The Independent JPEG Group's JPEG software v3
diff --git a/jquant2.c b/jquant2.c
index 2569b20..cf3eab1 100644
--- a/jquant2.c
+++ b/jquant2.c
@@ -1,7 +1,7 @@
/*
* jquant2.c
*
- * Copyright (C) 1991, Thomas G. Lane.
+ * Copyright (C) 1991, 1992, Thomas G. Lane.
* This file is part of the Independent JPEG Group's software.
* For conditions of distribution and use, see the accompanying README file.
*
@@ -16,47 +16,1070 @@
/*
- * Initialize for two-pass color quantization.
+ * This module implements the well-known Heckbert paradigm for color
+ * quantization. Most of the ideas used here can be traced back to
+ * Heckbert's seminal paper
+ * Heckbert, Paul. "Color Image Quantization for Frame Buffer Display",
+ * Proc. SIGGRAPH '82, Computer Graphics v.16 #3 (July 1982), pp 297-304.
+ *
+ * In the first pass over the image, we accumulate a histogram showing the
+ * usage count of each possible color. (To keep the histogram to a reasonable
+ * size, we reduce the precision of the input; typical practice is to retain
+ * 5 or 6 bits per color, so that 8 or 4 different input values are counted
+ * in the same histogram cell.) Next, the color-selection step begins with a
+ * box representing the whole color space, and repeatedly splits the "largest"
+ * remaining box until we have as many boxes as desired colors. Then the mean
+ * color in each remaining box becomes one of the possible output colors.
+ * The second pass over the image maps each input pixel to the closest output
+ * color (optionally after applying a Floyd-Steinberg dithering correction).
+ * This mapping is logically trivial, but making it go fast enough requires
+ * considerable care.
+ *
+ * Heckbert-style quantizers vary a good deal in their policies for choosing
+ * the "largest" box and deciding where to cut it. The particular policies
+ * used here have proved out well in experimental comparisons, but better ones
+ * may yet be found.
+ *
+ * The most significant difference between this quantizer and others is that
+ * this one is intended to operate in YCbCr colorspace, rather than RGB space
+ * as is usually done. Actually we work in scaled YCbCr colorspace, where
+ * Y distances are inflated by a factor of 2 relative to Cb or Cr distances.
+ * The empirical evidence is that distances in this space correspond to
+ * perceptual color differences more closely than do distances in RGB space;
+ * and working in this space is inexpensive within a JPEG decompressor, since
+ * the input data is already in YCbCr form. (We could transform to an even
+ * more perceptually linear space such as Lab or Luv, but that is very slow
+ * and doesn't yield much better results than scaled YCbCr.)
*/
-METHODDEF void
-color_quant_init (decompress_info_ptr cinfo)
-{
- TRACEMS(cinfo->emethods, 1, "color_quant_init 2 pass");
-}
+#define Y_SCALE 2 /* scale Y distances up by this much */
+
+#define MAXNUMCOLORS (MAXJSAMPLE+1) /* maximum size of colormap */
+
+
+/*
+ * First we have the histogram data structure and routines for creating it.
+ *
+ * For work in YCbCr space, it is useful to keep more precision for Y than
+ * for Cb or Cr. We recommend keeping 6 bits for Y and 5 bits each for Cb/Cr.
+ * If you have plenty of memory and cycles, 6 bits all around gives marginally
+ * better results; if you are short of memory, 5 bits all around will save
+ * some space but degrade the results.
+ * To maintain a fully accurate histogram, we'd need to allocate a "long"
+ * (preferably unsigned long) for each cell. In practice this is overkill;
+ * we can get by with 16 bits per cell. Few of the cell counts will overflow,
+ * and clamping those that do overflow to the maximum value will give close-
+ * enough results. This reduces the recommended histogram size from 256Kb
+ * to 128Kb, which is a useful savings on PC-class machines.
+ * (In the second pass the histogram space is re-used for pixel mapping data;
+ * in that capacity, each cell must be able to store zero to the number of
+ * desired colors. 16 bits/cell is plenty for that too.)
+ * Since the JPEG code is intended to run in small memory model on 80x86
+ * machines, we can't just allocate the histogram in one chunk. Instead
+ * of a true 3-D array, we use a row of pointers to 2-D arrays. Each
+ * pointer corresponds to a Y value (typically 2^6 = 64 pointers) and
+ * each 2-D array has 2^5^2 = 1024 or 2^6^2 = 4096 entries. Note that
+ * on 80x86 machines, the pointer row is in near memory but the actual
+ * arrays are in far memory (same arrangement as we use for image arrays).
+ */
+
+#ifndef HIST_Y_BITS /* so you can override from Makefile */
+#define HIST_Y_BITS 6 /* bits of precision in Y histogram */
+#endif
+#ifndef HIST_C_BITS /* so you can override from Makefile */
+#define HIST_C_BITS 5 /* bits of precision in Cb/Cr histogram */
+#endif
+
+#define HIST_Y_ELEMS (1<<HIST_Y_BITS) /* # of elements along histogram axes */
+#define HIST_C_ELEMS (1<<HIST_C_BITS)
+
+/* These are the amounts to shift an input value to get a histogram index.
+ * For a combination 8/12 bit implementation, would need variables here...
+ */
+
+#define Y_SHIFT (BITS_IN_JSAMPLE-HIST_Y_BITS)
+#define C_SHIFT (BITS_IN_JSAMPLE-HIST_C_BITS)
+
+
+typedef UINT16 histcell; /* histogram cell; MUST be an unsigned type */
+
+typedef histcell FAR * histptr; /* for pointers to histogram cells */
+
+typedef histcell hist1d[HIST_C_ELEMS]; /* typedefs for the array */
+typedef hist1d FAR * hist2d; /* type for the Y-level pointers */
+typedef hist2d * hist3d; /* type for top-level pointer */
+
+static hist3d histogram; /* pointer to the histogram */
/*
* Prescan some rows of pixels.
- * Note: this could change the data being written into the big image array,
- * if there were any benefit to doing so. The doit routine is not allowed
- * to modify the big image array, because the memory manager is not required
- * to support multiple write passes on a big image.
+ * In this module the prescan simply updates the histogram, which has been
+ * initialized to zeroes by color_quant_init.
+ * Note: workspace is probably not useful for this routine, but it is passed
+ * anyway to allow some code sharing within the pipeline controller.
