The Independent JPEG Group's JPEG software v5
diff --git a/jquant2.c b/jquant2.c
index 4f3b191..7984f58 100644
--- a/jquant2.c
+++ b/jquant2.c
@@ -1,16 +1,25 @@
/*
* jquant2.c
*
- * Copyright (C) 1991, 1992, 1993, Thomas G. Lane.
+ * Copyright (C) 1991-1994, Thomas G. Lane.
* This file is part of the Independent JPEG Group's software.
* For conditions of distribution and use, see the accompanying README file.
*
* This file contains 2-pass color quantization (color mapping) routines.
- * These routines are invoked via the methods color_quant_prescan,
- * color_quant_doit, and color_quant_init/term.
+ * 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
@@ -23,13 +32,16 @@
* 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
+ * 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.
+ * 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
@@ -40,28 +52,57 @@
* used here have proved out well in experimental comparisons, but better ones
* may yet be found.
*
- * The most significant difference between this quantizer and others is that
- * this one is intended to operate in YCbCr colorspace, rather than RGB space
- * as is usually done. Actually we work in scaled YCbCr colorspace, where
- * Y distances are inflated by a factor of 2 relative to Cb or Cr distances.
- * The empirical evidence is that distances in this space correspond to
- * perceptual color differences more closely than do distances in RGB space;
- * and working in this space is inexpensive within a JPEG decompressor, since
- * the input data is already in YCbCr form. (We could transform to an even
- * more perceptually linear space such as Lab or Luv, but that is very slow
- * and doesn't yield much better results than scaled YCbCr.)
+ * 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 Y_SCALE 2 /* scale Y distances up by this much */
+#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 */
-#define MAXNUMCOLORS (MAXJSAMPLE+1) /* maximum size of colormap */
+/* 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.
*
- * For work in YCbCr space, it is useful to keep more precision for Y than
- * for Cb or Cr. We recommend keeping 6 bits for Y and 5 bits each for Cb/Cr.
+ * 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.
@@ -77,119 +118,165 @@
* Since the JPEG code is intended to run in small memory model on 80x86
* machines, we can't just allocate the histogram in one chunk. Instead
* of a true 3-D array, we use a row of pointers to 2-D arrays. Each
- * pointer corresponds to a Y value (typically 2^6 = 64 pointers) and
- * each 2-D array has 2^5^2 = 1024 or 2^6^2 = 4096 entries. Note that
+ * 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).
*/
-#ifndef HIST_Y_BITS /* so you can override from Makefile */
-#define HIST_Y_BITS 6 /* bits of precision in Y histogram */
-#endif
-#ifndef HIST_C_BITS /* so you can override from Makefile */
-#define HIST_C_BITS 5 /* bits of precision in Cb/Cr histogram */
-#endif
+#define MAXNUMCOLORS (MAXJSAMPLE+1) /* maximum size of colormap */
-#define HIST_Y_ELEMS (1<<HIST_Y_BITS) /* # of elements along histogram axes */
-#define HIST_C_ELEMS (1<<HIST_C_BITS)
-
-/* These are the amounts to shift an input value to get a histogram index.
- * For a combination 8/12 bit implementation, would need variables here...
+/* 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 */
-#define Y_SHIFT (BITS_IN_JSAMPLE-HIST_Y_BITS)
-#define C_SHIFT (BITS_IN_JSAMPLE-HIST_C_BITS)
+/* 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; MUST be an unsigned type */
+typedef UINT16 histcell; /* histogram cell; prefer an unsigned type */
typedef histcell FAR * histptr; /* for pointers to histogram cells */
-typedef histcell hist1d[HIST_C_ELEMS]; /* typedefs for the array */
-typedef hist1d FAR * hist2d; /* type for the Y-level pointers */
+typedef 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 */
-static hist3d histogram; /* pointer to the histogram */
+
+/* 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 */
+
+ /* Variables for accumulating image statistics */
+ hist3d histogram; /* pointer to the 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 color_quant_init.
- * Note: workspace is probably not useful for this routine, but it is passed
- * anyway to allow some code sharing within the pipeline controller.
