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1 /////////////////////////////////////////////////////////////////////////////
2 // Name: quantize.cpp
3 // Purpose: wxQuantize implementation
4 // Author: Julian Smart
5 // Modified by:
6 // Created: 22/6/2000
7 // RCS-ID: $Id$
8 // Copyright: (c) Thomas G. Lane, Vaclav Slavik, Julian Smart
9 // Licence: wxWindows licence + JPEG library licence
10 /////////////////////////////////////////////////////////////////////////////
11
12 /*
13 * jquant2.c
14 *
15 * Copyright (C) 1991-1996, Thomas G. Lane.
16 * This file is part of the Independent JPEG Group's software.
17 * For conditions of distribution and use, see the accompanying README file.
18 *
19 * This file contains 2-pass color quantization (color mapping) routines.
20 * These routines provide selection of a custom color map for an image,
21 * followed by mapping of the image to that color map, with optional
22 * Floyd-Steinberg dithering.
23 * It is also possible to use just the second pass to map to an arbitrary
24 * externally-given color map.
25 *
26 * Note: ordered dithering is not supported, since there isn't any fast
27 * way to compute intercolor distances; it's unclear that ordered dither's
28 * fundamental assumptions even hold with an irregularly spaced color map.
29 */
30
31 /* modified by Vaclav Slavik for use as jpeglib-independent module */
32
33 #if defined(__GNUG__) && !defined(NO_GCC_PRAGMA)
34 #pragma implementation "quantize.h"
35 #endif
36
37 // For compilers that support precompilation, includes "wx/wx.h".
38 #include "wx/wxprec.h"
39
40 #ifdef __BORLANDC__
41 #pragma hdrstop
42 #endif
43
44 #ifndef WX_PRECOMP
45 #include "wx/palette.h"
46 #endif
47
48 #if wxUSE_IMAGE
49
50 #include "wx/image.h"
51 #include "wx/quantize.h"
52
53 #ifdef __WXMSW__
54 #include "wx/msw/private.h"
55 #endif
56
57 #include <stdlib.h>
58 #include <string.h>
59
60 #if defined(__OS2__)
61 #define RGB_RED_OS2 0
62 #define RGB_GREEN_OS2 1
63 #define RGB_BLUE_OS2 2
64 #else
65 #define RGB_RED 0
66 #define RGB_GREEN 1
67 #define RGB_BLUE 2
68 #endif
69 #define RGB_PIXELSIZE 3
70
71 #define MAXJSAMPLE 255
72 #define CENTERJSAMPLE 128
73 #define BITS_IN_JSAMPLE 8
74 #define GETJSAMPLE(value) ((int) (value))
75
76 #define RIGHT_SHIFT(x,shft) ((x) >> (shft))
77
78 typedef unsigned short UINT16;
79 typedef signed short INT16;
80 #ifndef __WATCOMC__
81 typedef signed int INT32;
82 #endif
83
84 typedef unsigned char JSAMPLE;
85 typedef JSAMPLE *JSAMPROW;
86 typedef JSAMPROW *JSAMPARRAY;
87 typedef unsigned int JDIMENSION;
88
89 typedef struct {
90 void *cquantize;
91 JDIMENSION output_width;
92 JSAMPARRAY colormap;
93 int actual_number_of_colors;
94 int desired_number_of_colors;
95 JSAMPLE *sample_range_limit, *srl_orig;
96 } j_decompress;
97
98 #if defined(__WINDOWS__) && !defined(__WXMICROWIN__)
99 #define JMETHOD(type,methodname,arglist) type (__cdecl methodname) arglist
100 #else
101 #define JMETHOD(type,methodname,arglist) type (methodname) arglist
102 #endif
103
104 typedef j_decompress *j_decompress_ptr;
105 struct jpeg_color_quantizer {
106 JMETHOD(void, start_pass, (j_decompress_ptr cinfo, bool is_pre_scan));
107 JMETHOD(void, color_quantize, (j_decompress_ptr cinfo,
108 JSAMPARRAY input_buf, JSAMPARRAY output_buf,
109 int num_rows));
110 JMETHOD(void, finish_pass, (j_decompress_ptr cinfo));
111 JMETHOD(void, new_color_map, (j_decompress_ptr cinfo));
112 };
113
114
115
116
117 /*
118 * This module implements the well-known Heckbert paradigm for color
119 * quantization. Most of the ideas used here can be traced back to
120 * Heckbert's seminal paper
121 * Heckbert, Paul. "Color Image Quantization for Frame Buffer Display",
122 * Proc. SIGGRAPH '82, Computer Graphics v.16 #3 (July 1982), pp 297-304.
123 *
124 * In the first pass over the image, we accumulate a histogram showing the
125 * usage count of each possible color. To keep the histogram to a reasonable
126 * size, we reduce the precision of the input; typical practice is to retain
127 * 5 or 6 bits per color, so that 8 or 4 different input values are counted
128 * in the same histogram cell.
129 *
130 * Next, the color-selection step begins with a box representing the whole
131 * color space, and repeatedly splits the "largest" remaining box until we
132 * have as many boxes as desired colors. Then the mean color in each
133 * remaining box becomes one of the possible output colors.
134 *
135 * The second pass over the image maps each input pixel to the closest output
136 * color (optionally after applying a Floyd-Steinberg dithering correction).
137 * This mapping is logically trivial, but making it go fast enough requires
138 * considerable care.
139 *
140 * Heckbert-style quantizers vary a good deal in their policies for choosing
141 * the "largest" box and deciding where to cut it. The particular policies
142 * used here have proved out well in experimental comparisons, but better ones
143 * may yet be found.
