libjpeg update

git-svn-id: http://svn.miranda-ng.org/main/trunk@5843 1316c22d-e87f-b044-9b9b-93d7a3e3ba9c

1 files changed, 1311 insertions, 1311 deletions

diff --git a/plugins/AdvaImg/src/LibJPEG/jquant2.c b/plugins/AdvaImg/src/LibJPEG/jquant2.c
index 38fc2af7a5..f7e351f2ac 100644
--- a/plugins/AdvaImg/src/LibJPEG/jquant2.c
+++ b/plugins/AdvaImg/src/LibJPEG/jquant2.c
@@ -1,1311 +1,1311 @@
-/*
- * jquant2.c
- *
- * Copyright (C) 1991-1996, Thomas G. Lane.
- * Modified 2011 by Guido Vollbeding.
- * This file is part of the Independent JPEG Group's software.
- * For conditions of distribution and use, see the accompanying README file.
- *
- * This file contains 2-pass color quantization (color mapping) routines.
- * These routines provide selection of a custom color map for an image,
- * followed by mapping of the image to that color map, with optional
- * Floyd-Steinberg dithering.
- * It is also possible to use just the second pass to map to an arbitrary
- * externally-given color map.
- *
- * Note: ordered dithering is not supported, since there isn't any fast
- * way to compute intercolor distances; it's unclear that ordered dither's
- * fundamental assumptions even hold with an irregularly spaced color map.
- */
-
-#define JPEG_INTERNALS
-#include "jinclude.h"
-#include "jpeglib.h"
-
-#ifdef QUANT_2PASS_SUPPORTED
-
-
-/*
- * 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.
- *
- * In earlier versions of the IJG code, this module quantized in YCbCr color
- * space, processing the raw upsampled data without a color conversion step.
- * This allowed the color conversion math to be done only once per colormap
- * entry, not once per pixel.  However, that optimization precluded other
- * useful optimizations (such as merging color conversion with upsampling)
- * and it also interfered with desired capabilities such as quantizing to an
- * externally-supplied colormap.  We have therefore abandoned that approach.
- * The present code works in the post-conversion color space, typically RGB.
- *
- * To improve the visual quality of the results, we actually work in scaled
- * RGB space, giving G distances more weight than R, and R in turn more than
- * B.  To do everything in integer math, we must use integer scale factors.
- * The 2/3/1 scale factors used here correspond loosely to the relative
- * weights of the colors in the NTSC grayscale equation.
- * If you want to use this code to quantize a non-RGB color space, you'll
- * probably need to change these scale factors.
- */
-
-#define R_SCALE 2		/* scale R distances by this much */
-#define G_SCALE 3		/* scale G distances by this much */
-#define B_SCALE 1		/* and B by this much */
-
-/* Relabel R/G/B as components 0/1/2, respecting the RGB ordering defined
- * in jmorecfg.h.  As the code stands, it will do the right thing for R,G,B
- * and B,G,R orders.  If you define some other weird order in jmorecfg.h,
- * you'll get compile errors until you extend this logic.  In that case
- * you'll probably want to tweak the histogram sizes too.
- */
-
-#if RGB_RED == 0
-#define C0_SCALE R_SCALE
-#endif
-#if RGB_BLUE == 0
-#define C0_SCALE B_SCALE
-#endif
-#if RGB_GREEN == 1
-#define C1_SCALE G_SCALE
-#endif
-#if RGB_RED == 2
-#define C2_SCALE R_SCALE
-#endif
-#if RGB_BLUE == 2
-#define C2_SCALE B_SCALE
-#endif
-
-
-/*
- * First we have the histogram data structure and routines for creating it.
- *
- * The number of bits of precision can be adjusted by changing these symbols.
- * We recommend keeping 6 bits for G and 5 each for R and B.
- * 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 C0 value (typically 2^5 = 32 pointers) and
- * each 2-D array has 2^6*2^5 = 2048 or 2^6*2^6 = 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).
- */
-
-#define MAXNUMCOLORS  (MAXJSAMPLE+1) /* maximum size of colormap */
-
-/* These will do the right thing for either R,G,B or B,G,R color order,
- * but you may not like the results for other color orders.
- */
-#define HIST_C0_BITS  5		/* bits of precision in R/B histogram */
-#define HIST_C1_BITS  6		/* bits of precision in G histogram */
-#define HIST_C2_BITS  5		/* bits of precision in B/R histogram */
-
-/* Number of elements along histogram axes. */
-#define HIST_C0_ELEMS  (1<<HIST_C0_BITS)
-#define HIST_C1_ELEMS  (1<<HIST_C1_BITS)
-#define HIST_C2_ELEMS  (1<<HIST_C2_BITS)
-
-/* These are the amounts to shift an input value to get a histogram index. */
-#define C0_SHIFT  (BITS_IN_JSAMPLE-HIST_C0_BITS)
-#define C1_SHIFT  (BITS_IN_JSAMPLE-HIST_C1_BITS)
-#define C2_SHIFT  (BITS_IN_JSAMPLE-HIST_C2_BITS)
-
-
-typedef UINT16 histcell;	/* histogram cell; prefer an unsigned type */
-
-typedef histcell FAR * histptr;	/* for pointers to histogram cells */
-
-typedef histcell hist1d[HIST_C2_ELEMS]; /* typedefs for the array */
-typedef hist1d FAR * hist2d;	/* type for the 2nd-level pointers */
-typedef hist2d * hist3d;	/* type for top-level pointer */
-
-
-/* Declarations for Floyd-Steinberg dithering.
- *
- * Errors are accumulated into the array fserrors[], at a resolution of
- * 1/16th of a pixel count.  The error at a given pixel is propagated
- * to its not-yet-processed 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.
- *
- * We can get away with a single array (holding one row's worth of errors)
- * by using it to store the current row's errors at pixel columns not yet
- * processed, but the next row's errors at columns already processed.  We
- * need only a few extra variables to hold the errors immediately around the
- * current column.  (If we are lucky, those variables are in registers, but
- * even if not, they're probably cheaper to access than array elements are.)
- *
- * The fserrors[] array 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, one value for each color component.
- *
- * Note: on a wide image, we might not have enough room in a PC's near data
- * segment to hold the error array; so it is allocated with alloc_large.
- */
-
-#if BITS_IN_JSAMPLE == 8
-typedef INT16 FSERROR;		/* 16 bits should be enough */
-typedef int LOCFSERROR;		/* use 'int' for calculation temps */
-#else
-typedef INT32 FSERROR;		/* may need more than 16 bits */
-typedef INT32 LOCFSERROR;	/* be sure calculation temps are big enough */
-#endif
-
-typedef FSERROR FAR *FSERRPTR;	/* pointer to error array (in FAR storage!) */
-
-
-/* Private subobject */
-
-typedef struct {
-  struct jpeg_color_quantizer pub; /* public fields */
-
-  /* Space for the eventually created colormap is stashed here */
-  JSAMPARRAY sv_colormap;	/* colormap allocated at init time */
-  int desired;			/* desired # of colors = size of colormap */
-
-  /* Variables for accumulating image statistics */
-  hist3d histogram;		/* pointer to the histogram */
-
-  boolean needs_zeroed;		/* TRUE if next pass must zero histogram */
-
-  /* Variables for Floyd-Steinberg dithering */
-  FSERRPTR fserrors;		/* accumulated errors */
-  boolean on_odd_row;		/* flag to remember which row we are on */
-  int * error_limiter;		/* table for clamping the applied error */
-} my_cquantizer;
-
-typedef my_cquantizer * my_cquantize_ptr;
-
-
-/*
- * Prescan some rows of pixels.
- * In this module the prescan simply updates the histogram, which has been
- * initialized to zeroes by start_pass.
- * An output_buf parameter is required by the method signature, but no data
- * is actually output (in fact the buffer controller is probably passing a
- * NULL pointer).
- */
-
-METHODDEF(void)
-prescan_quantize (j_decompress_ptr cinfo, JSAMPARRAY input_buf,
-		  JSAMPARRAY output_buf, int num_rows)
-{
-  my_cquantize_ptr cquantize = (my_cquantize_ptr) cinfo->cquantize;
-  register JSAMPROW ptr;
-  register histptr histp;
-  register hist3d histogram = cquantize->histogram;
-  int row;
-  JDIMENSION col;
-  JDIMENSION width = cinfo->output_width;
-
-  for (row = 0; row < num_rows; row++) {
-    ptr = input_buf[row];
-    for (col = width; col > 0; col--) {
-      /* get pixel value and index into the histogram */
-      histp = & histogram[GETJSAMPLE(ptr[0]) >> C0_SHIFT]
-			 [GETJSAMPLE(ptr[1]) >> C1_SHIFT]
-			 [GETJSAMPLE(ptr[2]) >> C2_SHIFT];
-      /* increment, check for overflow and undo increment if so. */
-      if (++(*histp) <= 0)
-	(*histp)--;
-      ptr += 3;
-    }
-  }
-}
-
-
-/*
- * Next 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 volume (actually 2-norm) of the box */
-  INT32 volume;
-  /* The number of nonzero histogram cells within this box */
-  long colorcount;
-} box;
-
-typedef box * boxptr;
-
-
-LOCAL(boxptr)
-find_biggest_color_pop (boxptr boxlist, int numboxes)
-/* Find the splittable box with the largest color population */
-/* Returns NULL if no splittable boxes remain */
-{
-  register boxptr boxp;