+ * 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
-color_quant_prescan (decompress_info_ptr cinfo, int num_rows,
- JSAMPIMAGE image_data, JSAMPARRAY workspace)
+prescan_quantize (j_decompress_ptr cinfo, JSAMPARRAY input_buf,
+ JSAMPARRAY output_buf, int num_rows)
{
- register JSAMPROW ptr0, ptr1, ptr2;
+ my_cquantize_ptr cquantize = (my_cquantize_ptr) cinfo->cquantize;
+ register JSAMPROW ptr;
register histptr histp;
- register int c0, c1, c2;
+ register hist3d histogram = cquantize->histogram;
int row;
- long col;
- long width = cinfo->image_width;
+ JDIMENSION col;
+ JDIMENSION width = cinfo->output_width;
for (row = 0; row < num_rows; row++) {
- ptr0 = image_data[0][row];
- ptr1 = image_data[1][row];
- ptr2 = image_data[2][row];
+ ptr = input_buf[row];
for (col = width; col > 0; col--) {
/* get pixel value and index into the histogram */
- c0 = GETJSAMPLE(*ptr0++) >> Y_SHIFT;
- c1 = GETJSAMPLE(*ptr1++) >> C_SHIFT;
- c2 = GETJSAMPLE(*ptr2++) >> C_SHIFT;
- histp = & histogram[c0][c1][c2];
+ 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. */
- /* We assume unsigned representation here! */
- if (++(*histp) == 0)
+ if (++(*histp) <= 0)
(*histp)--;
+ ptr += 3;
}
}
}
/*
- * Now we have the really interesting routines: selection of a colormap
+ * 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 number of nonzero histogram cells within this box */
- long colorcount;
- } box;
+ /* 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;
-static boxptr boxlist; /* array with room for desired # of boxes */
-static int numboxes; /* number of boxes currently in boxlist */
-
-static JSAMPARRAY my_colormap; /* the finished colormap (in YCbCr space) */
-
LOCAL boxptr
-find_biggest_color_pop (void)
+find_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 max = 0;
+ register long maxc = 0;
boxptr which = NULL;
for (i = 0, boxp = boxlist; i < numboxes; i++, boxp++) {
- if (boxp->colorcount > max) {
- if (boxp->c0max > boxp->c0min || boxp->c1max > boxp->c1min ||
- boxp->c2max > boxp->c2min) {
- which = boxp;
- max = boxp->colorcount;
- }
+ if (boxp->colorcount > maxc && boxp->volume > 0) {
+ which = boxp;
+ maxc = boxp->colorcount;
}
}
return which;
@@ -197,33 +284,19 @@
LOCAL boxptr
-find_biggest_volume (void)
+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 max = 0;
- register INT32 norm, c0,c1,c2;
+ register INT32 maxv = 0;
boxptr which = NULL;
- /* We use 2-norm rather than real volume here.
- * Some care is needed since the differences are expressed in
- * histogram-cell units; if HIST_Y_BITS != HIST_C_BITS, we have to
- * adjust the scaling to get the proper scaled-YCbCr-space distance.
- * This code won't work right if HIST_Y_BITS < HIST_C_BITS,
- * but that shouldn't ever be true.
- * Note norm > 0 iff box is splittable, so need not check separately.
- */
-
for (i = 0, boxp = boxlist; i < numboxes; i++, boxp++) {
- c0 = (boxp->c0max - boxp->c0min) * Y_SCALE;
- c1 = (boxp->c1max - boxp->c1min) << (HIST_Y_BITS-HIST_C_BITS);
- c2 = (boxp->c2max - boxp->c2min) << (HIST_Y_BITS-HIST_C_BITS);
- norm = c0*c0 + c1*c1 + c2*c2;
- if (norm > max) {
+ if (boxp->volume > maxv) {
which = boxp;
- max = norm;
+ maxv = boxp->volume;
}
}
return which;
@@ -231,13 +304,16 @@
LOCAL void
-update_box (boxptr boxp)
+update_box (j_decompress_ptr cinfo, boxptr boxp)
/* Shrink the min/max bounds of a box to enclose only nonzero elements, */
-/* and recompute its population */
+/* 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;
@@ -292,7 +368,7 @@
for (c2 = c2min; c2 <= c2max; c2++)
for (c0 = c0min; c0 <= c0max; c0++) {
histp = & histogram[c0][c1min][c2];
- for (c1 = c1min; c1 <= c1max; c1++, histp += HIST_C_ELEMS)
+ for (c1 = c1min; c1 <= c1max; c1++, histp += HIST_C2_ELEMS)
if (*histp != 0) {
boxp->c2min = c2min = c2;
goto have_c2min;
@@ -303,13 +379,26 @@
for (c2 = c2max; c2 >= c2min; c2--)
for (c0 = c0min; c0 <= c0max; c0++) {
histp = & histogram[c0][c1min][c2];
- for (c1 = c1min; c1 <= c1max; c1++, histp += HIST_C_ELEMS)
+ 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;
@@ -325,8 +414,9 @@
}
-LOCAL void
-median_cut (int desired_colors)
+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;
@@ -334,12 +424,13 @@
register boxptr b1,b2;
while (numboxes < desired_colors) {
- /* Select box to split */
- /* Current algorithm: by population for first half, then by volume */
+ /* Select box to split.
+ * Current algorithm: by population for first half, then by volume.
+ */
if (numboxes*2 <= desired_colors) {
- b1 = find_biggest_color_pop();
+ b1 = find_biggest_color_pop(boxlist, numboxes);
} else {
- b1 = find_biggest_volume();
+ b1 = find_biggest_volume(boxlist, numboxes);
}
if (b1 == NULL) /* no splittable boxes left! */
break;
@@ -349,14 +440,23 @@
b2->c0min = b1->c0min; b2->c1min = b1->c1min; b2->c2min = b1->c2min;
/* Choose which axis to split the box on.
* Current algorithm: longest scaled axis.
- * See notes in find_biggest_volume about scaling...
+ * See notes in update_box about scaling distances.