*/
METHODDEF void
color_quant_prescan (decompress_info_ptr cinfo, int num_rows,
- JSAMPIMAGE image_data)
+ JSAMPIMAGE image_data, JSAMPARRAY workspace)
{
- TRACEMS1(cinfo->emethods, 2, "color_quant_prescan %d rows", num_rows);
+ register JSAMPROW ptr0, ptr1, ptr2;
+ register histptr histp;
+ register int c0, c1, c2;
+ int row;
+ long col;
+ long width = cinfo->image_width;
+
+ for (row = 0; row < num_rows; row++) {
+ ptr0 = image_data[0][row];
+ ptr1 = image_data[1][row];
+ ptr2 = image_data[2][row];
+ for (col = width; col > 0; col--) {
+ /* get pixel value and index into the histogram */
+ c0 = GETJSAMPLE(*ptr0++) >> Y_SHIFT;
+ c1 = GETJSAMPLE(*ptr1++) >> C_SHIFT;
+ c2 = GETJSAMPLE(*ptr2++) >> C_SHIFT;
+ histp = & histogram[c0][c1][c2];
+ /* increment, check for overflow and undo increment if so. */
+ /* We assume unsigned representation here! */
+ if (++(*histp) == 0)
+ (*histp)--;
+ }
+ }
}
/*
- * This routine makes the final pass over the image data.
+ * Now we have the really interesting routines: selection of a colormap
+ * given the completed histogram.
+ * These routines work with a list of "boxes", each representing a rectangular
+ * subset of the input color space (to histogram precision).
+ */
+
+typedef struct {
+ /* The bounds of the box (inclusive); expressed as histogram indexes */
+ int c0min, c0max;
+ int c1min, c1max;
+ int c2min, c2max;
+ /* The number of nonzero histogram cells within this box */
+ long colorcount;
+ } box;
+typedef box * boxptr;
+
+static boxptr boxlist; /* array with room for desired # of boxes */
+static int numboxes; /* number of boxes currently in boxlist */
+
+static JSAMPARRAY my_colormap; /* the finished colormap (in YCbCr space) */
+
+
+LOCAL boxptr
+find_biggest_color_pop (void)
+/* Find the splittable box with the largest color population */
+/* Returns NULL if no splittable boxes remain */
+{
+ register boxptr boxp;
+ register int i;
+ register long max = 0;
+ boxptr which = NULL;
+
+ for (i = 0, boxp = boxlist; i < numboxes; i++, boxp++) {
+ if (boxp->colorcount > max) {
+ if (boxp->c0max > boxp->c0min || boxp->c1max > boxp->c1min ||
+ boxp->c2max > boxp->c2min) {
+ which = boxp;
+ max = boxp->colorcount;
+ }
+ }
+ }
+ return which;
+}
+
+
+LOCAL boxptr
+find_biggest_volume (void)
+/* Find the splittable box with the largest (scaled) volume */
+/* Returns NULL if no splittable boxes remain */
+{
+ register boxptr boxp;
+ register int i;
+ register INT32 max = 0;
+ register INT32 norm, c0,c1,c2;
+ boxptr which = NULL;
+
+ /* We use 2-norm rather than real volume here.
+ * Some care is needed since the differences are expressed in
+ * histogram-cell units; if HIST_Y_BITS != HIST_C_BITS, we have to
+ * adjust the scaling to get the proper scaled-YCbCr-space distance.
+ * This code won't work right if HIST_Y_BITS < HIST_C_BITS,
+ * but that shouldn't ever be true.
+ * Note norm > 0 iff box is splittable, so need not check separately.
+ */
+
+ for (i = 0, boxp = boxlist; i < numboxes; i++, boxp++) {
+ c0 = (boxp->c0max - boxp->c0min) * Y_SCALE;
+ c1 = (boxp->c1max - boxp->c1min) << (HIST_Y_BITS-HIST_C_BITS);
+ c2 = (boxp->c2max - boxp->c2min) << (HIST_Y_BITS-HIST_C_BITS);
+ norm = c0*c0 + c1*c1 + c2*c2;
+ if (norm > max) {
+ which = boxp;
+ max = norm;
+ }
+ }
+ return which;
+}
+
+
+LOCAL void
+update_box (boxptr boxp)
+/* Shrink the min/max bounds of a box to enclose only nonzero elements, */
+/* and recompute its population */
+{
+ histptr histp;
+ int c0,c1,c2;
+ int c0min,c0max,c1min,c1max,c2min,c2max;
+ long ccount;
+
+ c0min = boxp->c0min; c0max = boxp->c0max;
+ c1min = boxp->c1min; c1max = boxp->c1max;
+ c2min = boxp->c2min; c2max = boxp->c2max;
+
+ if (c0max > c0min)
+ for (c0 = c0min; c0 <= c0max; c0++)
+ for (c1 = c1min; c1 <= c1max; c1++) {
+ histp = & histogram[c0][c1][c2min];
+ for (c2 = c2min; c2 <= c2max; c2++)
+ if (*histp++ != 0) {
+ boxp->c0min = c0min = c0;
+ goto have_c0min;
+ }
+ }
+ have_c0min:
+ if (c0max > c0min)
+ for (c0 = c0max; c0 >= c0min; c0--)
+ for (c1 = c1min; c1 <= c1max; c1++) {
+ histp = & histogram[c0][c1][c2min];
+ for (c2 = c2min; c2 <= c2max; c2++)
+ if (*histp++ != 0) {
+ boxp->c0max = c0max = c0;
+ goto have_c0max;
+ }
+ }
+ have_c0max:
+ if (c1max > c1min)
+ for (c1 = c1min; c1 <= c1max; c1++)
+ for (c0 = c0min; c0 <= c0max; c0++) {
+ histp = & histogram[c0][c1][c2min];
+ for (c2 = c2min; c2 <= c2max; c2++)
+ if (*histp++ != 0) {
+ boxp->c1min = c1min = c1;
+ goto have_c1min;
+ }
+ }
+ have_c1min:
