*
*
* Notes:
* This simple 1-pass color quantization works by breaking the
* color space into 256 pieces, with 3 bits quantized for each of
* red and green, and 2 bits quantized for blue. We shortchange
* blue because the eye is least sensitive to blue. This
* division of the color space is into two levels of octrees,
* followed by a further division by 4 not 8, where both
* blue octrees have been combined in the third level.
*
* The color map is generated from the 256 color centers by
* taking the representative color to be the center of the
* cell volume. This gives a maximum error in the red and
* green values of 16 levels, and a maximum error in the
* blue sample of 32 levels.
*
* Each pixel in the 24-bit color image is placed in its containing
* cell, given by the relevant MSbits of the red, green and blue
* samples. An error-diffusion dithering is performed on each
* color sample to give the appearance of good average local color.
* Dithering is required; without it, the contouring and visible
* color errors are very bad.
*
* I originally implemented this algorithm in two passes,
* where the first pass was used to compute the weighted average
* of each sample in each pre-allocated region of color space.
* The idea was to use these centroids in the dithering algorithm
* of the second pass, to reduce the average error that was
* being dithered. However, with dithering, there is
* virtually no difference, so there is no reason to make the
* first pass. Consequently, this 1-pass version just assigns
* the pixels to the centers of the pre-allocated cells.
* We use dithering to spread the difference between the sample
* value and the location of the center of the cell. For speed
* and simplicity, we use integer dithering and propagate only
* to the right, down, and diagonally down-right, with ratios
* 3/8, 3/8 and 1/4, respectively. The results should be nearly
* as good, and a bit faster, with propagation only to the right
* and down.
*
* The algorithm is very fast, because there is no search,
* only fast generation of the cell index for each pixel.
* We use a simple mapping from the three 8 bit rgb samples
* to the 8 bit cell index; namely, r7 r6 r5 g7 g6 g5 b7 b6.
* This is not in an octcube format, but it doesn't matter.
* There are no storage requirements. We could keep a
* running average of the center of each sample in each
* cluster, rather than using the center of the cell, but
* this is just extra work, esp. with dithering.
*
* This method gives surprisingly good results with dithering.
* However, without dithering, the loss of color accuracy is
* evident in regions that are very light or that have subtle
* blending of colors.
*
*/
PIX *
pixFixedOctcubeQuant256(PIX *pixs,
l_int32 ditherflag)
{
l_uint8 index;
l_int32 rval, gval, bval;
l_int32 w, h, wpls, wpld, i, j, cindex;
l_uint32 *rtab, *gtab, *btab;
l_int32 *itab;
l_uint32 *datas, *datad, *lines, *lined;
PIX *pixd;
PIXCMAP *cmap;
PROCNAME("pixFixedOctcubeQuant256");
if (!pixs)
return (PIX *)ERROR_PTR("pixs not defined", procName, NULL);
if (pixGetDepth(pixs) != 32)
return (PIX *)ERROR_PTR("pixs not 32 bpp", procName, NULL);
/* Do not dither if image is very small */
pixGetDimensions(pixs, &w, &h, NULL);
if (w < MinDitherSize && h < MinDitherSize && ditherflag == 1) {
L_INFO("Small image: dithering turned off\n", procName);
ditherflag = 0;
}
/* Find the centers of the 256 cells, each of which represents
* the 3 MSBits of the red and green components, and the
* 2 MSBits of the blue component. This gives a mapping
* from a "cube index" to the rgb values. Save all 256
* rgb values of these centers in a colormap.
* For example, to get the red color of the cell center,
* you take the 3 MSBits of to the index and add the
* offset to the center of the cell, which is 0x10. */
cmap = pixcmapCreate(8);
for (cindex = 0; cindex < 256; cindex++) {
rval = (cindex & 0xe0) | 0x10;
gval = ((cindex << 3) & 0xe0) | 0x10;
bval = ((cindex << 6) & 0xc0) | 0x20;
pixcmapAddColor(cmap, rval, gval, bval);
}
/* Make output 8 bpp palette image */
datas = pixGetData(pixs);
wpls = pixGetWpl(pixs);
if ((pixd = pixCreate(w, h, 8)) == NULL) {
pixcmapDestroy(&cmap);
return (PIX *)ERROR_PTR("pixd not made", procName, NULL);
}
pixSetColormap(pixd, cmap);
pixCopyResolution(pixd, pixs);
pixCopyInputFormat(pixd, pixs);
datad = pixGetData(pixd);
wpld = pixGetWpl(pixd);
/* Set dest pix values to colortable indices */
if (ditherflag == 0) { /* no dithering */
for (i = 0; i < h; i++) {
lines = datas + i * wpls;
lined = datad + i * wpld;
for (j = 0; j < w; j++) {
extractRGBValues(lines[j], &rval, &gval, &bval);
index = (rval & 0xe0) | ((gval >> 3) & 0x1c) | (bval >> 6);
SET_DATA_BYTE(lined, j, index);
}
}
} else { /* ditherflag == 1 */
/* Set up conversion tables from rgb directly to the colormap
* index. However, the dithering function expects these tables
* to generate an octcube index (+1), and the table itab[] to
* convert to the colormap index. So we make a trivial
* itab[], that simply compensates for the -1 in
* pixDitherOctindexWithCmap(). No cap is required on
* the propagated difference. */
rtab = (l_uint32 *)LEPT_CALLOC(256, sizeof(l_uint32));
gtab = (l_uint32 *)LEPT_CALLOC(256, sizeof(l_uint32));
btab = (l_uint32 *)LEPT_CALLOC(256, sizeof(l_uint32));
itab = (l_int32 *)LEPT_CALLOC(256, sizeof(l_int32));
if (!rtab || !gtab || !btab || !itab) {
pixDestroy(&pixd);
return (PIX *)ERROR_PTR("calloc fail for table", procName, NULL);
}
for (i = 0; i < 256; i++) {
rtab[i] = i & 0xe0;
gtab[i] = (i >> 3) & 0x1c;
btab[i] = i >> 6;
itab[i] = i + 1;
}
pixDitherOctindexWithCmap(pixs, pixd, rtab, gtab, btab, itab,
FIXED_DIF_CAP);
LEPT_FREE(rtab);
LEPT_FREE(gtab);
LEPT_FREE(btab);
LEPT_FREE(itab);
}
return pixd;
}
/*---------------------------------------------------------------------------*
* Nearly exact quantization for images with few colors *
*---------------------------------------------------------------------------*/
/*!