*/
- c0 = (b1->c0max - b1->c0min) * Y_SCALE;
- c1 = (b1->c1max - b1->c1min) << (HIST_Y_BITS-HIST_C_BITS);
- c2 = (b1->c2max - b1->c2min) << (HIST_Y_BITS-HIST_C_BITS);
- cmax = c0; n = 0;
- if (c1 > cmax) { cmax = c1; n = 1; }
+ 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,
@@ -381,19 +481,22 @@
break;
}
/* Update stats for boxes */
- update_box(b1);
- update_box(b2);
+ update_box(cinfo, b1);
+ update_box(cinfo, b2);
numboxes++;
}
+ return numboxes;
}
LOCAL void
-compute_color (boxptr boxp, int icolor)
-/* Compute representative color for a box, put it in my_colormap[icolor] */
+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;
@@ -413,73 +516,48 @@
for (c2 = c2min; c2 <= c2max; c2++) {
if ((count = *histp++) != 0) {
total += count;
- c0total += ((c0 << Y_SHIFT) + ((1<<Y_SHIFT)>>1)) * count;
- c1total += ((c1 << C_SHIFT) + ((1<<C_SHIFT)>>1)) * count;
- c2total += ((c2 << C_SHIFT) + ((1<<C_SHIFT)>>1)) * count;
+ 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;
}
}
}
- my_colormap[0][icolor] = (JSAMPLE) ((c0total + (total>>1)) / total);
- my_colormap[1][icolor] = (JSAMPLE) ((c1total + (total>>1)) / total);
- my_colormap[2][icolor] = (JSAMPLE) ((c2total + (total>>1)) / total);
+ 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
-remap_colormap (decompress_info_ptr cinfo)
-/* Remap the internal colormap to the output colorspace */
-{
- /* This requires a little trickery since color_convert expects to
- * deal with 3-D arrays (a 2-D sample array for each component).
- * We must promote the colormaps into one-row 3-D arrays.
- */
- short ci;
- JSAMPARRAY input_hack[3];
- JSAMPARRAY output_hack[10]; /* assume no more than 10 output components */
-
- for (ci = 0; ci < 3; ci++)
- input_hack[ci] = &(my_colormap[ci]);
- for (ci = 0; ci < cinfo->color_out_comps; ci++)
- output_hack[ci] = &(cinfo->colormap[ci]);
-
- (*cinfo->methods->color_convert) (cinfo, 1,
- (long) cinfo->actual_number_of_colors,
- input_hack, output_hack);
-}
-
-
-LOCAL void
-select_colors (decompress_info_ptr cinfo)
+select_colors (j_decompress_ptr cinfo)
/* Master routine for color selection */
{
+ boxptr boxlist;
+ int numboxes;
int desired = cinfo->desired_number_of_colors;
int i;
/* Allocate workspace for box list */
- boxlist = (boxptr) (*cinfo->emethods->alloc_small) (desired * SIZEOF(box));
+ boxlist = (boxptr) (*cinfo->mem->alloc_small)
+ ((j_common_ptr) cinfo, JPOOL_IMAGE, desired * SIZEOF(box));
/* Initialize one box containing whole space */
numboxes = 1;
boxlist[0].c0min = 0;
- boxlist[0].c0max = MAXJSAMPLE >> Y_SHIFT;
+ boxlist[0].c0max = MAXJSAMPLE >> C0_SHIFT;
boxlist[0].c1min = 0;
- boxlist[0].c1max = MAXJSAMPLE >> C_SHIFT;
+ boxlist[0].c1max = MAXJSAMPLE >> C1_SHIFT;
boxlist[0].c2min = 0;
- boxlist[0].c2max = MAXJSAMPLE >> C_SHIFT;
+ boxlist[0].c2max = MAXJSAMPLE >> C2_SHIFT;
/* Shrink it to actually-used volume and set its statistics */
- update_box(& boxlist[0]);
+ update_box(cinfo, & boxlist[0]);
/* Perform median-cut to produce final box list */
- median_cut(desired);
- /* Compute the representative color for each box, fill my_colormap[] */
+ numboxes = median_cut(cinfo, boxlist, numboxes, desired);
+ /* Compute the representative color for each box, fill colormap */
for (i = 0; i < numboxes; i++)
- compute_color(& boxlist[i], i);
+ compute_color(cinfo, & boxlist[i], i);
cinfo->actual_number_of_colors = numboxes;
- /* Produce an output colormap in the desired output colorspace */
- remap_colormap(cinfo);
- TRACEMS1(cinfo->emethods, 1, "Selected %d colors for quantization",
- numboxes);
- /* Done with the box list */
- (*cinfo->emethods->free_small) ((void *) boxlist);
+ TRACEMS1(cinfo, 1, JTRC_QUANT_SELECTED, numboxes);
}
@@ -511,17 +589,13 @@
* cell (because the inner loop has to be over cells, not colormap entries).
* The work array elements have to be INT32s, so the work array would need
* 256Kb at our recommended precision. This is not feasible in DOS machines.
- * Another disadvantage of the brute force approach is that it computes
- * distances to every cell of the cubical histogram. When working with YCbCr
- * input, only about a quarter of the cube represents realizable colors, so
- * many of the cells will never be used and filling them is wasted effort.