+ if (c1max > c1min)
+ for (c1 = c1max; c1 >= c1min; c1--)
+ for (c0 = c0min; c0 <= c0max; c0++) {
+ histp = & histogram[c0][c1][c2min];
+ for (c2 = c2min; c2 <= c2max; c2++)
+ if (*histp++ != 0) {
+ boxp->c1max = c1max = c1;
+ goto have_c1max;
+ }
+ }
+ have_c1max:
+ if (c2max > c2min)
+ for (c2 = c2min; c2 <= c2max; c2++)
+ for (c0 = c0min; c0 <= c0max; c0++) {
+ histp = & histogram[c0][c1min][c2];
+ for (c1 = c1min; c1 <= c1max; c1++, histp += HIST_C_ELEMS)
+ if (*histp != 0) {
+ boxp->c2min = c2min = c2;
+ goto have_c2min;
+ }
+ }
+ have_c2min:
+ if (c2max > c2min)
+ for (c2 = c2max; c2 >= c2min; c2--)
+ for (c0 = c0min; c0 <= c0max; c0++) {
+ histp = & histogram[c0][c1min][c2];
+ for (c1 = c1min; c1 <= c1max; c1++, histp += HIST_C_ELEMS)
+ if (*histp != 0) {
+ boxp->c2max = c2max = c2;
+ goto have_c2max;
+ }
+ }
+ have_c2max:
+
+ /* Now scan remaining volume of box and compute population */
+ ccount = 0;
+ for (c0 = c0min; c0 <= c0max; c0++)
+ for (c1 = c1min; c1 <= c1max; c1++) {
+ histp = & histogram[c0][c1][c2min];
+ for (c2 = c2min; c2 <= c2max; c2++, histp++)
+ if (*histp != 0) {
+ ccount++;
+ }
+ }
+ boxp->colorcount = ccount;
+}
+
+
+LOCAL void
+median_cut (int desired_colors)
+/* Repeatedly select and split the largest box until we have enough boxes */
+{
+ int n,lb;
+ int c0,c1,c2,cmax;
+ register boxptr b1,b2;
+
+ while (numboxes < desired_colors) {
+ /* Select box to split */
+ /* Current algorithm: by population for first half, then by volume */
+ if (numboxes*2 <= desired_colors) {
+ b1 = find_biggest_color_pop();
+ } else {
+ b1 = find_biggest_volume();
+ }
+ if (b1 == NULL) /* no splittable boxes left! */
+ break;
+ b2 = &boxlist[numboxes]; /* where new box will go */
+ /* Copy the color bounds to the new box. */
+ b2->c0max = b1->c0max; b2->c1max = b1->c1max; b2->c2max = b1->c2max;
+ b2->c0min = b1->c0min; b2->c1min = b1->c1min; b2->c2min = b1->c2min;
+ /* Choose which axis to split the box on.
+ * Current algorithm: longest scaled axis.
+ * See notes in find_biggest_volume about scaling...
+ */
+ c0 = (b1->c0max - b1->c0min) * Y_SCALE;
+ c1 = (b1->c1max - b1->c1min) << (HIST_Y_BITS-HIST_C_BITS);
+ c2 = (b1->c2max - b1->c2min) << (HIST_Y_BITS-HIST_C_BITS);
+ cmax = c0; n = 0;
+ if (c1 > cmax) { cmax = c1; n = 1; }
+ if (c2 > cmax) { n = 2; }
+ /* Choose split point along selected axis, and update box bounds.
+ * Current algorithm: split at halfway point.
+ * (Since the box has been shrunk to minimum volume,
+ * any split will produce two nonempty subboxes.)
+ * Note that lb value is max for lower box, so must be < old max.
+ */
+ switch (n) {
+ case 0:
+ lb = (b1->c0max + b1->c0min) / 2;
+ b1->c0max = lb;
+ b2->c0min = lb+1;
+ break;
+ case 1:
+ lb = (b1->c1max + b1->c1min) / 2;
+ b1->c1max = lb;
+ b2->c1min = lb+1;
+ break;
+ case 2:
+ lb = (b1->c2max + b1->c2min) / 2;
+ b1->c2max = lb;
+ b2->c2min = lb+1;
+ break;
+ }
+ /* Update stats for boxes */
+ update_box(b1);
+ update_box(b2);
+ numboxes++;
+ }
+}
+
+
+LOCAL void
+compute_color (boxptr boxp, int icolor)
+/* Compute representative color for a box, put it in my_colormap[icolor] */
+{
+ /* Current algorithm: mean weighted by pixels (not colors) */
+ /* Note it is important to get the rounding correct! */
+ histptr histp;
+ int c0,c1,c2;
+ int c0min,c0max,c1min,c1max,c2min,c2max;
+ long count;
+ long total = 0;
+ long c0total = 0;
+ long c1total = 0;
+ long c2total = 0;
+
+ c0min = boxp->c0min; c0max = boxp->c0max;
+ c1min = boxp->c1min; c1max = boxp->c1max;
+ c2min = boxp->c2min; c2max = boxp->c2max;
+
+ for (c0 = c0min; c0 <= c0max; c0++)
+ for (c1 = c1min; c1 <= c1max; c1++) {
+ histp = & histogram[c0][c1][c2min];
+ for (c2 = c2min; c2 <= c2max; c2++) {
+ if ((count = *histp++) != 0) {
+ total += count;
+ c0total += ((c0 << Y_SHIFT) + ((1<<Y_SHIFT)>>1)) * count;
+ c1total += ((c1 << C_SHIFT) + ((1<<C_SHIFT)>>1)) * count;
+ c2total += ((c2 << C_SHIFT) + ((1<<C_SHIFT)>>1)) * count;
+ }
+ }
+ }
+
+ my_colormap[0][icolor] = (JSAMPLE) ((c0total + (total>>1)) / total);
+ my_colormap[1][icolor] = (JSAMPLE) ((c1total + (total>>1)) / total);
+ my_colormap[2][icolor] = (JSAMPLE) ((c2total + (total>>1)) / total);
+}
+
+
+LOCAL void
+remap_colormap (decompress_info_ptr cinfo)
+/* Remap the internal colormap to the output colorspace */
+{
+ /* This requires a little trickery since color_convert expects to
+ * deal with 3-D arrays (a 2-D sample array for each component).
+ * We must promote the colormaps into one-row 3-D arrays.