-  register int i;
-  register long maxc = 0;
-  boxptr which = NULL;
-  
-  for (i = 0, boxp = boxlist; i < numboxes; i++, boxp++) {
-    if (boxp->colorcount > maxc && boxp->volume > 0) {
-      which = boxp;
-      maxc = boxp->colorcount;
-    }
-  }
-  return which;
-}
-
-
-LOCAL(boxptr)
-find_biggest_volume (boxptr boxlist, int numboxes)
-/* Find the splittable box with the largest (scaled) volume */
-/* Returns NULL if no splittable boxes remain */
-{
-  register boxptr boxp;
-  register int i;
-  register INT32 maxv = 0;
-  boxptr which = NULL;
-  
-  for (i = 0, boxp = boxlist; i < numboxes; i++, boxp++) {
-    if (boxp->volume > maxv) {
-      which = boxp;
-      maxv = boxp->volume;
-    }
-  }
-  return which;
-}
-
-
-LOCAL(void)
-update_box (j_decompress_ptr cinfo, boxptr boxp)
-/* Shrink the min/max bounds of a box to enclose only nonzero elements, */
-/* and recompute its volume and population */
-{
-  my_cquantize_ptr cquantize = (my_cquantize_ptr) cinfo->cquantize;
-  hist3d histogram = cquantize->histogram;
-  histptr histp;
-  int c0,c1,c2;
-  int c0min,c0max,c1min,c1max,c2min,c2max;
-  INT32 dist0,dist1,dist2;
-  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_C2_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_C2_ELEMS)
-	  if (*histp != 0) {
-	    boxp->c2max = c2max = c2;
-	    goto have_c2max;
-	  }
-      }
- have_c2max:
-
-  /* Update box volume.
-   * We use 2-norm rather than real volume here; this biases the method
-   * against making long narrow boxes, and it has the side benefit that
-   * a box is splittable iff norm > 0.
-   * Since the differences are expressed in histogram-cell units,
-   * we have to shift back to JSAMPLE units to get consistent distances;
-   * after which, we scale according to the selected distance scale factors.
-   */
-  dist0 = ((c0max - c0min) << C0_SHIFT) * C0_SCALE;
-  dist1 = ((c1max - c1min) << C1_SHIFT) * C1_SCALE;
-  dist2 = ((c2max - c2min) << C2_SHIFT) * C2_SCALE;
-  boxp->volume = dist0*dist0 + dist1*dist1 + dist2*dist2;
-  
-  /* 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(int)
-median_cut (j_decompress_ptr cinfo, boxptr boxlist, int numboxes,
-	    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(boxlist, numboxes);
-    } else {
-      b1 = find_biggest_volume(boxlist, numboxes);
-    }
-    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 update_box about scaling distances.
-     */
-    c0 = ((b1->c0max - b1->c0min) << C0_SHIFT) * C0_SCALE;
-    c1 = ((b1->c1max - b1->c1min) << C1_SHIFT) * C1_SCALE;
-    c2 = ((b1->c2max - b1->c2min) << C2_SHIFT) * C2_SCALE;
-    /* We want to break any ties in favor of green, then red, blue last.
-     * This code does the right thing for R,G,B or B,G,R color orders only.
-     */
-#if RGB_RED == 0
-    cmax = c1; n = 1;
-    if (c0 > cmax) { cmax = c0; n = 0; }
-    if (c2 > cmax) { n = 2; }
-#else
-    cmax = c1; n = 1;
-    if (c2 > cmax) { cmax = c2; n = 2; }
-    if (c0 > cmax) { n = 0; }
-#endif
-    /* 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(cinfo, b1);
-    update_box(cinfo, b2);
-    numboxes++;
-  }
-  return numboxes;
-}
-
-
-LOCAL(void)
-compute_color (j_decompress_ptr cinfo, boxptr boxp, int icolor)
-/* Compute representative color for a box, put it in colormap[icolor] */
-{
-  /* Current algorithm: mean weighted by pixels (not colors) */
-  /* Note it is important to get the rounding correct! */
-  my_cquantize_ptr cquantize = (my_cquantize_ptr) cinfo->cquantize;
-  hist3d histogram = cquantize->histogram;
-  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 << C0_SHIFT) + ((1<<C0_SHIFT)>>1)) * count;
-	  c1total += ((c1 << C1_SHIFT) + ((1<<C1_SHIFT)>>1)) * count;
-	  c2total += ((c2 << C2_SHIFT) + ((1<<C2_SHIFT)>>1)) * count;
-	}
-      }
-    }
-  
-  cinfo->colormap[0][icolor] = (JSAMPLE) ((c0total + (total>>1)) / total);
-  cinfo->colormap[1][icolor] = (JSAMPLE) ((c1total + (total>>1)) / total);
-  cinfo->colormap[2][icolor] = (JSAMPLE) ((c2total + (total>>1)) / total);
-}
-
-
-LOCAL(void)
-select_colors (j_decompress_ptr cinfo, int desired_colors)
-/* Master routine for color selection */
-{
-  boxptr boxlist;
-  int numboxes;
-  int i;
-
-  /* Allocate workspace for box list */
-  boxlist = (boxptr) (*cinfo->mem->alloc_small)
-    ((j_common_ptr) cinfo, JPOOL_IMAGE, desired_colors * SIZEOF(box));
-  /* Initialize one box containing whole space */
-  numboxes = 1;
-  boxlist[0].c0min = 0;
-  boxlist[0].c0max = MAXJSAMPLE >> C0_SHIFT;
-  boxlist[0].c1min = 0;
-  boxlist[0].c1max = MAXJSAMPLE >> C1_SHIFT;
-  boxlist[0].c2min = 0;
-  boxlist[0].c2max = MAXJSAMPLE >> C2_SHIFT;
-  /* Shrink it to actually-used volume and set its statistics */
-  update_box(cinfo, & boxlist[0]);
-  /* Perform median-cut to produce final box list */
-  numboxes = median_cut(cinfo, boxlist, numboxes, desired_colors);
-  /* Compute the representative color for each box, fill colormap */
-  for (i = 0; i < numboxes; i++)
-    compute_color(cinfo, & boxlist[i], i);
-  cinfo->actual_number_of_colors = numboxes;
-  TRACEMS1(cinfo, 1, JTRC_QUANT_SELECTED, numboxes);
-}
-
-
-/*
- * 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.
- *
- * 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.  Furthermore, we need not fill subboxes that are never
- * referenced in pass2; many images use only part of the color gamut, so a
- * fair amount of work is saved.  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.
- */
-
-
-/* log2(histogram cells in update box) for each axis; this can be adjusted */
-#define BOX_C0_LOG  (HIST_C0_BITS-3)
-#define BOX_C1_LOG  (HIST_C1_BITS-3)
-#define BOX_C2_LOG  (HIST_C2_BITS-3)
-
-#define BOX_C0_ELEMS  (1<<BOX_C0_LOG) /* # of hist cells in update box */
-#define BOX_C1_ELEMS  (1<<BOX_C1_LOG)
-#define BOX_C2_ELEMS  (1<<BOX_C2_LOG)
-
-#define BOX_C0_SHIFT  (C0_SHIFT + BOX_C0_LOG)
-#define BOX_C1_SHIFT  (C1_SHIFT + BOX_C1_LOG)
-#define BOX_C2_SHIFT  (C2_SHIFT + BOX_C2_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 (j_decompress_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_C0_SHIFT) - (1 << C0_SHIFT));
-  centerc0 = (minc0 + maxc0) >> 1;
-  maxc1 = minc1 + ((1 << BOX_C1_SHIFT) - (1 << C1_SHIFT));
-  centerc1 = (minc1 + maxc1) >> 1;
-  maxc2 = minc2 + ((1 << BOX_C2_SHIFT) - (1 << C2_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.
-   */
-  minmaxdist = 0x7FFFFFFFL;
-
-  for (i = 0; i < numcolors; i++) {
-    /* We compute the squared-c0-distance term, then add in the other two. */
-    x = GETJSAMPLE(cinfo->colormap[0][i]);
-    if (x < minc0) {
-      tdist = (x - minc0) * C0_SCALE;
-      min_dist = tdist*tdist;
-      tdist = (x - maxc0) * C0_SCALE;
-      max_dist = tdist*tdist;
-    } else if (x > maxc0) {
-      tdist = (x - maxc0) * C0_SCALE;
-      min_dist = tdist*tdist;
-      tdist = (x - minc0) * C0_SCALE;
-      max_dist = tdist*tdist;
-    } else {
-      /* within cell range so no contribution to min_dist */
-      min_dist = 0;
-      if (x <= centerc0) {
-	tdist = (x - maxc0) * C0_SCALE;
-	max_dist = tdist*tdist;
-      } else {
-	tdist = (x - minc0) * C0_SCALE;
-	max_dist = tdist*tdist;
-      }
-    }
-
-    x = GETJSAMPLE(cinfo->colormap[1][i]);
-    if (x < minc1) {
-      tdist = (x - minc1) * C1_SCALE;
-      min_dist += tdist*tdist;
-      tdist = (x - maxc1) * C1_SCALE;
-      max_dist += tdist*tdist;
-    } else if (x > maxc1) {
-      tdist = (x - maxc1) * C1_SCALE;
-      min_dist += tdist*tdist;
-      tdist = (x - minc1) * C1_SCALE;
-      max_dist += tdist*tdist;
-    } else {
-      /* within cell range so no contribution to min_dist */
-      if (x <= centerc1) {
-	tdist = (x - maxc1) * C1_SCALE;
-	max_dist += tdist*tdist;
-      } else {
-	tdist = (x - minc1) * C1_SCALE;
-	max_dist += tdist*tdist;
-      }
-    }
-
-    x = GETJSAMPLE(cinfo->colormap[2][i]);
-    if (x < minc2) {
-      tdist = (x - minc2) * C2_SCALE;
-      min_dist += tdist*tdist;
-      tdist = (x - maxc2) * C2_SCALE;
-      max_dist += tdist*tdist;
-    } else if (x > maxc2) {
-      tdist = (x - maxc2) * C2_SCALE;
-      min_dist += tdist*tdist;
-      tdist = (x - minc2) * C2_SCALE;
-      max_dist += tdist*tdist;
-    } else {
-      /* within cell range so no contribution to min_dist */
-      if (x <= centerc2) {
-	tdist = (x - maxc2) * C2_SCALE;
-	max_dist += tdist*tdist;
-      } else {
-	tdist = (x - minc2) * C2_SCALE;
-	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 (j_decompress_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_C0_ELEMS * BOX_C1_ELEMS * BOX_C2_ELEMS];
-
-  /* Initialize best-distance for each cell of the update box */
-  bptr = bestdist;
-  for (i = BOX_C0_ELEMS*BOX_C1_ELEMS*BOX_C2_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.
-   */