*
* To get around these problems, we apply Thomas' method to compute the
* nearest colors for only the cells within a small subbox of the histogram.
* The work array need be only as big as the subbox, so the memory usage
- * problem is solved. A subbox is processed only when some cell in it is
- * referenced by the pass2 routines, so we will never bother with cells far
- * outside the realizable color volume. An additional advantage of this
+ * 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,
@@ -541,18 +615,18 @@
*/
-#ifndef BOX_Y_LOG /* so you can override from Makefile */
-#define BOX_Y_LOG (HIST_Y_BITS-3) /* log2(hist cells in update box, Y axis) */
-#endif
-#ifndef BOX_C_LOG /* so you can override from Makefile */
-#define BOX_C_LOG (HIST_C_BITS-3) /* log2(hist cells in update box, C axes) */
-#endif
+/* 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_Y_ELEMS (1<<BOX_Y_LOG) /* # of hist cells in update box */
-#define BOX_C_ELEMS (1<<BOX_C_LOG)
+#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_Y_SHIFT (Y_SHIFT + BOX_Y_LOG)
-#define BOX_C_SHIFT (C_SHIFT + BOX_C_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)
/*
@@ -564,7 +638,7 @@
*/
LOCAL int
-find_nearby_colors (decompress_info_ptr cinfo, int minc0, int minc1, int minc2,
+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
@@ -588,11 +662,11 @@
* Note that since ">>" rounds down, the "center" values may be closer to
* min than to max; hence comparisons to them must be "<=", not "<".
*/
- maxc0 = minc0 + ((1 << BOX_Y_SHIFT) - (1 << Y_SHIFT));
+ maxc0 = minc0 + ((1 << BOX_C0_SHIFT) - (1 << C0_SHIFT));
centerc0 = (minc0 + maxc0) >> 1;
- maxc1 = minc1 + ((1 << BOX_C_SHIFT) - (1 << C_SHIFT));
+ maxc1 = minc1 + ((1 << BOX_C1_SHIFT) - (1 << C1_SHIFT));
centerc1 = (minc1 + maxc1) >> 1;
- maxc2 = minc2 + ((1 << BOX_C_SHIFT) - (1 << C_SHIFT));
+ maxc2 = minc2 + ((1 << BOX_C2_SHIFT) - (1 << C2_SHIFT));
centerc2 = (minc2 + maxc2) >> 1;
/* For each color in colormap, find:
@@ -602,75 +676,74 @@
* Both of these can be found by considering only the corners of the box.
* We save the minimum distance for each color in mindist[];
* only the smallest maximum distance is of interest.
- * Note we have to scale Y to get correct distance in scaled space.
*/
minmaxdist = 0x7FFFFFFFL;
for (i = 0; i < numcolors; i++) {
/* We compute the squared-c0-distance term, then add in the other two. */
- x = GETJSAMPLE(my_colormap[0][i]);
+ x = GETJSAMPLE(cinfo->colormap[0][i]);
if (x < minc0) {
- tdist = (x - minc0) * Y_SCALE;
+ tdist = (x - minc0) * C0_SCALE;
min_dist = tdist*tdist;
- tdist = (x - maxc0) * Y_SCALE;
+ tdist = (x - maxc0) * C0_SCALE;
max_dist = tdist*tdist;
} else if (x > maxc0) {
- tdist = (x - maxc0) * Y_SCALE;
+ tdist = (x - maxc0) * C0_SCALE;
min_dist = tdist*tdist;
- tdist = (x - minc0) * Y_SCALE;
+ 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) * Y_SCALE;
+ tdist = (x - maxc0) * C0_SCALE;
max_dist = tdist*tdist;
} else {
- tdist = (x - minc0) * Y_SCALE;
+ tdist = (x - minc0) * C0_SCALE;
max_dist = tdist*tdist;
}
}
- x = GETJSAMPLE(my_colormap[1][i]);
+ x = GETJSAMPLE(cinfo->colormap[1][i]);
if (x < minc1) {
- tdist = x - minc1;
+ tdist = (x - minc1) * C1_SCALE;
min_dist += tdist*tdist;
- tdist = x - maxc1;
+ tdist = (x - maxc1) * C1_SCALE;
max_dist += tdist*tdist;
} else if (x > maxc1) {
- tdist = x - maxc1;
+ tdist = (x - maxc1) * C1_SCALE;
min_dist += tdist*tdist;
- tdist = x - minc1;
+ 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;
+ tdist = (x - maxc1) * C1_SCALE;
max_dist += tdist*tdist;
} else {
- tdist = x - minc1;
+ tdist = (x - minc1) * C1_SCALE;
max_dist += tdist*tdist;
}
}
- x = GETJSAMPLE(my_colormap[2][i]);
+ x = GETJSAMPLE(cinfo->colormap[2][i]);
if (x < minc2) {
- tdist = x - minc2;
+ tdist = (x - minc2) * C2_SCALE;
min_dist += tdist*tdist;
- tdist = x - maxc2;
+ tdist = (x - maxc2) * C2_SCALE;
max_dist += tdist*tdist;
} else if (x > maxc2) {
- tdist = x - maxc2;
+ tdist = (x - maxc2) * C2_SCALE;
min_dist += tdist*tdist;
- tdist = x - minc2;
+ 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;
+ tdist = (x - maxc2) * C2_SCALE;
max_dist += tdist*tdist;
} else {
- tdist = x - minc2;
+ tdist = (x - minc2) * C2_SCALE;
max_dist += tdist*tdist;
}
}
@@ -694,7 +767,7 @@
LOCAL void
-find_best_colors (decompress_info_ptr cinfo, int minc0, int minc1, int minc2,
+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.