* \brief pixFewColorsOctcubeQuant1()
*
* \param[in] pixs 32 bpp rgb
* \param[in] level significant bits for each of RGB; valid in [1...6]
* \return pixd quantized to octcube or NULL on error
*
*
* Notes:
* (1) Generates a colormapped image, where the colormap table values
* are the averages of all pixels that are found in the octcube.
* (2) This fails if there are more than 256 colors (i.e., more
* than 256 occupied octcubes).
* (3) Often level 3 (512 octcubes) will succeed because not more
* than half of them are occupied with 1 or more pixels.
* (4) The depth of the result, which is either 2, 4 or 8 bpp,
* is the minimum required to hold the number of colors that
* are found.
* (5) This can be useful for quantizing orthographically generated
* images such as color maps, where there may be more than 256 colors
* because of aliasing or jpeg artifacts on text or lines, but
* there are a relatively small number of solid colors. Then,
* use with level = 3 can often generate a compact and accurate
* representation of the original RGB image. For this purpose,
* it is better than pixFewColorsOctcubeQuant2(), because it
* uses the average value of pixels in the octcube rather
* than the first found pixel. It is also simpler to use,
* because it generates the histogram internally.
*
*/
PIX *
pixFewColorsOctcubeQuant1(PIX *pixs,
l_int32 level)
{
l_int32 w, h, wpls, wpld, i, j, depth, size, ncolors, index;
l_int32 rval, gval, bval;
l_int32 *carray, *rarray, *garray, *barray;
l_uint32 octindex;
l_uint32 *rtab, *gtab, *btab;
l_uint32 *lines, *lined, *datas, *datad, *pspixel;
PIX *pixd;
PIXCMAP *cmap;
PROCNAME("pixFewColorsOctcubeQuant1");
if (!pixs)
return (PIX *)ERROR_PTR("pixs not defined", procName, NULL);
if (pixGetDepth(pixs) != 32)
return (PIX *)ERROR_PTR("pixs not 32 bpp", procName, NULL);
if (level < 1 || level > 6)
return (PIX *)ERROR_PTR("invalid level", procName, NULL);
pixd = NULL;
if (octcubeGetCount(level, &size)) /* array size = 2 ** (3 * level) */
return (PIX *)ERROR_PTR("size not returned", procName, NULL);
rtab = gtab = btab = NULL;
makeRGBToIndexTables(level, &rtab, >ab, &btab);
carray = (l_int32 *)LEPT_CALLOC(size, sizeof(l_int32));
rarray = (l_int32 *)LEPT_CALLOC(size, sizeof(l_int32));
garray = (l_int32 *)LEPT_CALLOC(size, sizeof(l_int32));
barray = (l_int32 *)LEPT_CALLOC(size, sizeof(l_int32));
if (!carray || !rarray || !garray || !barray) {
L_ERROR("calloc fail for an array\n", procName);
goto array_cleanup;
}
/* Place the pixels in octcube leaves. */
pixGetDimensions(pixs, &w, &h, NULL);
datas = pixGetData(pixs);
wpls = pixGetWpl(pixs);
for (i = 0; i < h; i++) {
lines = datas + i * wpls;
for (j = 0; j < w; j++) {
pspixel = lines + j;
extractRGBValues(*pspixel, &rval, &gval, &bval);
octindex = rtab[rval] | gtab[gval] | btab[bval];
carray[octindex]++;
rarray[octindex] += rval;
garray[octindex] += gval;
barray[octindex] += bval;
}
}
/* Find the number of different colors */
for (i = 0, ncolors = 0; i < size; i++) {
if (carray[i] > 0)
ncolors++;
}
if (ncolors > 256) {
L_WARNING("%d colors found; more than 256\n", procName, ncolors);
goto array_cleanup;
}
if (ncolors <= 4)
depth = 2;
else if (ncolors <= 16)
depth = 4;
else
depth = 8;
/* Average the colors in each octcube leaf and add to colormap table;
* then use carray to hold the colormap index + 1 */
cmap = pixcmapCreate(depth);
for (i = 0, index = 0; i < size; i++) {
if (carray[i] > 0) {
rarray[i] /= carray[i];
garray[i] /= carray[i];
barray[i] /= carray[i];
pixcmapAddColor(cmap, rarray[i], garray[i], barray[i]);
carray[i] = index + 1; /* to avoid storing 0 */
index++;
}
}
pixd = pixCreate(w, h, depth);
pixSetColormap(pixd, cmap);
pixCopyResolution(pixd, pixs);
pixCopyInputFormat(pixd, pixs);
datad = pixGetData(pixd);
wpld = pixGetWpl(pixd);
for (i = 0; i < h; i++) {
lines = datas + i * wpls;
lined = datad + i * wpld;
for (j = 0; j < w; j++) {
pspixel = lines + j;
extractRGBValues(*pspixel, &rval, &gval, &bval);
octindex = rtab[rval] | gtab[gval] | btab[bval];
switch (depth)
{
case 2:
SET_DATA_DIBIT(lined, j, carray[octindex] - 1);
break;
case 4:
SET_DATA_QBIT(lined, j, carray[octindex] - 1);
break;
case 8:
SET_DATA_BYTE(lined, j, carray[octindex] - 1);
break;
default:
L_WARNING("shouldn't get here\n", procName);
}
}
}
array_cleanup:
LEPT_FREE(carray);
LEPT_FREE(rarray);
LEPT_FREE(garray);
LEPT_FREE(barray);
LEPT_FREE(rtab);
LEPT_FREE(gtab);
LEPT_FREE(btab);
return pixd;
}
/*!
* \brief pixFewColorsOctcubeQuant2()
*
* \param[in] pixs 32 bpp rgb
* \param[in] level of octcube indexing, for histogram: 3, 4, 5, 6
* \param[in] na histogram of pixel occupation in octree leaves
* at given level
* \param[in] ncolors number of occupied octree leaves at given level
* \param[out] pnerrors [optional] num of pixels not exactly
* represented in the colormap
* \return pixd 2, 4 or 8 bpp with colormap, or NULL on error
*
*
* Notes:
* (1) Generates a colormapped image, where the colormap table values
* are the averages of all pixels that are found in the octcube.
* (2) This fails if there are more than 256 colors (i.e., more
* than 256 occupied octcubes).
* (3) Often level 3 (512 octcubes) will succeed because not more
* than half of them are occupied with 1 or more pixels.
* (4) For an image with not more than 256 colors, it is unlikely
* that two pixels of different color will fall in the same
* octcube at level = 4. However it is possible, and this
* function optionally returns %nerrors, the number of pixels
* where, because more than one color is in the same octcube,
* the pixel color is not exactly reproduced in the colormap.