-  
-  /* Nominal steps between cell centers ("x" in Thomas article) */
-#define STEP_C0  ((1 << C0_SHIFT) * C0_SCALE)
-#define STEP_C1  ((1 << C1_SHIFT) * C1_SCALE)
-#define STEP_C2  ((1 << C2_SHIFT) * C2_SCALE)
-  
-  for (i = 0; i < numcolors; i++) {
-    icolor = GETJSAMPLE(colorlist[i]);
-    /* Compute (square of) distance from minc0/c1/c2 to this color */
-    inc0 = (minc0 - GETJSAMPLE(cinfo->colormap[0][icolor])) * C0_SCALE;
-    dist0 = inc0*inc0;
-    inc1 = (minc1 - GETJSAMPLE(cinfo->colormap[1][icolor])) * C1_SCALE;
-    dist0 += inc1*inc1;
-    inc2 = (minc2 - GETJSAMPLE(cinfo->colormap[2][icolor])) * C2_SCALE;
-    dist0 += inc2*inc2;
-    /* Form the initial difference increments */
-    inc0 = inc0 * (2 * STEP_C0) + STEP_C0 * STEP_C0;
-    inc1 = inc1 * (2 * STEP_C1) + STEP_C1 * STEP_C1;
-    inc2 = inc2 * (2 * STEP_C2) + STEP_C2 * STEP_C2;
-    /* Now loop over all cells in box, updating distance per Thomas method */
-    bptr = bestdist;
-    cptr = bestcolor;
-    xx0 = inc0;
-    for (ic0 = BOX_C0_ELEMS-1; ic0 >= 0; ic0--) {
-      dist1 = dist0;
-      xx1 = inc1;
-      for (ic1 = BOX_C1_ELEMS-1; ic1 >= 0; ic1--) {
-	dist2 = dist1;
-	xx2 = inc2;
-	for (ic2 = BOX_C2_ELEMS-1; ic2 >= 0; ic2--) {
-	  if (dist2 < *bptr) {
-	    *bptr = dist2;
-	    *cptr = (JSAMPLE) icolor;
-	  }
-	  dist2 += xx2;
-	  xx2 += 2 * STEP_C2 * STEP_C2;
-	  bptr++;
-	  cptr++;
-	}
-	dist1 += xx1;
-	xx1 += 2 * STEP_C1 * STEP_C1;
-      }
-      dist0 += xx0;
-      xx0 += 2 * STEP_C0 * STEP_C0;
-    }
-  }
-}
-
-
-LOCAL(void)
-fill_inverse_cmap (j_decompress_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.) */
-{
-  my_cquantize_ptr cquantize = (my_cquantize_ptr) cinfo->cquantize;
-  hist3d histogram = cquantize->histogram;
-  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_C0_ELEMS * BOX_C1_ELEMS * BOX_C2_ELEMS];
-
-  /* Convert cell coordinates to update box ID */
-  c0 >>= BOX_C0_LOG;
-  c1 >>= BOX_C1_LOG;
-  c2 >>= BOX_C2_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_C0_SHIFT) + ((1 << C0_SHIFT) >> 1);
-  minc1 = (c1 << BOX_C1_SHIFT) + ((1 << C1_SHIFT) >> 1);
-  minc2 = (c2 << BOX_C2_SHIFT) + ((1 << C2_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_C0_LOG;		/* convert ID back to base cell indexes */
-  c1 <<= BOX_C1_LOG;
-  c2 <<= BOX_C2_LOG;
-  cptr = bestcolor;
-  for (ic0 = 0; ic0 < BOX_C0_ELEMS; ic0++) {
-    for (ic1 = 0; ic1 < BOX_C1_ELEMS; ic1++) {
-      cachep = & histogram[c0+ic0][c1+ic1][c2];
-      for (ic2 = 0; ic2 < BOX_C2_ELEMS; ic2++) {
-	*cachep++ = (histcell) (GETJSAMPLE(*cptr++) + 1);
-      }
-    }
-  }
-}
-
-
-/*
- * Map some rows of pixels to the output colormapped representation.
- */
-
-METHODDEF(void)
-pass2_no_dither (j_decompress_ptr cinfo,
-		 JSAMPARRAY input_buf, JSAMPARRAY output_buf, int num_rows)
-/* This version performs no dithering */
-{
-  my_cquantize_ptr cquantize = (my_cquantize_ptr) cinfo->cquantize;
-  hist3d histogram = cquantize->histogram;
-  register JSAMPROW inptr, outptr;
-  register histptr cachep;
-  register int c0, c1, c2;
-  int row;
-  JDIMENSION col;
-  JDIMENSION width = cinfo->output_width;
-
-  for (row = 0; row < num_rows; row++) {
-    inptr = input_buf[row];
-    outptr = output_buf[row];
-    for (col = width; col > 0; col--) {
-      /* get pixel value and index into the cache */
-      c0 = GETJSAMPLE(*inptr++) >> C0_SHIFT;
-      c1 = GETJSAMPLE(*inptr++) >> C1_SHIFT;
-      c2 = GETJSAMPLE(*inptr++) >> C2_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);
-    }
-  }
-}
-
-
-METHODDEF(void)
-pass2_fs_dither (j_decompress_ptr cinfo,
-		 JSAMPARRAY input_buf, JSAMPARRAY output_buf, int num_rows)
-/* This version performs Floyd-Steinberg dithering */
-{
-  my_cquantize_ptr cquantize = (my_cquantize_ptr) cinfo->cquantize;
-  hist3d histogram = cquantize->histogram;
-  register LOCFSERROR cur0, cur1, cur2;	/* current error or pixel value */
-  LOCFSERROR belowerr0, belowerr1, belowerr2; /* error for pixel below cur */
-  LOCFSERROR bpreverr0, bpreverr1, bpreverr2; /* error for below/prev col */
-  register FSERRPTR errorptr;	/* => fserrors[] at column before current */
-  JSAMPROW inptr;		/* => current input pixel */
-  JSAMPROW outptr;		/* => current output pixel */
-  histptr cachep;
-  int dir;			/* +1 or -1 depending on direction */
-  int dir3;			/* 3*dir, for advancing inptr & errorptr */
-  int row;
-  JDIMENSION col;
-  JDIMENSION width = cinfo->output_width;
-  JSAMPLE *range_limit = cinfo->sample_range_limit;
-  int *error_limit = cquantize->error_limiter;
-  JSAMPROW colormap0 = cinfo->colormap[0];
-  JSAMPROW colormap1 = cinfo->colormap[1];
-  JSAMPROW colormap2 = cinfo->colormap[2];
-  SHIFT_TEMPS
-
-  for (row = 0; row < num_rows; row++) {
-    inptr = input_buf[row];
-    outptr = output_buf[row];
-    if (cquantize->on_odd_row) {
-      /* work right to left in this row */
-      inptr += (width-1) * 3;	/* so point to rightmost pixel */
-      outptr += width-1;
-      dir = -1;
-      dir3 = -3;
-      errorptr = cquantize->fserrors + (width+1)*3; /* => entry after last column */
-      cquantize->on_odd_row = FALSE; /* flip for next time */
-    } else {
-      /* work left to right in this row */
-      dir = 1;
-      dir3 = 3;
-      errorptr = cquantize->fserrors; /* => entry before first real column */
-      cquantize->on_odd_row = TRUE; /* flip for next time */
-    }
-    /* Preset error values: no error propagated to first pixel from left */
-    cur0 = cur1 = cur2 = 0;
-    /* and no error propagated to row below yet */
-    belowerr0 = belowerr1 = belowerr2 = 0;
-    bpreverr0 = bpreverr1 = bpreverr2 = 0;
-
-    for (col = width; col > 0; col--) {
-      /* curN holds the error propagated from the previous pixel on the
-       * current line.  Add the error propagated from the previous line
-       * to form the complete error correction term for this pixel, and
-       * round the error term (which is expressed * 16) to an integer.
-       * RIGHT_SHIFT rounds towards minus infinity, so adding 8 is correct
-       * for either sign of the error value.
-       * Note: errorptr points to *previous* column's array entry.
-       */
-      cur0 = RIGHT_SHIFT(cur0 + errorptr[dir3+0] + 8, 4);
-      cur1 = RIGHT_SHIFT(cur1 + errorptr[dir3+1] + 8, 4);
-      cur2 = RIGHT_SHIFT(cur2 + errorptr[dir3+2] + 8, 4);
-      /* Limit the error using transfer function set by init_error_limit.
-       * See comments with init_error_limit for rationale.
-       */
-      cur0 = error_limit[cur0];
-      cur1 = error_limit[cur1];
-      cur2 = error_limit[cur2];
-      /* Form pixel value + error, and range-limit to 0..MAXJSAMPLE.
-       * The maximum error is +- MAXJSAMPLE (or less with error limiting);
-       * this sets the required size of the range_limit array.
-       */
-      cur0 += GETJSAMPLE(inptr[0]);
-      cur1 += GETJSAMPLE(inptr[1]);
-      cur2 += GETJSAMPLE(inptr[2]);
-      cur0 = GETJSAMPLE(range_limit[cur0]);
-      cur1 = GETJSAMPLE(range_limit[cur1]);
-      cur2 = GETJSAMPLE(range_limit[cur2]);
-      /* Index into the cache with adjusted pixel value */
-      cachep = & histogram[cur0>>C0_SHIFT][cur1>>C1_SHIFT][cur2>>C2_SHIFT];
-      /* If we have not seen this color before, find nearest colormap */
-      /* entry and update the cache */
-      if (*cachep == 0)
-	fill_inverse_cmap(cinfo, cur0>>C0_SHIFT,cur1>>C1_SHIFT,cur2>>C2_SHIFT);
-      /* Now emit the colormap index for this cell */
-      { register int pixcode = *cachep - 1;
-	*outptr = (JSAMPLE) pixcode;
-	/* Compute representation error for this pixel */
-	cur0 -= GETJSAMPLE(colormap0[pixcode]);
-	cur1 -= GETJSAMPLE(colormap1[pixcode]);
-	cur2 -= GETJSAMPLE(colormap2[pixcode]);
-      }
-      /* Compute error fractions to be propagated to adjacent pixels.
-       * Add these into the running sums, and simultaneously shift the
-       * next-line error sums left by 1 column.
-       */
-      { register LOCFSERROR bnexterr, delta;
-
-	bnexterr = cur0;	/* Process component 0 */
-	delta = cur0 * 2;
-	cur0 += delta;		/* form error * 3 */
-	errorptr[0] = (FSERROR) (bpreverr0 + cur0);
-	cur0 += delta;		/* form error * 5 */
-	bpreverr0 = belowerr0 + cur0;
-	belowerr0 = bnexterr;
-	cur0 += delta;		/* form error * 7 */
-	bnexterr = cur1;	/* Process component 1 */
-	delta = cur1 * 2;
-	cur1 += delta;		/* form error * 3 */
-	errorptr[1] = (FSERROR) (bpreverr1 + cur1);
-	cur1 += delta;		/* form error * 5 */
-	bpreverr1 = belowerr1 + cur1;
-	belowerr1 = bnexterr;
-	cur1 += delta;		/* form error * 7 */
-	bnexterr = cur2;	/* Process component 2 */
-	delta = cur2 * 2;
-	cur2 += delta;		/* form error * 3 */
-	errorptr[2] = (FSERROR) (bpreverr2 + cur2);
-	cur2 += delta;		/* form error * 5 */