+ */
+ short ci;
+ JSAMPARRAY input_hack[3];
+ JSAMPARRAY output_hack[10]; /* assume no more than 10 output components */
+
+ for (ci = 0; ci < 3; ci++)
+ input_hack[ci] = &(my_colormap[ci]);
+ for (ci = 0; ci < cinfo->color_out_comps; ci++)
+ output_hack[ci] = &(cinfo->colormap[ci]);
+
+ (*cinfo->methods->color_convert) (cinfo, 1,
+ (long) cinfo->actual_number_of_colors,
+ input_hack, output_hack);
+}
+
+
+LOCAL void
+select_colors (decompress_info_ptr cinfo)
+/* Master routine for color selection */
+{
+ int desired = cinfo->desired_number_of_colors;
+ int i;
+
+ /* Allocate workspace for box list */
+ boxlist = (boxptr) (*cinfo->emethods->alloc_small) (desired * SIZEOF(box));
+ /* Initialize one box containing whole space */
+ numboxes = 1;
+ boxlist[0].c0min = 0;
+ boxlist[0].c0max = MAXJSAMPLE >> Y_SHIFT;
+ boxlist[0].c1min = 0;
+ boxlist[0].c1max = MAXJSAMPLE >> C_SHIFT;
+ boxlist[0].c2min = 0;
+ boxlist[0].c2max = MAXJSAMPLE >> C_SHIFT;
+ /* Shrink it to actually-used volume and set its statistics */
+ update_box(& boxlist[0]);
+ /* Perform median-cut to produce final box list */
+ median_cut(desired);
+ /* Compute the representative color for each box, fill my_colormap[] */
+ for (i = 0; i < numboxes; i++)
+ compute_color(& boxlist[i], i);
+ cinfo->actual_number_of_colors = numboxes;
+ /* Produce an output colormap in the desired output colorspace */
+ remap_colormap(cinfo);
+ TRACEMS1(cinfo->emethods, 1, "Selected %d colors for quantization",
+ numboxes);
+ /* Done with the box list */
+ (*cinfo->emethods->free_small) ((void *) boxlist);
+}
+
+
+/*
+ * These routines are concerned with the time-critical task of mapping input
+ * colors to the nearest color in the selected colormap.
+ *
+ * We re-use the histogram space as an "inverse color map", essentially a
+ * cache for the results of nearest-color searches. All colors within a
+ * histogram cell will be mapped to the same colormap entry, namely the one
+ * closest to the cell's center. This may not be quite the closest entry to
+ * the actual input color, but it's almost as good. A zero in the cache
+ * indicates we haven't found the nearest color for that cell yet; the array
+ * is cleared to zeroes before starting the mapping pass. When we find the
+ * nearest color for a cell, its colormap index plus one is recorded in the
+ * cache for future use. The pass2 scanning routines call fill_inverse_cmap
+ * when they need to use an unfilled entry in the cache.
+ *
+ * Our method of efficiently finding nearest colors is based on the "locally
+ * sorted search" idea described by Heckbert and on the incremental distance
+ * calculation described by Spencer W. Thomas in chapter III.1 of Graphics
+ * Gems II (James Arvo, ed. Academic Press, 1991). Thomas points out that
+ * the distances from a given colormap entry to each cell of the histogram can
+ * be computed quickly using an incremental method: the differences between
+ * distances to adjacent cells themselves differ by a constant. This allows a
+ * fairly fast implementation of the "brute force" approach of computing the
+ * distance from every colormap entry to every histogram cell. Unfortunately,
+ * it needs a work array to hold the best-distance-so-far for each histogram
+ * cell (because the inner loop has to be over cells, not colormap entries).
+ * The work array elements have to be INT32s, so the work array would need
+ * 256Kb at our recommended precision. This is not feasible in DOS machines.
+ * Another disadvantage of the brute force approach is that it computes
+ * distances to every cell of the cubical histogram. When working with YCbCr
+ * input, only about a quarter of the cube represents realizable colors, so
+ * many of the cells will never be used and filling them is wasted effort.
+ *
+ * To get around these problems, we apply Thomas' method to compute the
+ * nearest colors for only the cells within a small subbox of the histogram.
+ * The work array need be only as big as the subbox, so the memory usage
+ * problem is solved. A subbox is processed only when some cell in it is
+ * referenced by the pass2 routines, so we will never bother with cells far
+ * outside the realizable color volume. An additional advantage of this
+ * approach is that we can apply Heckbert's locality criterion to quickly
+ * eliminate colormap entries that are far away from the subbox; typically
+ * three-fourths of the colormap entries are rejected by Heckbert's criterion,
+ * and we need not compute their distances to individual cells in the subbox.
+ * The speed of this approach is heavily influenced by the subbox size: too
+ * small means too much overhead, too big loses because Heckbert's criterion
+ * can't eliminate as many colormap entries. Empirically the best subbox
+ * size seems to be about 1/512th of the histogram (1/8th in each direction).
+ *
+ * Thomas' article also describes a refined method which is asymptotically
+ * faster than the brute-force method, but it is also far more complex and
+ * cannot efficiently be applied to small subboxes. It is therefore not
+ * useful for programs intended to be portable to DOS machines. On machines
+ * with plenty of memory, filling the whole histogram in one shot with Thomas'
+ * refined method might be faster than the present code --- but then again,
+ * it might not be any faster, and it's certainly more complicated.
+ */
+
+
+#ifndef BOX_Y_LOG /* so you can override from Makefile */
+#define BOX_Y_LOG (HIST_Y_BITS-3) /* log2(hist cells in update box, Y axis) */
+#endif
+#ifndef BOX_C_LOG /* so you can override from Makefile */
+#define BOX_C_LOG (HIST_C_BITS-3) /* log2(hist cells in update box, C axes) */
+#endif
+
+#define BOX_Y_ELEMS (1<<BOX_Y_LOG) /* # of hist cells in update box */
+#define BOX_C_ELEMS (1<<BOX_C_LOG)
+
+#define BOX_Y_SHIFT (Y_SHIFT + BOX_Y_LOG)
+#define BOX_C_SHIFT (C_SHIFT + BOX_C_LOG)
+
+
+/*
+ * The next three routines implement inverse colormap filling. They could
+ * all be folded into one big routine, but splitting them up this way saves
+ * some stack space (the mindist[] and bestdist[] arrays need not coexist)
+ * and may allow some compilers to produce better code by registerizing more
+ * inner-loop variables.
+ */
+
+LOCAL int
+find_nearby_colors (decompress_info_ptr cinfo, int minc0, int minc1, int minc2,
+ JSAMPLE colorlist[])
+/* Locate the colormap entries close enough to an update box to be candidates
+ * for the nearest entry to some cell(s) in the update box. The update box
+ * is specified by the center coordinates of its first cell. The number of
+ * candidate colormap entries is returned, and their colormap indexes are
+ * placed in colorlist[].
+ * This routine uses Heckbert's "locally sorted search" criterion to select
+ * the colors that need further consideration.