@@ -713,72 +786,74 @@
register INT32 xx2;
INT32 inc0, inc1, inc2; /* initial values for increments */
/* This array holds the distance to the nearest-so-far color for each cell */
- INT32 bestdist[BOX_Y_ELEMS * BOX_C_ELEMS * BOX_C_ELEMS];
+ 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_Y_ELEMS*BOX_C_ELEMS*BOX_C_ELEMS-1; i >= 0; i--)
+ 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.
- * Note we have to scale Y to get correct distance in scaled space.
*/
/* Nominal steps between cell centers ("x" in Thomas article) */
-#define STEP_Y ((1 << Y_SHIFT) * Y_SCALE)
-#define STEP_C (1 << C_SHIFT)
+#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 - (int) GETJSAMPLE(my_colormap[0][icolor])) * Y_SCALE;
+ inc0 = (minc0 - GETJSAMPLE(cinfo->colormap[0][icolor])) * C0_SCALE;
dist0 = inc0*inc0;
- inc1 = minc1 - (int) GETJSAMPLE(my_colormap[1][icolor]);
+ inc1 = (minc1 - GETJSAMPLE(cinfo->colormap[1][icolor])) * C1_SCALE;
dist0 += inc1*inc1;
- inc2 = minc2 - (int) GETJSAMPLE(my_colormap[2][icolor]);
+ inc2 = (minc2 - GETJSAMPLE(cinfo->colormap[2][icolor])) * C2_SCALE;
dist0 += inc2*inc2;
/* Form the initial difference increments */
- inc0 = inc0 * (2 * STEP_Y) + STEP_Y * STEP_Y;
- inc1 = inc1 * (2 * STEP_C) + STEP_C * STEP_C;
- inc2 = inc2 * (2 * STEP_C) + STEP_C * STEP_C;
+ 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_Y_ELEMS-1; ic0 >= 0; ic0--) {
+ for (ic0 = BOX_C0_ELEMS-1; ic0 >= 0; ic0--) {
dist1 = dist0;
xx1 = inc1;
- for (ic1 = BOX_C_ELEMS-1; ic1 >= 0; ic1--) {
+ for (ic1 = BOX_C1_ELEMS-1; ic1 >= 0; ic1--) {
dist2 = dist1;
xx2 = inc2;
- for (ic2 = BOX_C_ELEMS-1; ic2 >= 0; ic2--) {
+ for (ic2 = BOX_C2_ELEMS-1; ic2 >= 0; ic2--) {
if (dist2 < *bptr) {
*bptr = dist2;
*cptr = (JSAMPLE) icolor;
}
dist2 += xx2;
- xx2 += 2 * STEP_C * STEP_C;
+ xx2 += 2 * STEP_C2 * STEP_C2;
bptr++;
cptr++;
}
dist1 += xx1;
- xx1 += 2 * STEP_C * STEP_C;
+ xx1 += 2 * STEP_C1 * STEP_C1;
}
dist0 += xx0;
- xx0 += 2 * STEP_Y * STEP_Y;
+ xx0 += 2 * STEP_C0 * STEP_C0;
}
}
}
LOCAL void
-fill_inverse_cmap (decompress_info_ptr cinfo, int c0, int c1, int c2)
+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 */
@@ -787,20 +862,20 @@
JSAMPLE colorlist[MAXNUMCOLORS];
int numcolors; /* number of candidate colors */
/* This array holds the actually closest colormap index for each cell. */
- JSAMPLE bestcolor[BOX_Y_ELEMS * BOX_C_ELEMS * BOX_C_ELEMS];
+ JSAMPLE bestcolor[BOX_C0_ELEMS * BOX_C1_ELEMS * BOX_C2_ELEMS];
/* Convert cell coordinates to update box ID */
- c0 >>= BOX_Y_LOG;
- c1 >>= BOX_C_LOG;
- c2 >>= BOX_C_LOG;
+ 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_Y_SHIFT) + ((1 << Y_SHIFT) >> 1);
- minc1 = (c1 << BOX_C_SHIFT) + ((1 << C_SHIFT) >> 1);
- minc2 = (c2 << BOX_C_SHIFT) + ((1 << C_SHIFT) >> 1);
+ 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.