-	bpreverr2 = belowerr2 + cur2;
-	belowerr2 = bnexterr;
-	cur2 += delta;		/* form error * 7 */
-      }
-      /* At this point curN contains the 7/16 error value to be propagated
-       * to the next pixel on the current line, and all the errors for the
-       * next line have been shifted over.  We are therefore ready to move on.
-       */
-      inptr += dir3;		/* Advance pixel pointers to next column */
-      outptr += dir;
-      errorptr += dir3;		/* advance errorptr to current column */
-    }
-    /* Post-loop cleanup: we must unload the final error values into the
-     * final fserrors[] entry.  Note we need not unload belowerrN because
-     * it is for the dummy column before or after the actual array.
-     */
-    errorptr[0] = (FSERROR) bpreverr0; /* unload prev errs into array */
-    errorptr[1] = (FSERROR) bpreverr1;
-    errorptr[2] = (FSERROR) bpreverr2;
-  }
-}
-
-
-/*
- * Initialize the error-limiting transfer function (lookup table).
- * The raw F-S error computation can potentially compute error values of up to
- * +- MAXJSAMPLE.  But we want the maximum correction applied to a pixel to be
- * much less, otherwise obviously wrong pixels will be created.  (Typical
- * effects include weird fringes at color-area boundaries, isolated bright
- * pixels in a dark area, etc.)  The standard advice for avoiding this problem
- * is to ensure that the "corners" of the color cube are allocated as output
- * colors; then repeated errors in the same direction cannot cause cascading
- * error buildup.  However, that only prevents the error from getting
- * completely out of hand; Aaron Giles reports that error limiting improves
- * the results even with corner colors allocated.
- * A simple clamping of the error values to about +- MAXJSAMPLE/8 works pretty
- * well, but the smoother transfer function used below is even better.  Thanks
- * to Aaron Giles for this idea.
- */
-
-LOCAL(void)
-init_error_limit (j_decompress_ptr cinfo)
-/* Allocate and fill in the error_limiter table */
-{
-  my_cquantize_ptr cquantize = (my_cquantize_ptr) cinfo->cquantize;
-  int * table;
-  int in, out;
-
-  table = (int *) (*cinfo->mem->alloc_small)
-    ((j_common_ptr) cinfo, JPOOL_IMAGE, (MAXJSAMPLE*2+1) * SIZEOF(int));
-  table += MAXJSAMPLE;		/* so can index -MAXJSAMPLE .. +MAXJSAMPLE */
-  cquantize->error_limiter = table;
-
-#define STEPSIZE ((MAXJSAMPLE+1)/16)
-  /* Map errors 1:1 up to +- MAXJSAMPLE/16 */
-  out = 0;
-  for (in = 0; in < STEPSIZE; in++, out++) {
-    table[in] = out; table[-in] = -out;
-  }
-  /* Map errors 1:2 up to +- 3*MAXJSAMPLE/16 */
-  for (; in < STEPSIZE*3; in++, out += (in&1) ? 0 : 1) {
-    table[in] = out; table[-in] = -out;
-  }
-  /* Clamp the rest to final out value (which is (MAXJSAMPLE+1)/8) */
-  for (; in <= MAXJSAMPLE; in++) {
-    table[in] = out; table[-in] = -out;
-  }
-#undef STEPSIZE
-}
-
-
-/*
- * Finish up at the end of each pass.
- */
-
-METHODDEF(void)
-finish_pass1 (j_decompress_ptr cinfo)
-{
-  my_cquantize_ptr cquantize = (my_cquantize_ptr) cinfo->cquantize;
-
-  /* Select the representative colors and fill in cinfo->colormap */
-  cinfo->colormap = cquantize->sv_colormap;
-  select_colors(cinfo, cquantize->desired);
-  /* Force next pass to zero the color index table */
-  cquantize->needs_zeroed = TRUE;
-}
-
-
-METHODDEF(void)
-finish_pass2 (j_decompress_ptr cinfo)
-{
-  /* no work */
-}
-
-
-/*
- * Initialize for each processing pass.
- */
-
-METHODDEF(void)
-start_pass_2_quant (j_decompress_ptr cinfo, boolean is_pre_scan)
-{
-  my_cquantize_ptr cquantize = (my_cquantize_ptr) cinfo->cquantize;
-  hist3d histogram = cquantize->histogram;
-  int i;
-
-  /* Only F-S dithering or no dithering is supported. */
-  /* If user asks for ordered dither, give him F-S. */
-  if (cinfo->dither_mode != JDITHER_NONE)
-    cinfo->dither_mode = JDITHER_FS;
-
-  if (is_pre_scan) {
-    /* Set up method pointers */
-    cquantize->pub.color_quantize = prescan_quantize;
-    cquantize->pub.finish_pass = finish_pass1;
-    cquantize->needs_zeroed = TRUE; /* Always zero histogram */
-  } else {
-    /* Set up method pointers */
-    if (cinfo->dither_mode == JDITHER_FS)
-      cquantize->pub.color_quantize = pass2_fs_dither;
-    else
-      cquantize->pub.color_quantize = pass2_no_dither;
-    cquantize->pub.finish_pass = finish_pass2;
-
-    /* Make sure color count is acceptable */
-    i = cinfo->actual_number_of_colors;
-    if (i < 1)
-      ERREXIT1(cinfo, JERR_QUANT_FEW_COLORS, 1);
-    if (i > MAXNUMCOLORS)
-      ERREXIT1(cinfo, JERR_QUANT_MANY_COLORS, MAXNUMCOLORS);
-
-    if (cinfo->dither_mode == JDITHER_FS) {
-      size_t arraysize = (size_t) ((cinfo->output_width + 2) *
-				   (3 * SIZEOF(FSERROR)));
-      /* Allocate Floyd-Steinberg workspace if we didn't already. */
-      if (cquantize->fserrors == NULL)
-	cquantize->fserrors = (FSERRPTR) (*cinfo->mem->alloc_large)
-	  ((j_common_ptr) cinfo, JPOOL_IMAGE, arraysize);
-      /* Initialize the propagated errors to zero. */
-      FMEMZERO((void FAR *) cquantize->fserrors, arraysize);
-      /* Make the error-limit table if we didn't already. */
-      if (cquantize->error_limiter == NULL)
-	init_error_limit(cinfo);
-      cquantize->on_odd_row = FALSE;
-    }
-
-  }
-  /* Zero the histogram or inverse color map, if necessary */
-  if (cquantize->needs_zeroed) {
-    for (i = 0; i < HIST_C0_ELEMS; i++) {
-      FMEMZERO((void FAR *) histogram[i],
-	       HIST_C1_ELEMS*HIST_C2_ELEMS * SIZEOF(histcell));
-    }
-    cquantize->needs_zeroed = FALSE;
-  }
-}
-
-
-/*
- * Switch to a new external colormap between output passes.
- */
-
-METHODDEF(void)
-new_color_map_2_quant (j_decompress_ptr cinfo)
-{
-  my_cquantize_ptr cquantize = (my_cquantize_ptr) cinfo->cquantize;
-
-  /* Reset the inverse color map */
-  cquantize->needs_zeroed = TRUE;
-}
-
-
-/*
- * Module initialization routine for 2-pass color quantization.
- */
-
-GLOBAL(void)
-jinit_2pass_quantizer (j_decompress_ptr cinfo)
-{
-  my_cquantize_ptr cquantize;
-  int i;
-
-  cquantize = (my_cquantize_ptr)
-    (*cinfo->mem->alloc_small) ((j_common_ptr) cinfo, JPOOL_IMAGE,
-				SIZEOF(my_cquantizer));
-  cinfo->cquantize = (struct jpeg_color_quantizer *) cquantize;
-  cquantize->pub.start_pass = start_pass_2_quant;
-  cquantize->pub.new_color_map = new_color_map_2_quant;
-  cquantize->fserrors = NULL;	/* flag optional arrays not allocated */
-  cquantize->error_limiter = NULL;
-
-  /* Make sure jdmaster didn't give me a case I can't handle */
-  if (cinfo->out_color_components != 3)
-    ERREXIT(cinfo, JERR_NOTIMPL);
-
-  /* Allocate the histogram/inverse colormap storage */
-  cquantize->histogram = (hist3d) (*cinfo->mem->alloc_small)
-    ((j_common_ptr) cinfo, JPOOL_IMAGE, HIST_C0_ELEMS * SIZEOF(hist2d));
-  for (i = 0; i < HIST_C0_ELEMS; i++) {
-    cquantize->histogram[i] = (hist2d) (*cinfo->mem->alloc_large)
-      ((j_common_ptr) cinfo, JPOOL_IMAGE,
-       HIST_C1_ELEMS*HIST_C2_ELEMS * SIZEOF(histcell));
-  }
-  cquantize->needs_zeroed = TRUE; /* histogram is garbage now */
-
-  /* Allocate storage for the completed colormap, if required.
-   * We do this now since it is FAR storage and may affect
-   * the memory manager's space calculations.
-   */
-  if (cinfo->enable_2pass_quant) {
-    /* Make sure color count is acceptable */
-    int desired = cinfo->desired_number_of_colors;
-    /* Lower bound on # of colors ... somewhat arbitrary as long as > 0 */
-    if (desired < 8)
-      ERREXIT1(cinfo, JERR_QUANT_FEW_COLORS, 8);
-    /* Make sure colormap indexes can be represented by JSAMPLEs */
-    if (desired > MAXNUMCOLORS)
-      ERREXIT1(cinfo, JERR_QUANT_MANY_COLORS, MAXNUMCOLORS);
-    cquantize->sv_colormap = (*cinfo->mem->alloc_sarray)
-      ((j_common_ptr) cinfo,JPOOL_IMAGE, (JDIMENSION) desired, (JDIMENSION) 3);
-    cquantize->desired = desired;
-  } else
-    cquantize->sv_colormap = NULL;
-
-  /* Only F-S dithering or no dithering is supported. */
-  /* If user asks for ordered dither, give him F-S. */
-  if (cinfo->dither_mode != JDITHER_NONE)
-    cinfo->dither_mode = JDITHER_FS;
-
-  /* Allocate Floyd-Steinberg workspace if necessary.
-   * This isn't really needed until pass 2, but again it is FAR storage.
-   * Although we will cope with a later change in dither_mode,
-   * we do not promise to honor max_memory_to_use if dither_mode changes.
-   */
-  if (cinfo->dither_mode == JDITHER_FS) {
-    cquantize->fserrors = (FSERRPTR) (*cinfo->mem->alloc_large)
-      ((j_common_ptr) cinfo, JPOOL_IMAGE,
-       (size_t) ((cinfo->output_width + 2) * (3 * SIZEOF(FSERROR))));
-    /* Might as well create the error-limiting table too. */
-    init_error_limit(cinfo);
-  }
-}
-
-#endif /* QUANT_2PASS_SUPPORTED */
+/*