* The colormap for an occupied leaf of the octree contains
* the color of the first pixel encountered in that octcube.
* (5) This differs from pixFewColorsOctcubeQuant1(), which also
* requires not more than 256 occupied leaves, but represents
* the color of each leaf by an average over the pixels in
* that leaf. This also requires precomputing the histogram
* of occupied octree leaves, which is generated using
* pixOctcubeHistogram().
* (6) This is used in pixConvertRGBToColormap() for images that
* are determined, by their histogram, to have relatively few
* colors. This typically happens with orthographically
* produced images (as oppopsed to natural images), where
* it is expected that most of the pixels within a leaf
* octcube have exactly the same color, and quantization to
* that color is lossless.
*
*/
PIX *
pixFewColorsOctcubeQuant2(PIX *pixs,
l_int32 level,
NUMA *na,
l_int32 ncolors,
l_int32 *pnerrors)
{
l_int32 w, h, wpls, wpld, i, j, nerrors;
l_int32 ncubes, depth, cindex, oval;
l_int32 rval, gval, bval;
l_int32 *octarray;
l_uint32 octindex;
l_uint32 *rtab, *gtab, *btab;
l_uint32 *lines, *lined, *datas, *datad, *ppixel;
l_uint32 *colorarray;
PIX *pixd;
PIXCMAP *cmap;
PROCNAME("pixFewColorsOctcubeQuant2");
if (!pixs)
return (PIX *)ERROR_PTR("pixs not defined", procName, NULL);
if (pixGetDepth(pixs) != 32)
return (PIX *)ERROR_PTR("pixs not 32 bpp", procName, NULL);
if (level < 3 || level > 6)
return (PIX *)ERROR_PTR("level not in {4, 5, 6}", procName, NULL);
if (ncolors > 256)
return (PIX *)ERROR_PTR("ncolors > 256", procName, NULL);
if (pnerrors)
*pnerrors = UNDEF;
pixd = NULL;
/* Represent the image with a set of leaf octcubes
* at 'level', one for each color. */
rtab = gtab = btab = NULL;
makeRGBToIndexTables(level, &rtab, >ab, &btab);
/* The octarray will give a ptr from the octcube to the colorarray */
ncubes = numaGetCount(na);
octarray = (l_int32 *)LEPT_CALLOC(ncubes, sizeof(l_int32));
/* The colorarray will hold the colors of the first pixel
* that lands in the leaf octcube. After filling, it is
* used to generate the colormap. */
colorarray = (l_uint32 *)LEPT_CALLOC(ncolors + 1, sizeof(l_uint32));
if (!octarray || !colorarray) {
L_ERROR("octarray or colorarray not made\n", procName);
goto cleanup_arrays;
}
/* Determine the output depth from the number of colors */
pixGetDimensions(pixs, &w, &h, NULL);
datas = pixGetData(pixs);
wpls = pixGetWpl(pixs);
if (ncolors <= 4)
depth = 2;
else if (ncolors <= 16)
depth = 4;
else /* ncolors <= 256 */
depth = 8;
if ((pixd = pixCreate(w, h, depth)) == NULL) {
L_ERROR("pixd not made\n", procName);
goto cleanup_arrays;
}
pixCopyResolution(pixd, pixs);
pixCopyInputFormat(pixd, pixs);
datad = pixGetData(pixd);
wpld = pixGetWpl(pixd);
/* For each pixel, get the octree index for its leaf octcube.
* Check if a pixel has already been found in this octcube.
* ~ If not yet found, save that color in the colorarray
* and save the cindex in the octarray.
* ~ If already found, compare the pixel color with the
* color in the colorarray, and note if it differs.
* Then set the dest pixel value to the cindex - 1, which
* will be the cmap index for this color. */
cindex = 1; /* start with 1 */
nerrors = 0;
for (i = 0; i < h; i++) {
lines = datas + i * wpls;
lined = datad + i * wpld;
for (j = 0; j < w; j++) {
ppixel = lines + j;
extractRGBValues(*ppixel, &rval, &gval, &bval);
octindex = rtab[rval] | gtab[gval] | btab[bval];
oval = octarray[octindex];
if (oval == 0) {
octarray[octindex] = cindex;
colorarray[cindex] = *ppixel;
setPixelLow(lined, j, depth, cindex - 1);
cindex++;
} else { /* already have seen this color; is it unique? */
setPixelLow(lined, j, depth, oval - 1);
if (colorarray[oval] != *ppixel)
nerrors++;
}
}
}
if (pnerrors)
*pnerrors = nerrors;
#if DEBUG_FEW_COLORS
lept_stderr("ncubes = %d, ncolors = %d\n", ncubes, ncolors);
for (i = 0; i < ncolors; i++)
lept_stderr("color[%d] = %x\n", i, colorarray[i + 1]);
#endif /* DEBUG_FEW_COLORS */
/* Make the colormap. */
cmap = pixcmapCreate(depth);
for (i = 0; i < ncolors; i++) {
ppixel = colorarray + i + 1;
extractRGBValues(*ppixel, &rval, &gval, &bval);
pixcmapAddColor(cmap, rval, gval, bval);
}
pixSetColormap(pixd, cmap);
cleanup_arrays:
LEPT_FREE(octarray);
LEPT_FREE(colorarray);
LEPT_FREE(rtab);
LEPT_FREE(gtab);
LEPT_FREE(btab);
return pixd;
}
/*!
* \brief pixFewColorsOctcubeQuantMixed()
*
* \param[in] pixs 32 bpp rgb
* \param[in] level significant octcube bits for each of RGB;
* valid in [1...6]; use 0 for default
* \param[in] darkthresh threshold near black; if the lightest component
* is below this, the pixel is not considered to
* be gray or color; uses 0 for default
* \param[in] lightthresh threshold near white; if the darkest component
* is above this, the pixel is not considered to
* be gray or color; use 0 for default
* \param[in] diffthresh thresh for the max difference between component
* values; for differences below this, the pixel
* is considered to be gray; use 0 for default
* \param[in] minfract min fraction of pixels for gray histo bin;
* use 0.0 for default
* \param[in] maxspan max size of gray histo bin; use 0 for default
* \return pixd 8 bpp, quantized to octcube for pixels that are
* not gray; gray pixels are quantized separately
* over the full gray range, or NULL on error
*
*
* Notes:
* (1) First runs pixFewColorsOctcubeQuant1(). If this succeeds,
* it separates the color from gray(ish) entries in the cmap,
* and re-quantizes the gray pixels. The result has some pixels
* in color and others in gray.