+ */
+{
+ int numcolors = cinfo->actual_number_of_colors;
+ int maxc0, maxc1, maxc2;
+ int centerc0, centerc1, centerc2;
+ int i, x, ncolors;
+ INT32 minmaxdist, min_dist, max_dist, tdist;
+ INT32 mindist[MAXNUMCOLORS]; /* min distance to colormap entry i */
+
+ /* Compute true coordinates of update box's upper corner and center.
+ * Actually we compute the coordinates of the center of the upper-corner
+ * histogram cell, which are the upper bounds of the volume we care about.
+ * Note that since ">>" rounds down, the "center" values may be closer to
+ * min than to max; hence comparisons to them must be "<=", not "<".
+ */
+ maxc0 = minc0 + ((1 << BOX_Y_SHIFT) - (1 << Y_SHIFT));
+ centerc0 = (minc0 + maxc0) >> 1;
+ maxc1 = minc1 + ((1 << BOX_C_SHIFT) - (1 << C_SHIFT));
+ centerc1 = (minc1 + maxc1) >> 1;
+ maxc2 = minc2 + ((1 << BOX_C_SHIFT) - (1 << C_SHIFT));
+ centerc2 = (minc2 + maxc2) >> 1;
+
+ /* For each color in colormap, find:
+ * 1. its minimum squared-distance to any point in the update box
+ * (zero if color is within update box);
+ * 2. its maximum squared-distance to any point in the update box.
+ * Both of these can be found by considering only the corners of the box.
+ * We save the minimum distance for each color in mindist[];
+ * only the smallest maximum distance is of interest.
+ * Note we have to scale Y to get correct distance in scaled space.
+ */
+ minmaxdist = 0x7FFFFFFFL;
+
+ for (i = 0; i < numcolors; i++) {
+ /* We compute the squared-c0-distance term, then add in the other two. */
+ x = GETJSAMPLE(my_colormap[0][i]);
+ if (x < minc0) {
+ tdist = (x - minc0) * Y_SCALE;
+ min_dist = tdist*tdist;
+ tdist = (x - maxc0) * Y_SCALE;
+ max_dist = tdist*tdist;
+ } else if (x > maxc0) {
+ tdist = (x - maxc0) * Y_SCALE;
+ min_dist = tdist*tdist;
+ tdist = (x - minc0) * Y_SCALE;
+ max_dist = tdist*tdist;
+ } else {
+ /* within cell range so no contribution to min_dist */
+ min_dist = 0;
+ if (x <= centerc0) {
+ tdist = (x - maxc0) * Y_SCALE;
+ max_dist = tdist*tdist;
+ } else {
+ tdist = (x - minc0) * Y_SCALE;
+ max_dist = tdist*tdist;
+ }
+ }
+
+ x = GETJSAMPLE(my_colormap[1][i]);
+ if (x < minc1) {
+ tdist = x - minc1;
+ min_dist += tdist*tdist;
+ tdist = x - maxc1;
+ max_dist += tdist*tdist;
+ } else if (x > maxc1) {
+ tdist = x - maxc1;
+ min_dist += tdist*tdist;
+ tdist = x - minc1;
+ max_dist += tdist*tdist;
+ } else {
+ /* within cell range so no contribution to min_dist */
+ if (x <= centerc1) {
+ tdist = x - maxc1;
+ max_dist += tdist*tdist;
+ } else {
+ tdist = x - minc1;
+ max_dist += tdist*tdist;
+ }
+ }
+
+ x = GETJSAMPLE(my_colormap[2][i]);
+ if (x < minc2) {
+ tdist = x - minc2;
+ min_dist += tdist*tdist;
+ tdist = x - maxc2;
+ max_dist += tdist*tdist;
+ } else if (x > maxc2) {
+ tdist = x - maxc2;
+ min_dist += tdist*tdist;
+ tdist = x - minc2;
+ max_dist += tdist*tdist;
+ } else {
+ /* within cell range so no contribution to min_dist */
+ if (x <= centerc2) {
+ tdist = x - maxc2;
+ max_dist += tdist*tdist;
+ } else {
+ tdist = x - minc2;
+ max_dist += tdist*tdist;
+ }
+ }
+
+ mindist[i] = min_dist; /* save away the results */
+ if (max_dist < minmaxdist)
+ minmaxdist = max_dist;
+ }
+
+ /* Now we know that no cell in the update box is more than minmaxdist
+ * away from some colormap entry. Therefore, only colors that are
+ * within minmaxdist of some part of the box need be considered.
+ */
+ ncolors = 0;
+ for (i = 0; i < numcolors; i++) {
+ if (mindist[i] <= minmaxdist)
+ colorlist[ncolors++] = (JSAMPLE) i;
+ }
+ return ncolors;
+}
+
+
+LOCAL void
+find_best_colors (decompress_info_ptr cinfo, int minc0, int minc1, int minc2,
+ int numcolors, JSAMPLE colorlist[], JSAMPLE bestcolor[])
+/* Find the closest colormap entry for each cell in the update box,
+ * given the list of candidate colors prepared by find_nearby_colors.
+ * Return the indexes of the closest entries in the bestcolor[] array.
+ * This routine uses Thomas' incremental distance calculation method to
+ * find the distance from a colormap entry to successive cells in the box.
+ */
+{
+ int ic0, ic1, ic2;
+ int i, icolor;
+ register INT32 * bptr; /* pointer into bestdist[] array */
+ JSAMPLE * cptr; /* pointer into bestcolor[] array */
+ INT32 dist0, dist1; /* initial distance values */
+ register INT32 dist2; /* current distance in inner loop */
+ INT32 xx0, xx1; /* distance increments */
+ register INT32 xx2;
+ INT32 inc0, inc1, inc2; /* initial values for increments */
+ /* This array holds the distance to the nearest-so-far color for each cell */
+ INT32 bestdist[BOX_Y_ELEMS * BOX_C_ELEMS * BOX_C_ELEMS];
+
+ /* Initialize best-distance for each cell of the update box */
+ bptr = bestdist;
+ for (i = BOX_Y_ELEMS*BOX_C_ELEMS*BOX_C_ELEMS-1; i >= 0; i--)
+ *bptr++ = 0x7FFFFFFFL;
+
+ /* For each color selected by find_nearby_colors,
+ * compute its distance to the center of each cell in the box.
+ * If that's less than best-so-far, update best distance and color number.
+ * Note we have to scale Y to get correct distance in scaled space.