+ * jquant2.c

+ *

+ * Copyright (C) 1991-1996, Thomas G. Lane.

+ * Modified 2011 by Guido Vollbeding.

+ * This file is part of the Independent JPEG Group's software.

+ * For conditions of distribution and use, see the accompanying README file.

+ *

+ * This file contains 2-pass color quantization (color mapping) routines.

+ * These routines provide selection of a custom color map for an image,

+ * followed by mapping of the image to that color map, with optional

+ * Floyd-Steinberg dithering.

+ * It is also possible to use just the second pass to map to an arbitrary

+ * externally-given color map.

+ *

+ * Note: ordered dithering is not supported, since there isn't any fast

+ * way to compute intercolor distances; it's unclear that ordered dither's

+ * fundamental assumptions even hold with an irregularly spaced color map.

+ */

+

+#define JPEG_INTERNALS

+#include "jinclude.h"

+#include "jpeglib.h"

+

+#ifdef QUANT_2PASS_SUPPORTED

+

+

+/*

+ * 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.

+ *

+ * In earlier versions of the IJG code, this module quantized in YCbCr color

+ * space, processing the raw upsampled data without a color conversion step.

+ * This allowed the color conversion math to be done only once per colormap

+ * entry, not once per pixel.  However, that optimization precluded other

+ * useful optimizations (such as merging color conversion with upsampling)

+ * and it also interfered with desired capabilities such as quantizing to an

+ * externally-supplied colormap.  We have therefore abandoned that approach.

+ * The present code works in the post-conversion color space, typically RGB.

+ *

+ * To improve the visual quality of the results, we actually work in scaled

+ * RGB space, giving G distances more weight than R, and R in turn more than

+ * B.  To do everything in integer math, we must use integer scale factors.

+ * The 2/3/1 scale factors used here correspond loosely to the relative

+ * weights of the colors in the NTSC grayscale equation.

+ * If you want to use this code to quantize a non-RGB color space, you'll

+ * probably need to change these scale factors.

+ */

+

+#define R_SCALE 2		/* scale R distances by this much */

+#define G_SCALE 3		/* scale G distances by this much */

+#define B_SCALE 1		/* and B by this much */

+

+/* Relabel R/G/B as components 0/1/2, respecting the RGB ordering defined

+ * in jmorecfg.h.  As the code stands, it will do the right thing for R,G,B

+ * and B,G,R orders.  If you define some other weird order in jmorecfg.h,

+ * you'll get compile errors until you extend this logic.  In that case

+ * you'll probably want to tweak the histogram sizes too.

+ */

+

+#if RGB_RED == 0

+#define C0_SCALE R_SCALE

+#endif

+#if RGB_BLUE == 0

+#define C0_SCALE B_SCALE

+#endif

+#if RGB_GREEN == 1

+#define C1_SCALE G_SCALE

+#endif

+#if RGB_RED == 2

+#define C2_SCALE R_SCALE

+#endif

+#if RGB_BLUE == 2

+#define C2_SCALE B_SCALE

+#endif

+

+

+/*

+ * First we have the histogram data structure and routines for creating it.

+ *

+ * The number of bits of precision can be adjusted by changing these symbols.

+ * We recommend keeping 6 bits for G and 5 each for R and B.

+ * 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 C0 value (typically 2^5 = 32 pointers) and

+ * each 2-D array has 2^6*2^5 = 2048 or 2^6*2^6 = 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).

+ */

+

+#define MAXNUMCOLORS  (MAXJSAMPLE+1) /* maximum size of colormap */

+

+/* These will do the right thing for either R,G,B or B,G,R color order,

+ * but you may not like the results for other color orders.

+ */

+#define HIST_C0_BITS  5		/* bits of precision in R/B histogram */

+#define HIST_C1_BITS  6		/* bits of precision in G histogram */

+#define HIST_C2_BITS  5		/* bits of precision in B/R histogram */

+

+/* Number of elements along histogram axes. */

+#define HIST_C0_ELEMS  (1<<HIST_C0_BITS)

+#define HIST_C1_ELEMS  (1<<HIST_C1_BITS)

+#define HIST_C2_ELEMS  (1<<HIST_C2_BITS)

+

+/* These are the amounts to shift an input value to get a histogram index. */

+#define C0_SHIFT  (BITS_IN_JSAMPLE-HIST_C0_BITS)

+#define C1_SHIFT  (BITS_IN_JSAMPLE-HIST_C1_BITS)

+#define C2_SHIFT  (BITS_IN_JSAMPLE-HIST_C2_BITS)

+

+

+typedef UINT16 histcell;	/* histogram cell; prefer an unsigned type */

+

+typedef histcell FAR * histptr;	/* for pointers to histogram cells */

+

+typedef histcell hist1d[HIST_C2_ELEMS]; /* typedefs for the array */

+typedef hist1d FAR * hist2d;	/* type for the 2nd-level pointers */

+typedef hist2d * hist3d;	/* type for top-level pointer */

+

+

+/* Declarations for Floyd-Steinberg dithering.

+ *

+ * Errors are accumulated into the array fserrors[], at a resolution of

+ * 1/16th of a pixel count.  The error at a given pixel is propagated

+ * to its not-yet-processed 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.

+ *

+ * We can get away with a single array (holding one row's worth of errors)

+ * by using it to store the current row's errors at pixel columns not yet

+ * processed, but the next row's errors at columns already processed.  We

+ * need only a few extra variables to hold the errors immediately around the

+ * current column.  (If we are lucky, those variables are in registers, but

+ * even if not, they're probably cheaper to access than array elements are.)

+ *

+ * The fserrors[] array 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, one value for each color component.

+ *

+ * Note: on a wide image, we might not have enough room in a PC's near data

+ * segment to hold the error array; so it is allocated with alloc_large.

+ */

+

+#if BITS_IN_JSAMPLE == 8

+typedef INT16 FSERROR;		/* 16 bits should be enough */

+typedef int LOCFSERROR;		/* use 'int' for calculation temps */

+#else

+typedef INT32 FSERROR;		/* may need more than 16 bits */

+typedef INT32 LOCFSERROR;	/* be sure calculation temps are big enough */

+#endif

+

+typedef FSERROR FAR *FSERRPTR;	/* pointer to error array (in FAR storage!) */

+

+

+/* Private subobject */

+

+typedef struct {

+  struct jpeg_color_quantizer pub; /* public fields */

+

+  /* Space for the eventually created colormap is stashed here */

+  JSAMPARRAY sv_colormap;	/* colormap allocated at init time */

+  int desired;			/* desired # of colors = size of colormap */

+

+  /* Variables for accumulating image statistics */

+  hist3d histogram;		/* pointer to the histogram */

+

+  boolean needs_zeroed;		/* TRUE if next pass must zero histogram */

+

+  /* Variables for Floyd-Steinberg dithering */

+  FSERRPTR fserrors;		/* accumulated errors */

+  boolean on_odd_row;		/* flag to remember which row we are on */

+  int * error_limiter;		/* table for clamping the applied error */

+} my_cquantizer;

+

+typedef my_cquantizer * my_cquantize_ptr;

+

+

+/*

+ * Prescan some rows of pixels.

+ * In this module the prescan simply updates the histogram, which has been

+ * initialized to zeroes by start_pass.

+ * An output_buf parameter is required by the method signature, but no data

+ * is actually output (in fact the buffer controller is probably passing a

+ * NULL pointer).

+ */

+

+METHODDEF(void)

+prescan_quantize (j_decompress_ptr cinfo, JSAMPARRAY input_buf,

+		  JSAMPARRAY output_buf, int num_rows)

+{

+  my_cquantize_ptr cquantize = (my_cquantize_ptr) cinfo->cquantize;

+  register JSAMPROW ptr;

+  register histptr histp;

+  register hist3d histogram = cquantize->histogram;

+  int row;

+  JDIMENSION col;

+  JDIMENSION width = cinfo->output_width;

+

+  for (row = 0; row < num_rows; row++) {

+    ptr = input_buf[row];

+    for (col = width; col > 0; col--) {

+      /* get pixel value and index into the histogram */

+      histp = & histogram[GETJSAMPLE(ptr[0]) >> C0_SHIFT]

+			 [GETJSAMPLE(ptr[1]) >> C1_SHIFT]

+			 [GETJSAMPLE(ptr[2]) >> C2_SHIFT];

+      /* increment, check for overflow and undo increment if so. */

+      if (++(*histp) <= 0)

+	(*histp)--;

+      ptr += 3;

+    }

+  }

+}

+

+

+/*

+ * Next 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 volume (actually 2-norm) of the box */

+  INT32 volume;

+  /* The number of nonzero histogram cells within this box */

+  long colorcount;

+} box;

+

+typedef box * boxptr;

+

+

+LOCAL(boxptr)

+find_biggest_color_pop (boxptr boxlist, int numboxes)

+/* Find the splittable box with the largest color population */

+/* Returns NULL if no splittable boxes remain */

+{

+  register boxptr boxp;

+  register int i;

+  register long maxc = 0;

+  boxptr which = NULL;

+  

+  for (i = 0, boxp = boxlist; i < numboxes; i++, boxp++) {

+    if (boxp->colorcount > maxc && boxp->volume > 0) {

+      which = boxp;

+      maxc = boxp->colorcount;

+    }

+  }

+  return which;

+}

+

+

+LOCAL(boxptr)

+find_biggest_volume (boxptr boxlist, int numboxes)

+/* Find the splittable box with the largest (scaled) volume */

+/* Returns NULL if no splittable boxes remain */

+{

+  register boxptr boxp;

+  register int i;

+  register INT32 maxv = 0;

+  boxptr which = NULL;

+  

+  for (i = 0, boxp = boxlist; i < numboxes; i++, boxp++) {

+    if (boxp->volume > maxv) {

+      which = boxp;

+      maxv = boxp->volume;

+    }

+  }

+  return which;

+}

+

+

+LOCAL(void)

+update_box (j_decompress_ptr cinfo, boxptr boxp)

+/* Shrink the min/max bounds of a box to enclose only nonzero elements, */

+/* and recompute its volume and population */

+{

+  my_cquantize_ptr cquantize = (my_cquantize_ptr) cinfo->cquantize;

+  hist3d histogram = cquantize->histogram;

+  histptr histp;

+  int c0,c1,c2;

+  int c0min,c0max,c1min,c1max,c2min,c2max;

+  INT32 dist0,dist1,dist2;

+  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_C2_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_C2_ELEMS)

+	  if (*histp != 0) {

+	    boxp->c2max = c2max = c2;

+	    goto have_c2max;

+	  }

+      }

+ have_c2max:

+

+  /* Update box volume.