* (2) This fails if there are more than 256 colors (i.e., more
* than 256 occupied octcubes in the color quantization).
* (3) Level 3 (512 octcubes) will usually succeed because not more
* than half of them are occupied with 1 or more pixels.
* (4) This uses the criterion from pixColorFraction() for deciding
* if a colormap entry is color; namely, if the color components
* are not too close to either black or white, and the maximum
* difference between component values equals or exceeds a threshold.
* (5) For quantizing the gray pixels, it uses a histogram-based
* method where input parameters determining the buckets are
* the minimum population fraction and the maximum allowed size.
* (6) Recommended input parameters are:
* %level: 3 or 4 (3 is default)
* %darkthresh: 20
* %lightthresh: 244
* %diffthresh: 20
* %minfract: 0.05
* %maxspan: 15
* These numbers are intended to be conservative (somewhat over-
* sensitive) in color detection, It's usually better to pay
* extra with octcube quantization of a grayscale image than
* to use grayscale quantization on an image that has some
* actual color. Input 0 on any of these to get the default.
* (7) This can be useful for quantizing orthographically generated
* images such as color maps, where there may be more than 256 colors
* because of aliasing or jpeg artifacts on text or lines, but
* there are a relatively small number of solid colors. It usually
* gives results that are better than pixOctcubeQuantMixedWithGray(),
* both in size and appearance. But it is a bit slower.
*
*/
PIX *
pixFewColorsOctcubeQuantMixed(PIX *pixs,
l_int32 level,
l_int32 darkthresh,
l_int32 lightthresh,
l_int32 diffthresh,
l_float32 minfract,
l_int32 maxspan)
{
l_int32 i, j, w, h, wplc, wplm, wpld, ncolors, index;
l_int32 rval, gval, bval, val, minval, maxval;
l_int32 *lut;
l_uint32 *datac, *datam, *datad, *linec, *linem, *lined;
PIX *pix1, *pixc, *pixm, *pixg, *pixd;
PIXCMAP *cmap, *cmapd;
PROCNAME("pixFewColorsOctcubeQuantMixed");
if (!pixs || pixGetDepth(pixs) != 32)
return (PIX *)ERROR_PTR("pixs undefined or not 32 bpp", procName, NULL);
if (level <= 0) level = 3;
if (level > 6)
return (PIX *)ERROR_PTR("invalid level", procName, NULL);
if (darkthresh <= 0) darkthresh = 20;
if (lightthresh <= 0) lightthresh = 244;
if (diffthresh <= 0) diffthresh = 20;
if (minfract <= 0.0) minfract = 0.05f;
if (maxspan <= 2) maxspan = 15;
/* Start with a simple fixed octcube quantizer. */
if ((pix1 = pixFewColorsOctcubeQuant1(pixs, level)) == NULL)
return (PIX *)ERROR_PTR("too many colors", procName, NULL);
pixc = pixConvertTo8(pix1, 1); /* must be 8 bpp */
pixDestroy(&pix1);
/* Identify and save color entries in the colormap. Set up a LUT
* that returns -1 for any gray pixel. */
cmap = pixGetColormap(pixc);
ncolors = pixcmapGetCount(cmap);
cmapd = pixcmapCreate(8);
lut = (l_int32 *)LEPT_CALLOC(256, sizeof(l_int32));
for (i = 0; i < 256; i++)
lut[i] = -1;
for (i = 0, index = 0; i < ncolors; i++) {
pixcmapGetColor(cmap, i, &rval, &gval, &bval);
minval = L_MIN(rval, gval);
minval = L_MIN(minval, bval);
if (minval > lightthresh) /* near white */
continue;
maxval = L_MAX(rval, gval);
maxval = L_MAX(maxval, bval);
if (maxval < darkthresh) /* near black */
continue;
/* Use the max diff between components to test for color */
if (maxval - minval >= diffthresh) {
pixcmapAddColor(cmapd, rval, gval, bval);
lut[i] = index;
index++;
}
}
/* Generate dest pix with just the color pixels set to their
* colormap indices. At the same time, make a 1 bpp mask
* of the non-color pixels */
pixGetDimensions(pixs, &w, &h, NULL);
pixd = pixCreate(w, h, 8);
pixSetColormap(pixd, cmapd);
pixm = pixCreate(w, h, 1);
datac = pixGetData(pixc);
datam = pixGetData(pixm);
datad = pixGetData(pixd);
wplc = pixGetWpl(pixc);
wplm = pixGetWpl(pixm);
wpld = pixGetWpl(pixd);
for (i = 0; i < h; i++) {
linec = datac + i * wplc;
linem = datam + i * wplm;
lined = datad + i * wpld;
for (j = 0; j < w; j++) {
val = GET_DATA_BYTE(linec, j);
if (lut[val] == -1)
SET_DATA_BIT(linem, j);
else
SET_DATA_BYTE(lined, j, lut[val]);
}
}
/* Fill in the gray values. Use a grayscale version of pixs
* as input, along with the mask over the actual gray pixels. */
pixg = pixConvertTo8(pixs, 0);
pixGrayQuantFromHisto(pixd, pixg, pixm, minfract, maxspan);
LEPT_FREE(lut);
pixDestroy(&pixc);
pixDestroy(&pixm);
pixDestroy(&pixg);
return pixd;
}
/*---------------------------------------------------------------------------*
* Fixed partition octcube quantization with RGB output *
*---------------------------------------------------------------------------*/
/*!
* \brief pixFixedOctcubeQuantGenRGB()
*
* \param[in] pixs 32 bpp rgb
* \param[in] level significant bits for each of r,g,b
* \return pixd rgb; quantized to octcube centers, or NULL on error
*
*
* Notes:
* (1) Unlike the other color quantization functions, this one
* generates an rgb image.
* (2) The pixel values are quantized to the center of each octcube
* (at the specified level) containing the pixel. They are
* not quantized to the average of the pixels in that octcube.