+ */
+
+ /* Nominal steps between cell centers ("x" in Thomas article) */
+#define STEP_Y ((1 << Y_SHIFT) * Y_SCALE)
+#define STEP_C (1 << C_SHIFT)
+
+ for (i = 0; i < numcolors; i++) {
+ icolor = GETJSAMPLE(colorlist[i]);
+ /* Compute (square of) distance from minc0/c1/c2 to this color */
+ inc0 = (minc0 - (int) GETJSAMPLE(my_colormap[0][icolor])) * Y_SCALE;
+ dist0 = inc0*inc0;
+ inc1 = minc1 - (int) GETJSAMPLE(my_colormap[1][icolor]);
+ dist0 += inc1*inc1;
+ inc2 = minc2 - (int) GETJSAMPLE(my_colormap[2][icolor]);
+ dist0 += inc2*inc2;
+ /* Form the initial difference increments */
+ inc0 = inc0 * (2 * STEP_Y) + STEP_Y * STEP_Y;
+ inc1 = inc1 * (2 * STEP_C) + STEP_C * STEP_C;
+ inc2 = inc2 * (2 * STEP_C) + STEP_C * STEP_C;
+ /* Now loop over all cells in box, updating distance per Thomas method */
+ bptr = bestdist;
+ cptr = bestcolor;
+ xx0 = inc0;
+ for (ic0 = BOX_Y_ELEMS-1; ic0 >= 0; ic0--) {
+ dist1 = dist0;
+ xx1 = inc1;
+ for (ic1 = BOX_C_ELEMS-1; ic1 >= 0; ic1--) {
+ dist2 = dist1;
+ xx2 = inc2;
+ for (ic2 = BOX_C_ELEMS-1; ic2 >= 0; ic2--) {
+ if (dist2 < *bptr) {
+ *bptr = dist2;
+ *cptr = (JSAMPLE) icolor;
+ }
+ dist2 += xx2;
+ xx2 += 2 * STEP_C * STEP_C;
+ bptr++;
+ cptr++;
+ }
+ dist1 += xx1;
+ xx1 += 2 * STEP_C * STEP_C;
+ }
+ dist0 += xx0;
+ xx0 += 2 * STEP_Y * STEP_Y;
+ }
+ }
+}
+
+
+LOCAL void
+fill_inverse_cmap (decompress_info_ptr cinfo, int c0, int c1, int c2)
+/* Fill the inverse-colormap entries in the update box that contains */
+/* histogram cell c0/c1/c2. (Only that one cell MUST be filled, but */
+/* we can fill as many others as we wish.) */
+{
+ int minc0, minc1, minc2; /* lower left corner of update box */
+ int ic0, ic1, ic2;
+ register JSAMPLE * cptr; /* pointer into bestcolor[] array */
+ register histptr cachep; /* pointer into main cache array */
+ /* This array lists the candidate colormap indexes. */
+ JSAMPLE colorlist[MAXNUMCOLORS];
+ int numcolors; /* number of candidate colors */
+ /* This array holds the actually closest colormap index for each cell. */
+ JSAMPLE bestcolor[BOX_Y_ELEMS * BOX_C_ELEMS * BOX_C_ELEMS];
+
+ /* Convert cell coordinates to update box ID */
+ c0 >>= BOX_Y_LOG;
+ c1 >>= BOX_C_LOG;
+ c2 >>= BOX_C_LOG;
+
+ /* Compute true coordinates of update box's origin corner.
+ * Actually we compute the coordinates of the center of the corner
+ * histogram cell, which are the lower bounds of the volume we care about.
+ */
+ minc0 = (c0 << BOX_Y_SHIFT) + ((1 << Y_SHIFT) >> 1);
+ minc1 = (c1 << BOX_C_SHIFT) + ((1 << C_SHIFT) >> 1);
+ minc2 = (c2 << BOX_C_SHIFT) + ((1 << C_SHIFT) >> 1);
+
+ /* Determine which colormap entries are close enough to be candidates
+ * for the nearest entry to some cell in the update box.
+ */
+ numcolors = find_nearby_colors(cinfo, minc0, minc1, minc2, colorlist);
+
+ /* Determine the actually nearest colors. */
+ find_best_colors(cinfo, minc0, minc1, minc2, numcolors, colorlist,
+ bestcolor);
+
+ /* Save the best color numbers (plus 1) in the main cache array */
+ c0 <<= BOX_Y_LOG; /* convert ID back to base cell indexes */
+ c1 <<= BOX_C_LOG;
+ c2 <<= BOX_C_LOG;
+ cptr = bestcolor;
+ for (ic0 = 0; ic0 < BOX_Y_ELEMS; ic0++) {
+ for (ic1 = 0; ic1 < BOX_C_ELEMS; ic1++) {
+ cachep = & histogram[c0+ic0][c1+ic1][c2];
+ for (ic2 = 0; ic2 < BOX_C_ELEMS; ic2++) {
+ *cachep++ = (histcell) (GETJSAMPLE(*cptr++) + 1);
+ }
+ }
+ }
+}
+
+
+/*
+ * These routines perform second-pass scanning of the image: map each pixel to
+ * the proper colormap index, and output the indexes to the output file.
+ *
* output_workspace is a one-component array of pixel dimensions at least
* as large as the input image strip; it can be used to hold the converted
* pixels' colormap indexes.
*/
METHODDEF void
-final_pass (decompress_info_ptr cinfo, int num_rows,
- JSAMPIMAGE image_data, JSAMPARRAY output_workspace)
+pass2_nodither (decompress_info_ptr cinfo, int num_rows,
+ JSAMPIMAGE image_data, JSAMPARRAY output_workspace)
+/* This version performs no dithering */
{
- TRACEMS1(cinfo->emethods, 2, "final_pass %d rows", num_rows);
- /* for debug purposes, just emit input data */
- /* NB: this only works for PPM output */
- (*cinfo->methods->put_pixel_rows) (cinfo, num_rows, image_data);
+ register JSAMPROW ptr0, ptr1, ptr2, outptr;
+ register histptr cachep;
+ register int c0, c1, c2;
+ int row;
+ long col;
+ long width = cinfo->image_width;
+
+ /* Convert data to colormap indexes, which we save in output_workspace */
+ for (row = 0; row < num_rows; row++) {
+ ptr0 = image_data[0][row];
+ ptr1 = image_data[1][row];
+ ptr2 = image_data[2][row];
+ outptr = output_workspace[row];
+ for (col = width; col > 0; col--) {
+ /* get pixel value and index into the cache */
+ c0 = GETJSAMPLE(*ptr0++) >> Y_SHIFT;
+ c1 = GETJSAMPLE(*ptr1++) >> C_SHIFT;
+ c2 = GETJSAMPLE(*ptr2++) >> C_SHIFT;
+ cachep = & histogram[c0][c1][c2];
+ /* If we have not seen this color before, find nearest colormap entry */
+ /* and update the cache */
+ if (*cachep == 0)
+ fill_inverse_cmap(cinfo, c0,c1,c2);
+ /* Now emit the colormap index for this cell */
+ *outptr++ = (JSAMPLE) (*cachep - 1);
+ }
+ }
+ /* Emit converted rows to the output file */
+ (*cinfo->methods->put_pixel_rows) (cinfo, num_rows, &output_workspace);
+}
+
+
+/* Declarations for Floyd-Steinberg dithering.