+   * We use 2-norm rather than real volume here; this biases the method

+   * against making long narrow boxes, and it has the side benefit that

+   * a box is splittable iff norm > 0.

+   * Since the differences are expressed in histogram-cell units,

+   * we have to shift back to JSAMPLE units to get consistent distances;

+   * after which, we scale according to the selected distance scale factors.

+   */

+  dist0 = ((c0max - c0min) << C0_SHIFT) * C0_SCALE;

+  dist1 = ((c1max - c1min) << C1_SHIFT) * C1_SCALE;

+  dist2 = ((c2max - c2min) << C2_SHIFT) * C2_SCALE;

+  boxp->volume = dist0*dist0 + dist1*dist1 + dist2*dist2;

+  

+  /* 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(int)

+median_cut (j_decompress_ptr cinfo, boxptr boxlist, int numboxes,

+	    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(boxlist, numboxes);

+    } else {

+      b1 = find_biggest_volume(boxlist, numboxes);

+    }

+    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 update_box about scaling distances.

+     */

+    c0 = ((b1->c0max - b1->c0min) << C0_SHIFT) * C0_SCALE;

+    c1 = ((b1->c1max - b1->c1min) << C1_SHIFT) * C1_SCALE;

+    c2 = ((b1->c2max - b1->c2min) << C2_SHIFT) * C2_SCALE;

+    /* We want to break any ties in favor of green, then red, blue last.

+     * This code does the right thing for R,G,B or B,G,R color orders only.

+     */

+#if RGB_RED == 0

+    cmax = c1; n = 1;

+    if (c0 > cmax) { cmax = c0; n = 0; }

+    if (c2 > cmax) { n = 2; }

+#else

+    cmax = c1; n = 1;

+    if (c2 > cmax) { cmax = c2; n = 2; }

+    if (c0 > cmax) { n = 0; }

+#endif

+    /* 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(cinfo, b1);

+    update_box(cinfo, b2);

+    numboxes++;

+  }

+  return numboxes;

+}

+

+

+LOCAL(void)

+compute_color (j_decompress_ptr cinfo, boxptr boxp, int icolor)

+/* Compute representative color for a box, put it in colormap[icolor] */

+{

+  /* Current algorithm: mean weighted by pixels (not colors) */

+  /* Note it is important to get the rounding correct! */

+  my_cquantize_ptr cquantize = (my_cquantize_ptr) cinfo->cquantize;

+  hist3d histogram = cquantize->histogram;

+  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 << C0_SHIFT) + ((1<<C0_SHIFT)>>1)) * count;

+	  c1total += ((c1 << C1_SHIFT) + ((1<<C1_SHIFT)>>1)) * count;

+	  c2total += ((c2 << C2_SHIFT) + ((1<<C2_SHIFT)>>1)) * count;

+	}

+      }

+    }

+  

+  cinfo->colormap[0][icolor] = (JSAMPLE) ((c0total + (total>>1)) / total);

+  cinfo->colormap[1][icolor] = (JSAMPLE) ((c1total + (total>>1)) / total);

+  cinfo->colormap[2][icolor] = (JSAMPLE) ((c2total + (total>>1)) / total);

+}

+

+

+LOCAL(void)

+select_colors (j_decompress_ptr cinfo, int desired_colors)

+/* Master routine for color selection */

+{

+  boxptr boxlist;

+  int numboxes;

+  int i;

+

+  /* Allocate workspace for box list */

+  boxlist = (boxptr) (*cinfo->mem->alloc_small)

+    ((j_common_ptr) cinfo, JPOOL_IMAGE, desired_colors * SIZEOF(box));

+  /* Initialize one box containing whole space */

+  numboxes = 1;

+  boxlist[0].c0min = 0;

+  boxlist[0].c0max = MAXJSAMPLE >> C0_SHIFT;

+  boxlist[0].c1min = 0;

+  boxlist[0].c1max = MAXJSAMPLE >> C1_SHIFT;

+  boxlist[0].c2min = 0;

+  boxlist[0].c2max = MAXJSAMPLE >> C2_SHIFT;

+  /* Shrink it to actually-used volume and set its statistics */

+  update_box(cinfo, & boxlist[0]);

+  /* Perform median-cut to produce final box list */

+  numboxes = median_cut(cinfo, boxlist, numboxes, desired_colors);

+  /* Compute the representative color for each box, fill colormap */

+  for (i = 0; i < numboxes; i++)

+    compute_color(cinfo, & boxlist[i], i);

+  cinfo->actual_number_of_colors = numboxes;

+  TRACEMS1(cinfo, 1, JTRC_QUANT_SELECTED, numboxes);

+}

+

+

+/*

+ * 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.

+ *

+ * 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.  Furthermore, we need not fill subboxes that are never

+ * referenced in pass2; many images use only part of the color gamut, so a

+ * fair amount of work is saved.  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.

+ */

+

+

+/* log2(histogram cells in update box) for each axis; this can be adjusted */

+#define BOX_C0_LOG  (HIST_C0_BITS-3)

+#define BOX_C1_LOG  (HIST_C1_BITS-3)

+#define BOX_C2_LOG  (HIST_C2_BITS-3)

+

+#define BOX_C0_ELEMS  (1<<BOX_C0_LOG) /* # of hist cells in update box */

+#define BOX_C1_ELEMS  (1<<BOX_C1_LOG)

+#define BOX_C2_ELEMS  (1<<BOX_C2_LOG)

+

+#define BOX_C0_SHIFT  (C0_SHIFT + BOX_C0_LOG)

+#define BOX_C1_SHIFT  (C1_SHIFT + BOX_C1_LOG)

+#define BOX_C2_SHIFT  (C2_SHIFT + BOX_C2_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 (j_decompress_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_C0_SHIFT) - (1 << C0_SHIFT));

+  centerc0 = (minc0 + maxc0) >> 1;

+  maxc1 = minc1 + ((1 << BOX_C1_SHIFT) - (1 << C1_SHIFT));

+  centerc1 = (minc1 + maxc1) >> 1;

+  maxc2 = minc2 + ((1 << BOX_C2_SHIFT) - (1 << C2_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.

+   */

+  minmaxdist = 0x7FFFFFFFL;

+

+  for (i = 0; i < numcolors; i++) {

+    /* We compute the squared-c0-distance term, then add in the other two. */

+    x = GETJSAMPLE(cinfo->colormap[0][i]);

+    if (x < minc0) {

+      tdist = (x - minc0) * C0_SCALE;

+      min_dist = tdist*tdist;

+      tdist = (x - maxc0) * C0_SCALE;

+      max_dist = tdist*tdist;

+    } else if (x > maxc0) {

+      tdist = (x - maxc0) * C0_SCALE;

+      min_dist = tdist*tdist;

+      tdist = (x - minc0) * C0_SCALE;

+      max_dist = tdist*tdist;

+    } else {

+      /* within cell range so no contribution to min_dist */

+      min_dist = 0;

+      if (x <= centerc0) {

+	tdist = (x - maxc0) * C0_SCALE;

+	max_dist = tdist*tdist;

+      } else {

+	tdist = (x - minc0) * C0_SCALE;

+	max_dist = tdist*tdist;

+      }

+    }

+

+    x = GETJSAMPLE(cinfo->colormap[1][i]);

+    if (x < minc1) {

+      tdist = (x - minc1) * C1_SCALE;

+      min_dist += tdist*tdist;

+      tdist = (x - maxc1) * C1_SCALE;

+      max_dist += tdist*tdist;

+    } else if (x > maxc1) {

+      tdist = (x - maxc1) * C1_SCALE;

+      min_dist += tdist*tdist;

+      tdist = (x - minc1) * C1_SCALE;

+      max_dist += tdist*tdist;

+    } else {

+      /* within cell range so no contribution to min_dist */

+      if (x <= centerc1) {

+	tdist = (x - maxc1) * C1_SCALE;

+	max_dist += tdist*tdist;

+      } else {

+	tdist = (x - minc1) * C1_SCALE;

+	max_dist += tdist*tdist;

+      }

+    }

+

+    x = GETJSAMPLE(cinfo->colormap[2][i]);

+    if (x < minc2) {

+      tdist = (x - minc2) * C2_SCALE;

+      min_dist += tdist*tdist;

+      tdist = (x - maxc2) * C2_SCALE;

+      max_dist += tdist*tdist;

+    } else if (x > maxc2) {

+      tdist = (x - maxc2) * C2_SCALE;

+      min_dist += tdist*tdist;

+      tdist = (x - minc2) * C2_SCALE;

+      max_dist += tdist*tdist;

+    } else {

+      /* within cell range so no contribution to min_dist */

+      if (x <= centerc2) {

+	tdist = (x - maxc2) * C2_SCALE;

+	max_dist += tdist*tdist;

+      } else {

+	tdist = (x - minc2) * C2_SCALE;

+	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 (j_decompress_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_C0_ELEMS * BOX_C1_ELEMS * BOX_C2_ELEMS];

+

+  /* Initialize best-distance for each cell of the update box */

+  bptr = bestdist;

+  for (i = BOX_C0_ELEMS*BOX_C1_ELEMS*BOX_C2_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.