*
*/
PIX *
pixFixedOctcubeQuantGenRGB(PIX *pixs,
l_int32 level)
{
l_int32 w, h, wpls, wpld, i, j;
l_int32 rval, gval, bval;
l_uint32 octindex;
l_uint32 *rtab, *gtab, *btab;
l_uint32 *lines, *lined, *datas, *datad;
PIX *pixd;
PROCNAME("pixFixedOctcubeQuantGenRGB");
if (!pixs)
return (PIX *)ERROR_PTR("pixs not defined", procName, NULL);
if (pixGetDepth(pixs) != 32)
return (PIX *)ERROR_PTR("pixs not 32 bpp", procName, NULL);
if (level < 1 || level > 6)
return (PIX *)ERROR_PTR("level not in {1,...6}", procName, NULL);
if (makeRGBToIndexTables(level, &rtab, >ab, &btab))
return (PIX *)ERROR_PTR("tables not made", procName, NULL);
pixGetDimensions(pixs, &w, &h, NULL);
pixd = pixCreate(w, h, 32);
pixCopyResolution(pixd, pixs);
pixCopyInputFormat(pixd, pixs);
datad = pixGetData(pixd);
wpld = pixGetWpl(pixd);
datas = pixGetData(pixs);
wpls = pixGetWpl(pixs);
for (i = 0; i < h; i++) {
lines = datas + i * wpls;
lined = datad + i * wpld;
for (j = 0; j < w; j++) {
extractRGBValues(lines[j], &rval, &gval, &bval);
octindex = rtab[rval] | gtab[gval] | btab[bval];
getRGBFromOctcube(octindex, level, &rval, &gval, &bval);
composeRGBPixel(rval, gval, bval, lined + j);
}
}
LEPT_FREE(rtab);
LEPT_FREE(gtab);
LEPT_FREE(btab);
return pixd;
}
/*------------------------------------------------------------------*
* Color quantize RGB image using existing colormap *
*------------------------------------------------------------------*/
/*!
* \brief pixQuantFromCmap()
*
* \param[in] pixs 8 bpp grayscale without cmap, or 32 bpp rgb
* \param[in] cmap to quantize to; insert copy into dest pix
* \param[in] mindepth minimum depth of pixd: can be 2, 4 or 8 bpp
* \param[in] level of octcube used for finding nearest color in cmap
* \param[in] metric L_MANHATTAN_DISTANCE, L_EUCLIDEAN_DISTANCE
* \return pixd 2, 4 or 8 bpp, colormapped, or NULL on error
*
*
* Notes:
* (1) This is a top-level wrapper for quantizing either grayscale
* or rgb images to a specified colormap.
* (2) The actual output depth is constrained by %mindepth and
* by the number of colors in %cmap.
* (3) For grayscale, %level and %metric are ignored.
* (4) If the cmap has color and pixs is grayscale, the color is
* removed from the cmap before quantizing pixs.
*
*/
PIX *
pixQuantFromCmap(PIX *pixs,
PIXCMAP *cmap,
l_int32 mindepth,
l_int32 level,
l_int32 metric)
{
l_int32 d;
PROCNAME("pixQuantFromCmap");
if (!pixs)
return (PIX *)ERROR_PTR("pixs not defined", procName, NULL);
if (mindepth != 2 && mindepth != 4 && mindepth != 8)
return (PIX *)ERROR_PTR("invalid mindepth", procName, NULL);
d = pixGetDepth(pixs);
if (d == 8)
return pixGrayQuantFromCmap(pixs, cmap, mindepth);
else if (d == 32)
return pixOctcubeQuantFromCmap(pixs, cmap, mindepth,
level, metric);
else
return (PIX *)ERROR_PTR("d not 8 or 32 bpp", procName, NULL);
}
/*!
* \brief pixOctcubeQuantFromCmap()
*
* \param[in] pixs 32 bpp rgb
* \param[in] cmap to quantize to; insert copy into dest pix
* \param[in] mindepth minimum depth of pixd: can be 2, 4 or 8 bpp
* \param[in] level of octcube used for finding nearest color in cmap
* \param[in] metric L_MANHATTAN_DISTANCE, L_EUCLIDEAN_DISTANCE
* \return pixd 2, 4 or 8 bpp, colormapped, or NULL on error
*
*
* Notes:
* (1) In typical use, we are doing an operation, such as
* interpolative scaling, on a colormapped pix, where it is
* necessary to remove the colormap before the operation.
* We then want to re-quantize the RGB result using the same
* colormap.
* (2) The level is used to divide the color space into octcubes.
* Each input pixel is, in effect, placed at the center of an
* octcube at the given level, and it is mapped into the
* exact color (given in the colormap) that is the closest
* to that location. We need to know that distance, for each color
* in the colormap. The higher the level of the octtree, the smaller
* the octcubes in the color space, and hence the more accurately
* we can determine the closest color in the colormap; however,
* the size of the LUT, which is the total number of octcubes,
* increases by a factor of 8 for each increase of 1 level.
* The time required to acquire a level 4 mapping table, which has
* about 4K entries, is less than 1 msec, so that is the
* recommended minimum size to be used. At that size, the
* octcubes have their centers 16 units apart in each (r,g,b)
* direction. If two colors are in the same octcube, the one
* closest to the center will always be chosen. The maximum
* error for any component occurs when the correct color is
* at a cube corner and there is an incorrect color just inside
* the cube next to the opposite corner, giving an error of
* 14 units (out of 256) for each component. Using a level 5
* mapping table reduces the maximum error to 6 units.
* (3) Typically you should use the Euclidean metric, because the
* resulting voronoi cells (which are generated using the actual
* colormap values as seeds) are convex for Euclidean distance
* but not for Manhattan distance. In terms of the octcubes,
* convexity of the voronoi cells means that if the 8 corners
* of any cube (of which the octcubes are special cases)
* are all within a cell, then every point in the cube will
* lie within the cell.
* (4) The depth of the output pixd is equal to the maximum of
* (a) %mindepth and (b) the minimum (2, 4 or 8 bpp) necessary
* to hold the indices in the colormap.
* (5) We build a mapping table from octcube to colormap index so
* that this function can run in a time (otherwise) independent
* of the number of colors in the colormap. This avoids a
* brute-force search for the closest colormap color to each
* pixel in the image.
* (6) This is similar to the function pixAssignToNearestColor()
* used for color segmentation.
* (7) Except for very small images or when using level > 4,
* it takes very little time to generate the tables,
* compared to the generation of the colormapped dest pix,
* so one would not typically use the low-level version.