@@ -812,14 +887,14 @@
bestcolor);
/* Save the best color numbers (plus 1) in the main cache array */
- c0 <<= BOX_Y_LOG; /* convert ID back to base cell indexes */
- c1 <<= BOX_C_LOG;
- c2 <<= BOX_C_LOG;
+ 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_Y_ELEMS; ic0++) {
- for (ic1 = 0; ic1 < BOX_C_ELEMS; ic1++) {
+ 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_C_ELEMS; ic2++) {
+ for (ic2 = 0; ic2 < BOX_C2_ELEMS; ic2++) {
*cachep++ = (histcell) (GETJSAMPLE(*cptr++) + 1);
}
}
@@ -828,37 +903,31 @@
/*
- * These routines perform second-pass scanning of the image: map each pixel to
- * the proper colormap index, and output the indexes to the output file.
- *
- * output_workspace is a one-component array of pixel dimensions at least
- * as large as the input image strip; it can be used to hold the converted
- * pixels' colormap indexes.
+ * Map some rows of pixels to the output colormapped representation.
*/
METHODDEF void
-pass2_nodither (decompress_info_ptr cinfo, int num_rows,
- JSAMPIMAGE image_data, JSAMPARRAY output_workspace)
+pass2_no_dither (j_decompress_ptr cinfo,
+ JSAMPARRAY input_buf, JSAMPARRAY output_buf, int num_rows)
/* This version performs no dithering */
{
- register JSAMPROW ptr0, ptr1, ptr2, outptr;
+ 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;
- long col;
- long width = cinfo->image_width;
+ JDIMENSION col;
+ JDIMENSION width = cinfo->output_width;
- /* Convert data to colormap indexes, which we save in output_workspace */
for (row = 0; row < num_rows; row++) {
- ptr0 = image_data[0][row];
- ptr1 = image_data[1][row];
- ptr2 = image_data[2][row];
- outptr = output_workspace[row];
+ inptr = input_buf[row];
+ outptr = output_buf[row];
for (col = width; col > 0; col--) {
/* get pixel value and index into the cache */
- c0 = GETJSAMPLE(*ptr0++) >> Y_SHIFT;
- c1 = GETJSAMPLE(*ptr1++) >> C_SHIFT;
- c2 = GETJSAMPLE(*ptr2++) >> C_SHIFT;
+ 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 */
@@ -868,94 +937,52 @@
*outptr++ = (JSAMPLE) (*cachep - 1);
}
}
- /* Emit converted rows to the output file */
- (*cinfo->methods->put_pixel_rows) (cinfo, num_rows, &output_workspace);
}
-/* Declarations for Floyd-Steinberg dithering.
- *
- * Errors are accumulated into the 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_medium.
- */
-
-#ifdef EIGHT_BIT_SAMPLES
-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!) */
-
-static FSERRPTR fserrors; /* accumulated errors */
-static boolean on_odd_row; /* flag to remember which row we are on */
-
-
METHODDEF void
-pass2_dither (decompress_info_ptr cinfo, int num_rows,
- JSAMPIMAGE image_data, JSAMPARRAY output_workspace)
+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 ptr0, ptr1, ptr2; /* => current input pixel */
+ 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 errorptr */
+ int dir3; /* 3*dir, for advancing inptr & errorptr */
int row;
- long col;
- long width = cinfo->image_width;
+ JDIMENSION col;
+ JDIMENSION width = cinfo->output_width;
JSAMPLE *range_limit = cinfo->sample_range_limit;
- JSAMPROW colormap0 = my_colormap[0];
- JSAMPROW colormap1 = my_colormap[1];
- JSAMPROW colormap2 = my_colormap[2];
+ int *error_limit = cquantize->error_limiter;
+ JSAMPROW colormap0 = cinfo->colormap[0];
+ JSAMPROW colormap1 = cinfo->colormap[1];
+ JSAMPROW colormap2 = cinfo->colormap[2];
SHIFT_TEMPS
- /* Convert data to colormap indexes, which we save in output_workspace */
for (row = 0; row < num_rows; row++) {
- ptr0 = image_data[0][row];
- ptr1 = image_data[1][row];
- ptr2 = image_data[2][row];
- outptr = output_workspace[row];
- if (on_odd_row) {
+ inptr = input_buf[row];
+ outptr = output_buf[row];
+ if (cquantize->on_odd_row) {
/* work right to left in this row */
- ptr0 += width - 1; /* so point to rightmost pixel */
- ptr1 += width - 1;
- ptr2 += width - 1;
- outptr += width - 1;
+ inptr += (width-1) * 3; /* so point to rightmost pixel */
+ outptr += width-1;
dir = -1;
dir3 = -3;
- errorptr = fserrors + (width+1)*3; /* point to entry after last column */
- on_odd_row = FALSE; /* flip for next time */
+ 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 = fserrors; /* point to entry before first real column */
- on_odd_row = TRUE; /* flip for next time */
+ 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;
@@ -975,22 +1002,28 @@
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);
- /* Form pixel value + error, and range-limit to 0..MAXJSAMPLE.
- * The maximum error is +- MAXJSAMPLE; this sets the required size
- * of the range_limit array.
+ /* Limit the error using transfer function set by init_error_limit.
+ * See comments with init_error_limit for rationale.