+   */

+  

+  /* Nominal steps between cell centers ("x" in Thomas article) */

+#define STEP_C0  ((1 << C0_SHIFT) * C0_SCALE)

+#define STEP_C1  ((1 << C1_SHIFT) * C1_SCALE)

+#define STEP_C2  ((1 << C2_SHIFT) * C2_SCALE)

+  

+  for (i = 0; i < numcolors; i++) {

+    icolor = GETJSAMPLE(colorlist[i]);

+    /* Compute (square of) distance from minc0/c1/c2 to this color */

+    inc0 = (minc0 - GETJSAMPLE(cinfo->colormap[0][icolor])) * C0_SCALE;

+    dist0 = inc0*inc0;

+    inc1 = (minc1 - GETJSAMPLE(cinfo->colormap[1][icolor])) * C1_SCALE;

+    dist0 += inc1*inc1;

+    inc2 = (minc2 - GETJSAMPLE(cinfo->colormap[2][icolor])) * C2_SCALE;

+    dist0 += inc2*inc2;

+    /* Form the initial difference increments */

+    inc0 = inc0 * (2 * STEP_C0) + STEP_C0 * STEP_C0;

+    inc1 = inc1 * (2 * STEP_C1) + STEP_C1 * STEP_C1;

+    inc2 = inc2 * (2 * STEP_C2) + STEP_C2 * STEP_C2;

+    /* Now loop over all cells in box, updating distance per Thomas method */

+    bptr = bestdist;

+    cptr = bestcolor;

+    xx0 = inc0;

+    for (ic0 = BOX_C0_ELEMS-1; ic0 >= 0; ic0--) {

+      dist1 = dist0;

+      xx1 = inc1;

+      for (ic1 = BOX_C1_ELEMS-1; ic1 >= 0; ic1--) {

+	dist2 = dist1;

+	xx2 = inc2;

+	for (ic2 = BOX_C2_ELEMS-1; ic2 >= 0; ic2--) {

+	  if (dist2 < *bptr) {

+	    *bptr = dist2;

+	    *cptr = (JSAMPLE) icolor;

+	  }

+	  dist2 += xx2;

+	  xx2 += 2 * STEP_C2 * STEP_C2;

+	  bptr++;

+	  cptr++;

+	}

+	dist1 += xx1;

+	xx1 += 2 * STEP_C1 * STEP_C1;

+      }

+      dist0 += xx0;

+      xx0 += 2 * STEP_C0 * STEP_C0;

+    }

+  }

+}

+

+

+LOCAL(void)

+fill_inverse_cmap (j_decompress_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.) */

+{

+  my_cquantize_ptr cquantize = (my_cquantize_ptr) cinfo->cquantize;

+  hist3d histogram = cquantize->histogram;

+  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_C0_ELEMS * BOX_C1_ELEMS * BOX_C2_ELEMS];

+

+  /* Convert cell coordinates to update box ID */

+  c0 >>= BOX_C0_LOG;

+  c1 >>= BOX_C1_LOG;

+  c2 >>= BOX_C2_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_C0_SHIFT) + ((1 << C0_SHIFT) >> 1);

+  minc1 = (c1 << BOX_C1_SHIFT) + ((1 << C1_SHIFT) >> 1);

+  minc2 = (c2 << BOX_C2_SHIFT) + ((1 << C2_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_C0_LOG;		/* convert ID back to base cell indexes */

+  c1 <<= BOX_C1_LOG;

+  c2 <<= BOX_C2_LOG;

+  cptr = bestcolor;

+  for (ic0 = 0; ic0 < BOX_C0_ELEMS; ic0++) {

+    for (ic1 = 0; ic1 < BOX_C1_ELEMS; ic1++) {

+      cachep = & histogram[c0+ic0][c1+ic1][c2];

+      for (ic2 = 0; ic2 < BOX_C2_ELEMS; ic2++) {

+	*cachep++ = (histcell) (GETJSAMPLE(*cptr++) + 1);

+      }

+    }

+  }

+}

+

+

+/*

+ * Map some rows of pixels to the output colormapped representation.

+ */

+

+METHODDEF(void)

+pass2_no_dither (j_decompress_ptr cinfo,

+		 JSAMPARRAY input_buf, JSAMPARRAY output_buf, int num_rows)

+/* This version performs no dithering */

+{

+  my_cquantize_ptr cquantize = (my_cquantize_ptr) cinfo->cquantize;

+  hist3d histogram = cquantize->histogram;

+  register JSAMPROW inptr, outptr;

+  register histptr cachep;

+  register int c0, c1, c2;

+  int row;

+  JDIMENSION col;

+  JDIMENSION width = cinfo->output_width;

+

+  for (row = 0; row < num_rows; row++) {

+    inptr = input_buf[row];

+    outptr = output_buf[row];

+    for (col = width; col > 0; col--) {

+      /* get pixel value and index into the cache */

+      c0 = GETJSAMPLE(*inptr++) >> C0_SHIFT;

+      c1 = GETJSAMPLE(*inptr++) >> C1_SHIFT;

+      c2 = GETJSAMPLE(*inptr++) >> C2_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);

+    }

+  }

+}

+

+

+METHODDEF(void)

+pass2_fs_dither (j_decompress_ptr cinfo,

+		 JSAMPARRAY input_buf, JSAMPARRAY output_buf, int num_rows)

+/* This version performs Floyd-Steinberg dithering */

+{

+  my_cquantize_ptr cquantize = (my_cquantize_ptr) cinfo->cquantize;

+  hist3d histogram = cquantize->histogram;

+  register LOCFSERROR cur0, cur1, cur2;	/* current error or pixel value */

+  LOCFSERROR belowerr0, belowerr1, belowerr2; /* error for pixel below cur */

+  LOCFSERROR bpreverr0, bpreverr1, bpreverr2; /* error for below/prev col */

+  register FSERRPTR errorptr;	/* => fserrors[] at column before current */

+  JSAMPROW inptr;		/* => current input pixel */

+  JSAMPROW outptr;		/* => current output pixel */

+  histptr cachep;

+  int dir;			/* +1 or -1 depending on direction */

+  int dir3;			/* 3*dir, for advancing inptr & errorptr */

+  int row;

+  JDIMENSION col;

+  JDIMENSION width = cinfo->output_width;

+  JSAMPLE *range_limit = cinfo->sample_range_limit;

+  int *error_limit = cquantize->error_limiter;

+  JSAMPROW colormap0 = cinfo->colormap[0];

+  JSAMPROW colormap1 = cinfo->colormap[1];

+  JSAMPROW colormap2 = cinfo->colormap[2];

+  SHIFT_TEMPS

+

+  for (row = 0; row < num_rows; row++) {

+    inptr = input_buf[row];

+    outptr = output_buf[row];

+    if (cquantize->on_odd_row) {

+      /* work right to left in this row */

+      inptr += (width-1) * 3;	/* so point to rightmost pixel */

+      outptr += width-1;

+      dir = -1;

+      dir3 = -3;

+      errorptr = cquantize->fserrors + (width+1)*3; /* => entry after last column */

+      cquantize->on_odd_row = FALSE; /* flip for next time */

+    } else {

+      /* work left to right in this row */

+      dir = 1;

+      dir3 = 3;

+      errorptr = cquantize->fserrors; /* => entry before first real column */

+      cquantize->on_odd_row = TRUE; /* flip for next time */

+    }

+    /* Preset error values: no error propagated to first pixel from left */

+    cur0 = cur1 = cur2 = 0;

+    /* and no error propagated to row below yet */

+    belowerr0 = belowerr1 = belowerr2 = 0;

+    bpreverr0 = bpreverr1 = bpreverr2 = 0;

+

+    for (col = width; col > 0; col--) {

+      /* curN holds the error propagated from the previous pixel on the

+       * current line.  Add the error propagated from the previous line

+       * to form the complete error correction term for this pixel, and

+       * round the error term (which is expressed * 16) to an integer.

+       * RIGHT_SHIFT rounds towards minus infinity, so adding 8 is correct

+       * for either sign of the error value.

+       * Note: errorptr points to *previous* column's array entry.

+       */

+      cur0 = RIGHT_SHIFT(cur0 + errorptr[dir3+0] + 8, 4);

+      cur1 = RIGHT_SHIFT(cur1 + errorptr[dir3+1] + 8, 4);

+      cur2 = RIGHT_SHIFT(cur2 + errorptr[dir3+2] + 8, 4);

+      /* Limit the error using transfer function set by init_error_limit.

+       * See comments with init_error_limit for rationale.

+       */

+      cur0 = error_limit[cur0];

+      cur1 = error_limit[cur1];

+      cur2 = error_limit[cur2];

+      /* Form pixel value + error, and range-limit to 0..MAXJSAMPLE.

+       * The maximum error is +- MAXJSAMPLE (or less with error limiting);

+       * this sets the required size of the range_limit array.

+       */

+      cur0 += GETJSAMPLE(inptr[0]);

+      cur1 += GETJSAMPLE(inptr[1]);

+      cur2 += GETJSAMPLE(inptr[2]);

+      cur0 = GETJSAMPLE(range_limit[cur0]);

+      cur1 = GETJSAMPLE(range_limit[cur1]);

+      cur2 = GETJSAMPLE(range_limit[cur2]);

+      /* Index into the cache with adjusted pixel value */

+      cachep = & histogram[cur0>>C0_SHIFT][cur1>>C1_SHIFT][cur2>>C2_SHIFT];

+      /* If we have not seen this color before, find nearest colormap */

+      /* entry and update the cache */

+      if (*cachep == 0)

+	fill_inverse_cmap(cinfo, cur0>>C0_SHIFT,cur1>>C1_SHIFT,cur2>>C2_SHIFT);

+      /* Now emit the colormap index for this cell */

+      { register int pixcode = *cachep - 1;

+	*outptr = (JSAMPLE) pixcode;

+	/* Compute representation error for this pixel */

+	cur0 -= GETJSAMPLE(colormap0[pixcode]);

+	cur1 -= GETJSAMPLE(colormap1[pixcode]);

+	cur2 -= GETJSAMPLE(colormap2[pixcode]);

+      }

+      /* Compute error fractions to be propagated to adjacent pixels.

+       * Add these into the running sums, and simultaneously shift the

+       * next-line error sums left by 1 column.

+       */

+      { register LOCFSERROR bnexterr, delta;

+

+	bnexterr = cur0;	/* Process component 0 */

+	delta = cur0 * 2;

+	cur0 += delta;		/* form error * 3 */

+	errorptr[0] = (FSERROR) (bpreverr0 + cur0);

+	cur0 += delta;		/* form error * 5 */

+	bpreverr0 = belowerr0 + cur0;

+	belowerr0 = bnexterr;

+	cur0 += delta;		/* form error * 7 */

+	bnexterr = cur1;	/* Process component 1 */

+	delta = cur1 * 2;

+	cur1 += delta;		/* form error * 3 */

+	errorptr[1] = (FSERROR) (bpreverr1 + cur1);

+	cur1 += delta;		/* form error * 5 */

+	bpreverr1 = belowerr1 + cur1;

+	belowerr1 = bnexterr;

+	cur1 += delta;		/* form error * 7 */

+	bnexterr = cur2;	/* Process component 2 */

+	delta = cur2 * 2;

+	cur2 += delta;		/* form error * 3 */

+	errorptr[2] = (FSERROR) (bpreverr2 + cur2);

+	cur2 += delta;		/* form error * 5 */

+	bpreverr2 = belowerr2 + cur2;

+	belowerr2 = bnexterr;

+	cur2 += delta;		/* form error * 7 */

+      }

+      /* At this point curN contains the 7/16 error value to be propagated

+       * to the next pixel on the current line, and all the errors for the

+       * next line have been shifted over.  We are therefore ready to move on.