*
*/
PIX *
pixOctcubeQuantFromCmap(PIX *pixs,
PIXCMAP *cmap,
l_int32 mindepth,
l_int32 level,
l_int32 metric)
{
l_int32 *cmaptab;
l_uint32 *rtab, *gtab, *btab;
PIX *pixd;
PROCNAME("pixOctcubeQuantFromCmap");
if (!pixs)
return (PIX *)ERROR_PTR("pixs not defined", procName, NULL);
if (pixGetDepth(pixs) != 32)
return (PIX *)ERROR_PTR("pixs not 32 bpp", procName, NULL);
if (!cmap)
return (PIX *)ERROR_PTR("cmap not defined", procName, NULL);
if (mindepth != 2 && mindepth != 4 && mindepth != 8)
return (PIX *)ERROR_PTR("invalid mindepth", procName, NULL);
if (level < 1 || level > 6)
return (PIX *)ERROR_PTR("level not in {1...6}", procName, NULL);
if (metric != L_MANHATTAN_DISTANCE && metric != L_EUCLIDEAN_DISTANCE)
return (PIX *)ERROR_PTR("invalid metric", procName, NULL);
/* Set up the tables to map rgb to the nearest colormap index */
rtab = gtab = btab = NULL;
makeRGBToIndexTables(level, &rtab, >ab, &btab);
cmaptab = pixcmapToOctcubeLUT(cmap, level, metric);
pixd = pixOctcubeQuantFromCmapLUT(pixs, cmap, mindepth,
cmaptab, rtab, gtab, btab);
LEPT_FREE(cmaptab);
LEPT_FREE(rtab);
LEPT_FREE(gtab);
LEPT_FREE(btab);
return pixd;
}
/*!
* \brief pixOctcubeQuantFromCmapLUT()
*
* \param[in] pixs 32 bpp rgb
* \param[in] cmap to quantize to; insert copy into dest pix
* \param[in] mindepth minimum depth of pixd: can be 2, 4 or 8 bpp
* \param[in] cmaptab table mapping from octindex to colormap index
* \param[in] rtab, gtab, btab tables mapping from RGB to octindex
* \return pixd 2, 4 or 8 bpp, colormapped, or NULL on error
*
*
* Notes:
* (1) See the notes in the higher-level function
* pixOctcubeQuantFromCmap(). The octcube level for
* the generated octree is specified there, along with
* the distance metric for determining the closest
* color in the colormap to each octcube.
* (2) If the colormap, level and metric information have already
* been used to construct the set of mapping tables,
* this low-level function can be used directly (i.e.,
* independently of pixOctcubeQuantFromCmap()) to build
* a colormapped pix that uses the specified colormap.
*
*/
static PIX *
pixOctcubeQuantFromCmapLUT(PIX *pixs,
PIXCMAP *cmap,
l_int32 mindepth,
l_int32 *cmaptab,
l_uint32 *rtab,
l_uint32 *gtab,
l_uint32 *btab)
{
l_int32 i, j, w, h, depth, wpls, wpld;
l_int32 rval, gval, bval, index;
l_uint32 octindex;
l_uint32 *lines, *lined, *datas, *datad;
PIX *pixd;
PIXCMAP *cmapc;
PROCNAME("pixOctcubeQuantFromCmapLUT");
if (!pixs)
return (PIX *)ERROR_PTR("pixs not defined", procName, NULL);
if (pixGetDepth(pixs) != 32)
return (PIX *)ERROR_PTR("pixs not 32 bpp", procName, NULL);
if (!cmap)
return (PIX *)ERROR_PTR("cmap not defined", procName, NULL);
if (mindepth != 2 && mindepth != 4 && mindepth != 8)
return (PIX *)ERROR_PTR("invalid mindepth", procName, NULL);
if (!rtab || !gtab || !btab || !cmaptab)
return (PIX *)ERROR_PTR("tables not all defined", procName, NULL);
/* Init dest pix (with minimum bpp depending on cmap) */
pixcmapGetMinDepth(cmap, &depth);
depth = L_MAX(depth, mindepth);
pixGetDimensions(pixs, &w, &h, NULL);
if ((pixd = pixCreate(w, h, depth)) == NULL)
return (PIX *)ERROR_PTR("pixd not made", procName, NULL);
cmapc = pixcmapCopy(cmap);
pixSetColormap(pixd, cmapc);
pixCopyResolution(pixd, pixs);
pixCopyInputFormat(pixd, pixs);
/* Insert the colormap index of the color nearest to the input pixel */
datas = pixGetData(pixs);
datad = pixGetData(pixd);
wpls = pixGetWpl(pixs);
wpld = pixGetWpl(pixd);
for (i = 0; i < h; i++) {
lines = datas + i * wpls;
lined = datad + i * wpld;
for (j = 0; j < w; j++) {
extractRGBValues(lines[j], &rval, &gval, &bval);
/* Map from rgb to octcube index */
getOctcubeIndexFromRGB(rval, gval, bval, rtab, gtab, btab,
&octindex);
/* Map from octcube index to nearest colormap index */
index = cmaptab[octindex];
if (depth == 2)
SET_DATA_DIBIT(lined, j, index);
else if (depth == 4)
SET_DATA_QBIT(lined, j, index);
else /* depth == 8 */
SET_DATA_BYTE(lined, j, index);
}
}
return pixd;
}
/*---------------------------------------------------------------------------*
* Generation of octcube histogram *
*---------------------------------------------------------------------------*/
/*!
* \brief pixOctcubeHistogram()
*
* \param[in] pixs 32 bpp rgb
* \param[in] level significant bits for each of RGB; valid in [1...6]
* \param[out] pncolors [optional] number of occupied cubes
* \return numa histogram of color pixels, or NULL on error
*
*
* Notes:
* (1) Input NULL for &ncolors to prevent computation and return value.
*
*/
NUMA *
pixOctcubeHistogram(PIX *pixs,
l_int32 level,
l_int32 *pncolors)
{
l_int32 size, i, j, w, h, wpl, ncolors, val;
l_int32 rval, gval, bval;
l_uint32 octindex;
l_uint32 *rtab, *gtab, *btab;
l_uint32 *data, *line;
l_float32 *array;
NUMA *na;
PROCNAME("pixOctcubeHistogram");
if (pncolors) *pncolors = 0;
if (!pixs)
return (NUMA *)ERROR_PTR("pixs not defined", procName, NULL);
if (pixGetDepth(pixs) != 32)
return (NUMA *)ERROR_PTR("pixs not 32 bpp", procName, NULL);
pixGetDimensions(pixs, &w, &h, NULL);
wpl = pixGetWpl(pixs);
data = pixGetData(pixs);
if (octcubeGetCount(level, &size)) /* array size = 2 ** (3 * level) */
return (NUMA *)ERROR_PTR("size not returned", procName, NULL);
rtab = gtab = btab = NULL;
makeRGBToIndexTables(level, &rtab, >ab, &btab);
if ((na = numaCreate(size)) == NULL) {
L_ERROR("na not made\n", procName);
goto cleanup_arrays;
}
numaSetCount(na, size);
array = numaGetFArray(na, L_NOCOPY);
for (i = 0; i < h; i++) {
line = data + i * wpl;
for (j = 0; j < w; j++) {
extractRGBValues(line[j], &rval, &gval, &bval);
octindex = rtab[rval] | gtab[gval] | btab[bval];
#if DEBUG_OCTINDEX
if ((level == 1 && octindex > 7) ||
(level == 2 && octindex > 63) ||
(level == 3 && octindex > 511) ||
(level == 4 && octindex > 4097) ||
(level == 5 && octindex > 32783) ||
(level == 6 && octindex > 262271)) {
lept_stderr("level = %d, octindex = %d, index error!\n",
level, octindex);
continue;
}
#endif /* DEBUG_OCTINDEX */
array[octindex] += 1.0;
}
}
if (pncolors) {
for (i = 0, ncolors = 0; i < size; i++) {
numaGetIValue(na, i, &val);
if (val > 0)
ncolors++;
}
*pncolors = ncolors;
}
cleanup_arrays:
LEPT_FREE(rtab);
LEPT_FREE(gtab);
LEPT_FREE(btab);
return na;
}
/*------------------------------------------------------------------*
* Get filled octcube table from colormap *
*------------------------------------------------------------------*/
/*!