*/
- cur0 += GETJSAMPLE(*ptr0);
- cur1 += GETJSAMPLE(*ptr1);
- cur2 += GETJSAMPLE(*ptr2);
+ 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 >> Y_SHIFT][cur1 >> C_SHIFT][cur2 >> C_SHIFT];
+ 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>>Y_SHIFT, cur1>>C_SHIFT, cur2>>C_SHIFT);
+ 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;
@@ -1034,9 +1067,7 @@
* 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.
*/
- ptr0 += dir; /* Advance pixel pointers to next column */
- ptr1 += dir;
- ptr2 += dir;
+ inptr += dir3; /* Advance pixel pointers to next column */
outptr += dir;
errorptr += dir3; /* advance errorptr to current column */
}
@@ -1048,149 +1079,174 @@
errorptr[1] = (FSERROR) bpreverr1;
errorptr[2] = (FSERROR) bpreverr2;
}
- /* Emit converted rows to the output file */
- (*cinfo->methods->put_pixel_rows) (cinfo, num_rows, &output_workspace);
}
/*
- * Initialize for two-pass color quantization.
+ * 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.
*/
-METHODDEF void
-color_quant_init (decompress_info_ptr cinfo)
+LOCAL void
+init_error_limit (j_decompress_ptr cinfo)
+/* Allocate and fill in the error_limiter table */
{
- int i;
+ my_cquantize_ptr cquantize = (my_cquantize_ptr) cinfo->cquantize;
+ int * table;
+ int in, out;
- /* Lower bound on # of colors ... somewhat arbitrary as long as > 0 */
- if (cinfo->desired_number_of_colors < 8)
- ERREXIT(cinfo->emethods, "Cannot request less than 8 quantized colors");
- /* Make sure colormap indexes can be represented by JSAMPLEs */
- if (cinfo->desired_number_of_colors > MAXNUMCOLORS)
- ERREXIT1(cinfo->emethods, "Cannot request more than %d quantized colors",
- MAXNUMCOLORS);
+ 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;
- /* Allocate and zero the histogram */
- histogram = (hist3d) (*cinfo->emethods->alloc_small)
- (HIST_Y_ELEMS * SIZEOF(hist2d));
- for (i = 0; i < HIST_Y_ELEMS; i++) {
- histogram[i] = (hist2d) (*cinfo->emethods->alloc_medium)
- (HIST_C_ELEMS*HIST_C_ELEMS * SIZEOF(histcell));
- jzero_far((void FAR *) histogram[i],
- HIST_C_ELEMS*HIST_C_ELEMS * SIZEOF(histcell));
+#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;
}
-
- /* Allocate storage for the internal and external colormaps. */
- /* We do this now since it is FAR storage and may affect the memory */
- /* manager's space calculations. */
- my_colormap = (*cinfo->emethods->alloc_small_sarray)
- ((long) cinfo->desired_number_of_colors,
- (long) 3);
- cinfo->colormap = (*cinfo->emethods->alloc_small_sarray)
- ((long) cinfo->desired_number_of_colors,
- (long) cinfo->color_out_comps);
-
- /* Allocate Floyd-Steinberg workspace if necessary */
- /* This isn't needed until pass 2, but again it is FAR storage. */
- if (cinfo->use_dithering) {
- size_t arraysize = (size_t) ((cinfo->image_width + 2L) *
- (3 * SIZEOF(FSERROR)));
-
- fserrors = (FSERRPTR) (*cinfo->emethods->alloc_medium) (arraysize);
- /* Initialize the propagated errors to zero. */
- jzero_far((void FAR *) fserrors, arraysize);
- on_odd_row = FALSE;
+ /* 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;
}
-
- /* Indicate number of passes needed, excluding the prescan pass. */
- cinfo->total_passes++; /* I always use one pass */
+ /* Clamp the rest to final out value (which is (MAXJSAMPLE+1)/8) */
+ for (; in <= MAXJSAMPLE; in++) {
+ table[in] = out; table[-in] = -out;
+ }
+#undef STEPSIZE
}
/*
- * Perform two-pass quantization: rescan the image data and output the
- * converted data via put_color_map and put_pixel_rows.
- * The source_method is a routine that can scan the image data; it can
- * be called as many times as desired. The processing routine called by
- * source_method has the same interface as color_quantize does in the
- * one-pass case, except it must call put_pixel_rows itself. (This allows
- * me to use multiple passes in which earlier passes don't output anything.)
+ * Finish up at the end of each pass.