+       */

+      inptr += dir3;		/* Advance pixel pointers to next column */

+      outptr += dir;

+      errorptr += dir3;		/* advance errorptr to current column */

+    }

+    /* Post-loop cleanup: we must unload the final error values into the

+     * final fserrors[] entry.  Note we need not unload belowerrN because

+     * it is for the dummy column before or after the actual array.

+     */

+    errorptr[0] = (FSERROR) bpreverr0; /* unload prev errs into array */

+    errorptr[1] = (FSERROR) bpreverr1;

+    errorptr[2] = (FSERROR) bpreverr2;

+  }

+}

+

+

+/*

+ * Initialize the error-limiting transfer function (lookup table).

+ * The raw F-S error computation can potentially compute error values of up to

+ * +- MAXJSAMPLE.  But we want the maximum correction applied to a pixel to be

+ * much less, otherwise obviously wrong pixels will be created.  (Typical

+ * effects include weird fringes at color-area boundaries, isolated bright

+ * pixels in a dark area, etc.)  The standard advice for avoiding this problem

+ * is to ensure that the "corners" of the color cube are allocated as output

+ * colors; then repeated errors in the same direction cannot cause cascading

+ * error buildup.  However, that only prevents the error from getting

+ * completely out of hand; Aaron Giles reports that error limiting improves

+ * the results even with corner colors allocated.

+ * A simple clamping of the error values to about +- MAXJSAMPLE/8 works pretty

+ * well, but the smoother transfer function used below is even better.  Thanks

+ * to Aaron Giles for this idea.

+ */

+

+LOCAL(void)

+init_error_limit (j_decompress_ptr cinfo)

+/* Allocate and fill in the error_limiter table */

+{

+  my_cquantize_ptr cquantize = (my_cquantize_ptr) cinfo->cquantize;

+  int * table;

+  int in, out;

+

+  table = (int *) (*cinfo->mem->alloc_small)

+    ((j_common_ptr) cinfo, JPOOL_IMAGE, (MAXJSAMPLE*2+1) * SIZEOF(int));

+  table += MAXJSAMPLE;		/* so can index -MAXJSAMPLE .. +MAXJSAMPLE */

+  cquantize->error_limiter = table;

+

+#define STEPSIZE ((MAXJSAMPLE+1)/16)

+  /* Map errors 1:1 up to +- MAXJSAMPLE/16 */

+  out = 0;

+  for (in = 0; in < STEPSIZE; in++, out++) {

+    table[in] = out; table[-in] = -out;

+  }

+  /* Map errors 1:2 up to +- 3*MAXJSAMPLE/16 */

+  for (; in < STEPSIZE*3; in++, out += (in&1) ? 0 : 1) {

+    table[in] = out; table[-in] = -out;

+  }

+  /* Clamp the rest to final out value (which is (MAXJSAMPLE+1)/8) */

+  for (; in <= MAXJSAMPLE; in++) {

+    table[in] = out; table[-in] = -out;

+  }

+#undef STEPSIZE

+}

+

+

+/*

+ * Finish up at the end of each pass.

+ */

+

+METHODDEF(void)

+finish_pass1 (j_decompress_ptr cinfo)

+{

+  my_cquantize_ptr cquantize = (my_cquantize_ptr) cinfo->cquantize;

+

+  /* Select the representative colors and fill in cinfo->colormap */

+  cinfo->colormap = cquantize->sv_colormap;

+  select_colors(cinfo, cquantize->desired);

+  /* Force next pass to zero the color index table */

+  cquantize->needs_zeroed = TRUE;

+}

+

+

+METHODDEF(void)

+finish_pass2 (j_decompress_ptr cinfo)

+{

+  /* no work */

+}

+

+

+/*

+ * Initialize for each processing pass.

+ */

+

+METHODDEF(void)

+start_pass_2_quant (j_decompress_ptr cinfo, boolean is_pre_scan)

+{

+  my_cquantize_ptr cquantize = (my_cquantize_ptr) cinfo->cquantize;

+  hist3d histogram = cquantize->histogram;

+  int i;

+

+  /* Only F-S dithering or no dithering is supported. */

+  /* If user asks for ordered dither, give him F-S. */

+  if (cinfo->dither_mode != JDITHER_NONE)

+    cinfo->dither_mode = JDITHER_FS;

+

+  if (is_pre_scan) {

+    /* Set up method pointers */

+    cquantize->pub.color_quantize = prescan_quantize;

+    cquantize->pub.finish_pass = finish_pass1;

+    cquantize->needs_zeroed = TRUE; /* Always zero histogram */

+  } else {

+    /* Set up method pointers */

+    if (cinfo->dither_mode == JDITHER_FS)

+      cquantize->pub.color_quantize = pass2_fs_dither;

+    else

+      cquantize->pub.color_quantize = pass2_no_dither;

+    cquantize->pub.finish_pass = finish_pass2;

+

+    /* Make sure color count is acceptable */

+    i = cinfo->actual_number_of_colors;

+    if (i < 1)

+      ERREXIT1(cinfo, JERR_QUANT_FEW_COLORS, 1);

+    if (i > MAXNUMCOLORS)

+      ERREXIT1(cinfo, JERR_QUANT_MANY_COLORS, MAXNUMCOLORS);

+

+    if (cinfo->dither_mode == JDITHER_FS) {

+      size_t arraysize = (size_t) ((cinfo->output_width + 2) *

+				   (3 * SIZEOF(FSERROR)));

+      /* Allocate Floyd-Steinberg workspace if we didn't already. */

+      if (cquantize->fserrors == NULL)

+	cquantize->fserrors = (FSERRPTR) (*cinfo->mem->alloc_large)

+	  ((j_common_ptr) cinfo, JPOOL_IMAGE, arraysize);

+      /* Initialize the propagated errors to zero. */

+      FMEMZERO((void FAR *) cquantize->fserrors, arraysize);

+      /* Make the error-limit table if we didn't already. */

+      if (cquantize->error_limiter == NULL)

+	init_error_limit(cinfo);

+      cquantize->on_odd_row = FALSE;

+    }

+

+  }

+  /* Zero the histogram or inverse color map, if necessary */

+  if (cquantize->needs_zeroed) {

+    for (i = 0; i < HIST_C0_ELEMS; i++) {

+      FMEMZERO((void FAR *) histogram[i],

+	       HIST_C1_ELEMS*HIST_C2_ELEMS * SIZEOF(histcell));

+    }

+    cquantize->needs_zeroed = FALSE;

+  }

+}

+

+

+/*

+ * Switch to a new external colormap between output passes.

+ */

+

+METHODDEF(void)

+new_color_map_2_quant (j_decompress_ptr cinfo)

+{

+  my_cquantize_ptr cquantize = (my_cquantize_ptr) cinfo->cquantize;

+

+  /* Reset the inverse color map */

+  cquantize->needs_zeroed = TRUE;

+}

+

+

+/*

+ * Module initialization routine for 2-pass color quantization.

+ */

+

+GLOBAL(void)

+jinit_2pass_quantizer (j_decompress_ptr cinfo)

+{

+  my_cquantize_ptr cquantize;

+  int i;

+

+  cquantize = (my_cquantize_ptr)

+    (*cinfo->mem->alloc_small) ((j_common_ptr) cinfo, JPOOL_IMAGE,

+				SIZEOF(my_cquantizer));

+  cinfo->cquantize = (struct jpeg_color_quantizer *) cquantize;

+  cquantize->pub.start_pass = start_pass_2_quant;

+  cquantize->pub.new_color_map = new_color_map_2_quant;

+  cquantize->fserrors = NULL;	/* flag optional arrays not allocated */

+  cquantize->error_limiter = NULL;

+

+  /* Make sure jdmaster didn't give me a case I can't handle */

+  if (cinfo->out_color_components != 3)

+    ERREXIT(cinfo, JERR_NOTIMPL);

+

+  /* Allocate the histogram/inverse colormap storage */

+  cquantize->histogram = (hist3d) (*cinfo->mem->alloc_small)

+    ((j_common_ptr) cinfo, JPOOL_IMAGE, HIST_C0_ELEMS * SIZEOF(hist2d));

+  for (i = 0; i < HIST_C0_ELEMS; i++) {

+    cquantize->histogram[i] = (hist2d) (*cinfo->mem->alloc_large)

+      ((j_common_ptr) cinfo, JPOOL_IMAGE,

+       HIST_C1_ELEMS*HIST_C2_ELEMS * SIZEOF(histcell));

+  }

+  cquantize->needs_zeroed = TRUE; /* histogram is garbage now */

+

+  /* Allocate storage for the completed colormap, if required.

+   * We do this now since it is FAR storage and may affect

+   * the memory manager's space calculations.

+   */

+  if (cinfo->enable_2pass_quant) {

+    /* Make sure color count is acceptable */

+    int desired = cinfo->desired_number_of_colors;

+    /* Lower bound on # of colors ... somewhat arbitrary as long as > 0 */

+    if (desired < 8)

+      ERREXIT1(cinfo, JERR_QUANT_FEW_COLORS, 8);

+    /* Make sure colormap indexes can be represented by JSAMPLEs */

+    if (desired > MAXNUMCOLORS)

+      ERREXIT1(cinfo, JERR_QUANT_MANY_COLORS, MAXNUMCOLORS);

+    cquantize->sv_colormap = (*cinfo->mem->alloc_sarray)

+      ((j_common_ptr) cinfo,JPOOL_IMAGE, (JDIMENSION) desired, (JDIMENSION) 3);

+    cquantize->desired = desired;

+  } else

+    cquantize->sv_colormap = NULL;

+

+  /* Only F-S dithering or no dithering is supported. */

+  /* If user asks for ordered dither, give him F-S. */

+  if (cinfo->dither_mode != JDITHER_NONE)

+    cinfo->dither_mode = JDITHER_FS;

+

+  /* Allocate Floyd-Steinberg workspace if necessary.

+   * This isn't really needed until pass 2, but again it is FAR storage.

+   * Although we will cope with a later change in dither_mode,

+   * we do not promise to honor max_memory_to_use if dither_mode changes.

+   */

+  if (cinfo->dither_mode == JDITHER_FS) {

+    cquantize->fserrors = (FSERRPTR) (*cinfo->mem->alloc_large)

+      ((j_common_ptr) cinfo, JPOOL_IMAGE,

+       (size_t) ((cinfo->output_width + 2) * (3 * SIZEOF(FSERROR))));

+    /* Might as well create the error-limiting table too. */

+    init_error_limit(cinfo);

+  }

+}

+

+#endif /* QUANT_2PASS_SUPPORTED */