* \brief pixcmapToOctcubeLUT()
*
* \param[in] cmap
* \param[in] level significant bits for each of RGB; valid in [1...6]
* \param[in] metric L_MANHATTAN_DISTANCE, L_EUCLIDEAN_DISTANCE
* \return tab[2**3 * level]
*
*
* Notes:
* (1) This function is used to quickly find the colormap color
* that is closest to any rgb color. It is used to assign
* rgb colors to an existing colormap. It can be very expensive
* to search through the entire colormap for the closest color
* to each pixel. Instead, we first set up this table, which is
* populated by the colormap index nearest to each octcube
* color. Then we go through the image; for each pixel,
* do two table lookups: first to generate the octcube index
* from rgb and second to use this table to read out the
* colormap index.
* (2) Do a slight modification for white and black. For level = 4,
* each octcube size is 16. The center of the whitest octcube
* is at (248, 248, 248), which is closer to 242 than 255.
* Consequently, any gray color between 242 and 254 will
* be selected, even if white (255, 255, 255) exists. This is
* typically not optimal, because the original color was
* likely white. Therefore, if white exists in the colormap,
* use it for any rgb color that falls into the most white octcube.
* Do the similar thing for black.
* (3) Here are the actual function calls for quantizing to a
* specified colormap:
* ~ first make the tables that map from rgb --> octcube index
* makeRGBToIndexTables()
* ~ then for each pixel:
* * use the tables to get the octcube index
* getOctcubeIndexFromRGB()
* * use this table to get the nearest color in the colormap
* cmap_index = tab[index]
* (4) Distance can be either manhattan or euclidean.
* (5) In typical use, level = 4 gives reasonable results, and
* level = 5 is slightly better. When this function is used
* for color segmentation, there are typically a small number
* of colors and the number of levels can be small (e.g., level = 3).
*
*/
l_int32 *
pixcmapToOctcubeLUT(PIXCMAP *cmap,
l_int32 level,
l_int32 metric)
{
l_int32 i, k, size, ncolors, mindist, dist, mincolor, index;
l_int32 rval, gval, bval; /* color at center of the octcube */
l_int32 *rmap, *gmap, *bmap, *tab;
PROCNAME("pixcmapToOctcubeLUT");
if (!cmap)
return (l_int32 *)ERROR_PTR("cmap not defined", procName, NULL);
if (level < 1 || level > 6)
return (l_int32 *)ERROR_PTR("level not in {1...6}", procName, NULL);
if (metric != L_MANHATTAN_DISTANCE && metric != L_EUCLIDEAN_DISTANCE)
return (l_int32 *)ERROR_PTR("invalid metric", procName, NULL);
if (octcubeGetCount(level, &size)) /* array size = 2 ** (3 * level) */
return (l_int32 *)ERROR_PTR("size not returned", procName, NULL);
if ((tab = (l_int32 *)LEPT_CALLOC(size, sizeof(l_int32))) == NULL)
return (l_int32 *)ERROR_PTR("tab not allocated", procName, NULL);
ncolors = pixcmapGetCount(cmap);
pixcmapToArrays(cmap, &rmap, &gmap, &bmap, NULL);
/* Assign based on the closest octcube center to the cmap color */
for (i = 0; i < size; i++) {
getRGBFromOctcube(i, level, &rval, &gval, &bval);
mindist = 1000000;
mincolor = 0; /* irrelevant init */
for (k = 0; k < ncolors; k++) {
if (metric == L_MANHATTAN_DISTANCE) {
dist = L_ABS(rval - rmap[k]) + L_ABS(gval - gmap[k]) +
L_ABS(bval - bmap[k]);
} else { /* L_EUCLIDEAN_DISTANCE */
dist = (rval - rmap[k]) * (rval - rmap[k]) +
(gval - gmap[k]) * (gval - gmap[k]) +
(bval - bmap[k]) * (bval - bmap[k]);
}
if (dist < mindist) {
mindist = dist;
mincolor = k;
}
}
tab[i] = mincolor;
}
/* Reset black and white if available in the colormap.
* The darkest octcube is at octindex 0.
* The lightest octcube is at the max octindex. */
pixcmapGetNearestIndex(cmap, 0, 0, 0, &index);
pixcmapGetColor(cmap, index, &rval, &gval, &bval);
if (rval < 7 && gval < 7 && bval < 7) {
tab[0] = index;
}
pixcmapGetNearestIndex(cmap, 255, 255, 255, &index);
pixcmapGetColor(cmap, index, &rval, &gval, &bval);
if (rval > 248 && gval > 248 && bval > 248) {
tab[(1 << (3 * level)) - 1] = index;
}
LEPT_FREE(rmap);
LEPT_FREE(gmap);
LEPT_FREE(bmap);
return tab;
}
/*------------------------------------------------------------------*
* Strip out unused elements in colormap *
*------------------------------------------------------------------*/
/*!
* \brief pixRemoveUnusedColors()
*
* \param[in] pixs colormapped
* \return 0 if OK, 1 on error
*
*
* Notes:
* (1) This is an in-place operation.
* (2) If the image doesn't have a colormap, returns without error.
* (3) Unusued colors are removed from the colormap, and the
* image pixels are re-numbered.