+ *
+ * Errors are accumulated into the arrays evenrowerrs[] and oddrowerrs[].
+ * These have resolutions of 1/16th of a pixel count. The error at a given
+ * pixel is propagated to its unprocessed neighbors using the standard F-S
+ * fractions,
+ * ... (here) 7/16
+ * 3/16 5/16 1/16
+ * We work left-to-right on even rows, right-to-left on odd rows.
+ *
+ * Each of the arrays has (#columns + 2) entries; the extra entry
+ * at each end saves us from special-casing the first and last pixels.
+ * Each entry is three values long.
+ * In evenrowerrs[], the entries for a component are stored left-to-right, but
+ * in oddrowerrs[] they are stored right-to-left. This means we always
+ * process the current row's error entries in increasing order and the next
+ * row's error entries in decreasing order, regardless of whether we are
+ * working L-to-R or R-to-L in the pixel data!
+ *
+ * Note: on a wide image, we might not have enough room in a PC's near data
+ * segment to hold the error arrays; so they are allocated with alloc_medium.
+ */
+
+#ifdef EIGHT_BIT_SAMPLES
+typedef INT16 FSERROR; /* 16 bits should be enough */
+#else
+typedef INT32 FSERROR; /* may need more than 16 bits? */
+#endif
+
+typedef FSERROR FAR *FSERRPTR; /* pointer to error array (in FAR storage!) */
+
+static FSERRPTR evenrowerrs, oddrowerrs; /* current-row and next-row errors */
+static boolean on_odd_row; /* flag to remember which row we are on */
+
+
+METHODDEF void
+pass2_dither (decompress_info_ptr cinfo, int num_rows,
+ JSAMPIMAGE image_data, JSAMPARRAY output_workspace)
+/* This version performs Floyd-Steinberg dithering */
+{
+ register FSERROR val;
+ register FSERRPTR thisrowerr, nextrowerr;
+ register FSERROR c0, c1, c2;
+ register int pixcode;
+ JSAMPROW ptr0, ptr1, ptr2, outptr;
+ histptr cachep;
+ int dir;
+ long col;
+ int row;
+ long width = cinfo->image_width;
+
+ /* Convert data to colormap indexes, which we save in output_workspace */
+ for (row = 0; row < num_rows; row++) {
+ ptr0 = image_data[0][row];
+ ptr1 = image_data[1][row];
+ ptr2 = image_data[2][row];
+ outptr = output_workspace[row];
+ if (on_odd_row) {
+ /* work right to left in this row */
+ ptr0 += width - 1;
+ ptr1 += width - 1;
+ ptr2 += width - 1;
+ outptr += width - 1;
+ dir = -1;
+ thisrowerr = oddrowerrs + 3;
+ nextrowerr = evenrowerrs + width*3;
+ on_odd_row = FALSE; /* flip for next time */
+ } else {
+ /* work left to right in this row */
+ dir = 1;
+ thisrowerr = evenrowerrs + 3;
+ nextrowerr = oddrowerrs + width*3;
+ on_odd_row = TRUE; /* flip for next time */
+ }
+ /* need only initialize this one entry in nextrowerr */
+ nextrowerr[0] = nextrowerr[1] = nextrowerr[2] = 0;
+ for (col = width; col > 0; col--) {
+ /* Get this pixel's value and add accumulated errors */
+ /* The errors are in units of 1/16th pixel value */
+ val = (GETJSAMPLE(*ptr0) << 4) + thisrowerr[0];
+ if (val <= 0) val = 0; /* must watch for range overflow! */
+ else {
+ val += 8; /* divide by 16 with proper rounding */
+ val >>= 4;
+ if (val > MAXJSAMPLE) val = MAXJSAMPLE;
+ }
+ c0 = val;
+ val = (GETJSAMPLE(*ptr1) << 4) + thisrowerr[1];
+ if (val <= 0) val = 0; /* must watch for range overflow! */
+ else {
+ val += 8; /* divide by 16 with proper rounding */
+ val >>= 4;
+ if (val > MAXJSAMPLE) val = MAXJSAMPLE;
+ }
+ c1 = val;
+ val = (GETJSAMPLE(*ptr2) << 4) + thisrowerr[2];
+ if (val <= 0) val = 0; /* must watch for range overflow! */
+ else {
+ val += 8; /* divide by 16 with proper rounding */
+ val >>= 4;
+ if (val > MAXJSAMPLE) val = MAXJSAMPLE;
+ }
+ c2 = val;
+ /* Index into the cache with adjusted value */
+ cachep = & histogram[c0 >> Y_SHIFT][c1 >> C_SHIFT][c2 >> C_SHIFT];
+ /* If we have not seen this color before, find nearest colormap */
+ /* entry and update the cache */
+ if (*cachep == 0)
+ fill_inverse_cmap(cinfo, c0 >> Y_SHIFT, c1 >> C_SHIFT, c2 >> C_SHIFT);
+ /* Now emit the colormap index for this cell */
+ pixcode = *cachep - 1;
+ *outptr = (JSAMPLE) pixcode;
+ /* Compute representation error for this pixel */
+ c0 -= (FSERROR) GETJSAMPLE(my_colormap[0][pixcode]);
+ c1 -= (FSERROR) GETJSAMPLE(my_colormap[1][pixcode]);
+ c2 -= (FSERROR) GETJSAMPLE(my_colormap[2][pixcode]);
+ /* Propagate error to adjacent pixels */
+ /* Remember that nextrowerr entries are in reverse order! */
+ val = c0 * 2;
+ nextrowerr[0-3] = c0; /* not +=, since not initialized yet */
+ c0 += val; /* form error * 3 */
+ nextrowerr[0+3] += c0;
+ c0 += val; /* form error * 5 */
+ nextrowerr[0 ] += c0;
+ c0 += val; /* form error * 7 */
+ thisrowerr[0+3] += c0;
+ val = c1 * 2;
+ nextrowerr[1-3] = c1; /* not +=, since not initialized yet */
+ c1 += val; /* form error * 3 */
+ nextrowerr[1+3] += c1;
+ c1 += val; /* form error * 5 */
+ nextrowerr[1 ] += c1;
+ c1 += val; /* form error * 7 */
+ thisrowerr[1+3] += c1;
+ val = c2 * 2;
+ nextrowerr[2-3] = c2; /* not +=, since not initialized yet */
+ c2 += val; /* form error * 3 */
+ nextrowerr[2+3] += c2;
+ c2 += val; /* form error * 5 */
+ nextrowerr[2 ] += c2;
+ c2 += val; /* form error * 7 */
+ thisrowerr[2+3] += c2;
+ /* Advance to next column */
+ ptr0 += dir;
+ ptr1 += dir;
+ ptr2 += dir;
+ outptr += dir;
+ thisrowerr += 3; /* cur-row error ptr advances to right */
+ nextrowerr -= 3; /* next-row error ptr advances to left */
+ }
+ }
+ /* Emit converted rows to the output file */
+ (*cinfo->methods->put_pixel_rows) (cinfo, num_rows, &output_workspace);
+}
+
+
+/*
+ * Initialize for two-pass color quantization.