*/
METHODDEF void
-color_quant_doit (decompress_info_ptr cinfo, quantize_caller_ptr source_method)
+finish_pass1 (j_decompress_ptr cinfo)
{
- int i;
-
- /* Select the representative colors */
+ /* Select the representative colors and fill in cinfo->colormap */
select_colors(cinfo);
- /* Pass the external colormap to the output module. */
- /* NB: the output module may continue to use the colormap until shutdown. */
- (*cinfo->methods->put_color_map) (cinfo, cinfo->actual_number_of_colors,
- cinfo->colormap);
- /* Re-zero the histogram so pass 2 can use it as nearest-color cache */
- for (i = 0; i < HIST_Y_ELEMS; i++) {
- jzero_far((void FAR *) histogram[i],
- HIST_C_ELEMS*HIST_C_ELEMS * SIZEOF(histcell));
+}
+
+
+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;
+
+ if (is_pre_scan) {
+ /* Set up method pointers */
+ cquantize->pub.color_quantize = prescan_quantize;
+ cquantize->pub.finish_pass = finish_pass1;
+ } 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;
}
- /* Perform pass 2 */
- if (cinfo->use_dithering)
- (*source_method) (cinfo, pass2_dither);
- else
- (*source_method) (cinfo, pass2_nodither);
+ /* Zero the histogram or inverse color map */
+ for (i = 0; i < HIST_C0_ELEMS; i++) {
+ jzero_far((void FAR *) histogram[i],
+ HIST_C1_ELEMS*HIST_C2_ELEMS * SIZEOF(histcell));
+ }
}
/*
- * Finish up at the end of the file.
- */
-
-METHODDEF void
-color_quant_term (decompress_info_ptr cinfo)
-{
- /* no work (we let free_all release the histogram/cache and colormaps) */
- /* Note that we *mustn't* free the external colormap before free_all, */
- /* since output module may use it! */
-}
-
-
-/*
- * Map some rows of pixels to the output colormapped representation.
- * Not used in two-pass case.
- */
-
-METHODDEF void
-color_quantize (decompress_info_ptr cinfo, int num_rows,
- JSAMPIMAGE input_data, JSAMPARRAY output_data)
-{
- ERREXIT(cinfo->emethods, "Should not get here!");
-}
-
-
-/*
- * The method selection routine for 2-pass color quantization.
+ * Module initialization routine for 2-pass color quantization.
*/
GLOBAL void
-jsel2quantize (decompress_info_ptr cinfo)
+jinit_2pass_quantizer (j_decompress_ptr cinfo)
{
- if (cinfo->two_pass_quantize) {
- /* Make sure jdmaster didn't give me a case I can't handle */
- if (cinfo->num_components != 3 || cinfo->jpeg_color_space != CS_YCbCr)
- ERREXIT(cinfo->emethods, "2-pass quantization only handles YCbCr input");
- cinfo->methods->color_quant_init = color_quant_init;
- cinfo->methods->color_quant_prescan = color_quant_prescan;
- cinfo->methods->color_quant_doit = color_quant_doit;
- cinfo->methods->color_quant_term = color_quant_term;
- cinfo->methods->color_quantize = color_quantize;
- /* Quantized grayscale output is normally done by jquant1.c (which will do
- * a much better job of it). But if the program is configured with only
- * 2-pass quantization, then I have to do the job. In this situation,
- * jseldcolor's clearing of the Cb/Cr component_needed flags is incorrect,
- * because I will look at those components before conversion.
- */
- cinfo->cur_comp_info[1]->component_needed = TRUE;
- cinfo->cur_comp_info[2]->component_needed = TRUE;
+ 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;
+
+ /* Make sure jdmaster didn't give me a case I can't handle */
+ if (cinfo->out_color_components != 3)
+ ERREXIT(cinfo, JERR_NOTIMPL);
+
+ /* 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;
+
+ /* Make sure color count is acceptable */
+ i = (cinfo->colormap != NULL) ? cinfo->actual_number_of_colors
+ : cinfo->desired_number_of_colors;
+ /* Lower bound on # of colors ... somewhat arbitrary as long as > 0 */
+ if (i < 8)
+ ERREXIT1(cinfo, JERR_QUANT_FEW_COLORS, 8);
+ /* Make sure colormap indexes can be represented by JSAMPLEs */
+ if (i > MAXNUMCOLORS)
+ ERREXIT1(cinfo, JERR_QUANT_MANY_COLORS, MAXNUMCOLORS);
+
+ /* 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));
+ }
+
+ /* Allocate storage for the completed colormap,
+ * unless it has been supplied by the application.
+ * We do this now since it is FAR storage and may affect
+ * the memory manager's space calculations.
+ */
+ if (cinfo->colormap == NULL) {
+ cinfo->colormap = (*cinfo->mem->alloc_sarray)
+ ((j_common_ptr) cinfo, JPOOL_IMAGE,
+ (JDIMENSION) cinfo->desired_number_of_colors, (JDIMENSION) 3);
+ }
+
+ /* Allocate Floyd-Steinberg workspace if necessary. */
+ /* This isn't needed until pass 2, but again it is FAR storage. */
+ if (cinfo->dither_mode == JDITHER_FS) {
+ size_t arraysize = (size_t) ((cinfo->output_width + 2) *
+ (3 * SIZEOF(FSERROR)));
+
+ cquantize->fserrors = (FSERRPTR) (*cinfo->mem->alloc_large)
+ ((j_common_ptr) cinfo, JPOOL_IMAGE, arraysize);
+ /* Initialize the propagated errors to zero. */
+ jzero_far((void FAR *) cquantize->fserrors, arraysize);
+ cquantize->on_odd_row = FALSE;
+ init_error_limit(cinfo);
}
}