*
*/
l_ok
pixRemoveUnusedColors(PIX *pixs)
{
l_int32 i, j, w, h, d, nc, wpls, val, newval, index, zerofound;
l_int32 rval, gval, bval;
l_uint32 *datas, *lines;
l_int32 *histo, *map1, *map2;
PIXCMAP *cmap, *cmapd;
PROCNAME("pixRemoveUnusedColors");
if (!pixs)
return ERROR_INT("pixs not defined", procName, 1);
if ((cmap = pixGetColormap(pixs)) == NULL)
return 0;
d = pixGetDepth(pixs);
if (d != 2 && d != 4 && d != 8)
return ERROR_INT("d not in {2, 4, 8}", procName, 1);
/* Find which indices are actually used */
nc = pixcmapGetCount(cmap);
if ((histo = (l_int32 *)LEPT_CALLOC(nc, sizeof(l_int32))) == NULL)
return ERROR_INT("histo not made", procName, 1);
pixGetDimensions(pixs, &w, &h, NULL);
wpls = pixGetWpl(pixs);
datas = pixGetData(pixs);
for (i = 0; i < h; i++) {
lines = datas + i * wpls;
for (j = 0; j < w; j++) {
switch (d)
{
case 2:
val = GET_DATA_DIBIT(lines, j);
break;
case 4:
val = GET_DATA_QBIT(lines, j);
break;
case 8:
val = GET_DATA_BYTE(lines, j);
break;
default:
LEPT_FREE(histo);
return ERROR_INT("switch ran off end!", procName, 1);
}
if (val >= nc) {
L_WARNING("cmap index out of bounds!\n", procName);
continue;
}
histo[val]++;
}
}
/* Check if there are any zeroes. If none, quit. */
zerofound = FALSE;
for (i = 0; i < nc; i++) {
if (histo[i] == 0) {
zerofound = TRUE;
break;
}
}
if (!zerofound) {
LEPT_FREE(histo);
return 0;
}
/* Generate mapping tables between indices */
map1 = (l_int32 *)LEPT_CALLOC(nc, sizeof(l_int32));
map2 = (l_int32 *)LEPT_CALLOC(nc, sizeof(l_int32));
index = 0;
for (i = 0; i < nc; i++) {
if (histo[i] != 0) {
map1[index] = i; /* get old index from new */
map2[i] = index; /* get new index from old */
index++;
}
}
/* Generate new colormap and attach to pixs */
cmapd = pixcmapCreate(d);
for (i = 0; i < index; i++) {
pixcmapGetColor(cmap, map1[i], &rval, &gval, &bval);
pixcmapAddColor(cmapd, rval, gval, bval);
}
pixSetColormap(pixs, cmapd);
/* Map pixel (index) values to new cmap */
for (i = 0; i < h; i++) {
lines = datas + i * wpls;
for (j = 0; j < w; j++) {
switch (d)
{
case 2:
val = GET_DATA_DIBIT(lines, j);
newval = map2[val];
SET_DATA_DIBIT(lines, j, newval);
break;
case 4:
val = GET_DATA_QBIT(lines, j);
newval = map2[val];
SET_DATA_QBIT(lines, j, newval);
break;
case 8:
val = GET_DATA_BYTE(lines, j);
newval = map2[val];
SET_DATA_BYTE(lines, j, newval);
break;
default:
LEPT_FREE(histo);
LEPT_FREE(map1);
LEPT_FREE(map2);
return ERROR_INT("switch ran off end!", procName, 1);
}
}
}
LEPT_FREE(histo);
LEPT_FREE(map1);
LEPT_FREE(map2);
return 0;
}
/*------------------------------------------------------------------*
* Find number of occupied octcubes at the specified level *
*------------------------------------------------------------------*/
/*!
* \brief pixNumberOccupiedOctcubes()
*
* \param[in] pix 32 bpp
* \param[in] level of octcube
* \param[in] mincount minimum num pixels in an octcube to be counted;
* -1 to not use
* \param[in] minfract minimum fract of pixels in an octcube to be
* counted; -1 to not use
* \param[out] pncolors number of occupied octcubes
* \return 0 if OK, 1 on error
*
*
* Notes:
* (1) Exactly one of (%mincount, %minfract) must be -1, so, e.g.,
* if %mincount == -1, then we use %minfract.
* (2) If all occupied octcubes are to count, set %mincount == 1.
* Setting %minfract == 0.0 is taken to mean the same thing.
*
*/
l_ok
pixNumberOccupiedOctcubes(PIX *pix,
l_int32 level,
l_int32 mincount,
l_float32 minfract,
l_int32 *pncolors)
{
l_int32 i, j, w, h, d, wpl, ncolors, size, octindex;
l_int32 rval, gval, bval;
l_int32 *carray;
l_uint32 *data, *line, *rtab, *gtab, *btab;
PROCNAME("pixNumberOccupiedOctcubes");
if (!pncolors)
return ERROR_INT("&ncolors not defined", procName, 1);
*pncolors = 0;
if (!pix)
return ERROR_INT("pix not defined", procName, 1);
pixGetDimensions(pix, &w, &h, &d);
if (d != 32)
return ERROR_INT("pix not 32 bpp", procName, 1);
if (level < 1 || level > 6)
return ERROR_INT("invalid level", procName, 1);
if ((mincount < 0 && minfract < 0) || (mincount >= 0.0 && minfract >= 0.0))
return ERROR_INT("invalid mincount/minfract", procName, 1);
if (mincount == 0 || minfract == 0.0)
mincount = 1;
else if (minfract > 0.0)
mincount = L_MIN(1, (l_int32)(minfract * w * h));
if (octcubeGetCount(level, &size)) /* array size = 2 ** (3 * level) */
return ERROR_INT("size not returned", procName, 1);
rtab = gtab = btab = NULL;
makeRGBToIndexTables(level, &rtab, >ab, &btab);
if ((carray = (l_int32 *)LEPT_CALLOC(size, sizeof(l_int32))) == NULL) {
L_ERROR("carray not made\n", procName);
goto cleanup_arrays;
}
/* Mark the occupied octcube leaves */
data = pixGetData(pix);
wpl = pixGetWpl(pix);
for (i = 0; i < h; i++) {
line = data + i * wpl;
for (j = 0; j < w; j++) {
extractRGBValues(line[j], &rval, &gval, &bval);
octindex = rtab[rval] | gtab[gval] | btab[bval];
carray[octindex]++;
}
}
/* Count them */
for (i = 0, ncolors = 0; i < size; i++) {
if (carray[i] >= mincount)
ncolors++;
}
*pncolors = ncolors;
cleanup_arrays:
LEPT_FREE(carray);
LEPT_FREE(rtab);
LEPT_FREE(gtab);
LEPT_FREE(btab);
return 0;
}