+ */
+
+METHODDEF void
+color_quant_init (decompress_info_ptr cinfo)
+{
+ int i;
+
+ /* Lower bound on # of colors ... somewhat arbitrary as long as > 0 */
+ if (cinfo->desired_number_of_colors < 8)
+ ERREXIT(cinfo->emethods, "Cannot request less than 8 quantized colors");
+ /* Make sure colormap indexes can be represented by JSAMPLEs */
+ if (cinfo->desired_number_of_colors > MAXNUMCOLORS)
+ ERREXIT1(cinfo->emethods, "Cannot request more than %d quantized colors",
+ MAXNUMCOLORS);
+
+ /* Allocate and zero the histogram */
+ histogram = (hist3d) (*cinfo->emethods->alloc_small)
+ (HIST_Y_ELEMS * SIZEOF(hist2d));
+ for (i = 0; i < HIST_Y_ELEMS; i++) {
+ histogram[i] = (hist2d) (*cinfo->emethods->alloc_medium)
+ (HIST_C_ELEMS*HIST_C_ELEMS * SIZEOF(histcell));
+ jzero_far((void FAR *) histogram[i],
+ HIST_C_ELEMS*HIST_C_ELEMS * SIZEOF(histcell));
+ }
+
+ /* Allocate storage for the internal and external colormaps. */
+ /* We do this now since it is FAR storage and may affect the memory */
+ /* manager's space calculations. */
+ my_colormap = (*cinfo->emethods->alloc_small_sarray)
+ ((long) cinfo->desired_number_of_colors,
+ (long) 3);
+ cinfo->colormap = (*cinfo->emethods->alloc_small_sarray)
+ ((long) cinfo->desired_number_of_colors,
+ (long) cinfo->color_out_comps);
+
+ /* Allocate Floyd-Steinberg workspace if necessary */
+ /* This isn't needed until pass 2, but again it is FAR storage. */
+ if (cinfo->use_dithering) {
+ size_t arraysize = (size_t) ((cinfo->image_width + 2L) * 3L * SIZEOF(FSERROR));
+
+ evenrowerrs = (FSERRPTR) (*cinfo->emethods->alloc_medium) (arraysize);
+ oddrowerrs = (FSERRPTR) (*cinfo->emethods->alloc_medium) (arraysize);
+ /* we only need to zero the forward contribution for current row. */
+ jzero_far((void FAR *) evenrowerrs, arraysize);
+ on_odd_row = FALSE;
+ }
+
+ /* Indicate number of passes needed, excluding the prescan pass. */
+ cinfo->total_passes++; /* I always use one pass */
}
@@ -73,8 +1096,24 @@
METHODDEF void
color_quant_doit (decompress_info_ptr cinfo, quantize_caller_ptr source_method)
{
- TRACEMS(cinfo->emethods, 1, "color_quant_doit 2 pass");
- (*source_method) (cinfo, final_pass);
+ int i;
+
+ /* Select the representative colors */
+ select_colors(cinfo);
+ /* Pass the external colormap to the output module. */
+ /* NB: the output module may continue to use the colormap until shutdown. */
+ (*cinfo->methods->put_color_map) (cinfo, cinfo->actual_number_of_colors,
+ cinfo->colormap);
+ /* Re-zero the histogram so pass 2 can use it as nearest-color cache */
+ for (i = 0; i < HIST_Y_ELEMS; i++) {
+ jzero_far((void FAR *) histogram[i],
+ HIST_C_ELEMS*HIST_C_ELEMS * SIZEOF(histcell));
+ }
+ /* Perform pass 2 */
+ if (cinfo->use_dithering)
+ (*source_method) (cinfo, pass2_dither);
+ else
+ (*source_method) (cinfo, pass2_nodither);
}
@@ -85,7 +1124,9 @@
METHODDEF void
color_quant_term (decompress_info_ptr cinfo)
{
- TRACEMS(cinfo->emethods, 1, "color_quant_term 2 pass");
+ /* no work (we let free_all release the histogram/cache and colormaps) */
+ /* Note that we *mustn't* free the external colormap before free_all, */
+ /* since output module may use it! */
}
@@ -110,7 +1151,9 @@
jsel2quantize (decompress_info_ptr cinfo)
{
if (cinfo->two_pass_quantize) {
- /* just one alternative for the moment */
+ /* Make sure jdmaster didn't give me a case I can't handle */
+ if (cinfo->num_components != 3 || cinfo->jpeg_color_space != CS_YCbCr)
+ ERREXIT(cinfo->emethods, "2-pass quantization only handles YCbCr input");
cinfo->methods->color_quant_init = color_quant_init;
cinfo->methods->color_quant_prescan = color_quant_prescan;
cinfo->methods->color_quant_doit = color_quant_doit;