144 *
145 * In earlier versions of the IJG code, this module quantized in YCbCr color
146 * space, processing the raw upsampled data without a color conversion step.
147 * This allowed the color conversion math to be done only once per colormap
148 * entry, not once per pixel. However, that optimization precluded other
149 * useful optimizations (such as merging color conversion with upsampling)
150 * and it also interfered with desired capabilities such as quantizing to an
151 * externally-supplied colormap. We have therefore abandoned that approach.
152 * The present code works in the post-conversion color space, typically RGB.
153 *
154 * To improve the visual quality of the results, we actually work in scaled
155 * RGB space, giving G distances more weight than R, and R in turn more than
156 * B. To do everything in integer math, we must use integer scale factors.
157 * The 2/3/1 scale factors used here correspond loosely to the relative
158 * weights of the colors in the NTSC grayscale equation.
159 * If you want to use this code to quantize a non-RGB color space, you'll
160 * probably need to change these scale factors.
161 */
162
163 #define R_SCALE 2 /* scale R distances by this much */
164 #define G_SCALE 3 /* scale G distances by this much */
165 #define B_SCALE 1 /* and B by this much */
166
167 /* Relabel R/G/B as components 0/1/2, respecting the RGB ordering defined
168 * in jmorecfg.h. As the code stands, it will do the right thing for R,G,B
169 * and B,G,R orders. If you define some other weird order in jmorecfg.h,
170 * you'll get compile errors until you extend this logic. In that case
171 * you'll probably want to tweak the histogram sizes too.
172 */
173
174 #if defined(__OS2__)
175
176 #if RGB_RED_OS2 == 0
177 #define C0_SCALE R_SCALE
178 #endif
179 #if RGB_BLUE_OS2 == 0
180 #define C0_SCALE B_SCALE
181 #endif
182 #if RGB_GREEN_OS2 == 1
183 #define C1_SCALE G_SCALE
184 #endif
185 #if RGB_RED_OS2 == 2
186 #define C2_SCALE R_SCALE
187 #endif
188 #if RGB_BLUE_OS2 == 2
189 #define C2_SCALE B_SCALE
190 #endif
191
192 #else
193
194 #if RGB_RED == 0
195 #define C0_SCALE R_SCALE
196 #endif
197 #if RGB_BLUE == 0
198 #define C0_SCALE B_SCALE
199 #endif
200 #if RGB_GREEN == 1
201 #define C1_SCALE G_SCALE
202 #endif
203 #if RGB_RED == 2
204 #define C2_SCALE R_SCALE
205 #endif
206 #if RGB_BLUE == 2
207 #define C2_SCALE B_SCALE
208 #endif
209
210 #endif
211
212 /*
213 * First we have the histogram data structure and routines for creating it.
214 *
215 * The number of bits of precision can be adjusted by changing these symbols.
216 * We recommend keeping 6 bits for G and 5 each for R and B.
217 * If you have plenty of memory and cycles, 6 bits all around gives marginally
218 * better results; if you are short of memory, 5 bits all around will save
219 * some space but degrade the results.
220 * To maintain a fully accurate histogram, we'd need to allocate a "long"
221 * (preferably unsigned long) for each cell. In practice this is overkill;
222 * we can get by with 16 bits per cell. Few of the cell counts will overflow,
223 * and clamping those that do overflow to the maximum value will give close-
224 * enough results. This reduces the recommended histogram size from 256Kb
225 * to 128Kb, which is a useful savings on PC-class machines.
226 * (In the second pass the histogram space is re-used for pixel mapping data;
227 * in that capacity, each cell must be able to store zero to the number of
228 * desired colors. 16 bits/cell is plenty for that too.)
229 * Since the JPEG code is intended to run in small memory model on 80x86
230 * machines, we can't just allocate the histogram in one chunk. Instead
231 * of a true 3-D array, we use a row of pointers to 2-D arrays. Each
232 * pointer corresponds to a C0 value (typically 2^5 = 32 pointers) and
233 * each 2-D array has 2^6*2^5 = 2048 or 2^6*2^6 = 4096 entries. Note that
234 * on 80x86 machines, the pointer row is in near memory but the actual
235 * arrays are in far memory (same arrangement as we use for image arrays).
236 */
237
238 #define MAXNUMCOLORS (MAXJSAMPLE+1) /* maximum size of colormap */
239
240 /* These will do the right thing for either R,G,B or B,G,R color order,
241 * but you may not like the results for other color orders.
242 */
243 #define HIST_C0_BITS 5 /* bits of precision in R/B histogram */
244 #define HIST_C1_BITS 6 /* bits of precision in G histogram */
245 #define HIST_C2_BITS 5 /* bits of precision in B/R histogram */
246
247 /* Number of elements along histogram axes. */
248 #define HIST_C0_ELEMS (1<<HIST_C0_BITS)
249 #define HIST_C1_ELEMS (1<<HIST_C1_BITS)
250 #define HIST_C2_ELEMS (1<<HIST_C2_BITS)
251
252 /* These are the amounts to shift an input value to get a histogram index. */
253 #define C0_SHIFT (BITS_IN_JSAMPLE-HIST_C0_BITS)
254 #define C1_SHIFT (BITS_IN_JSAMPLE-HIST_C1_BITS)
255 #define C2_SHIFT (BITS_IN_JSAMPLE-HIST_C2_BITS)
256
257
258 typedef UINT16 histcell; /* histogram cell; prefer an unsigned type */
259
260 typedef histcell * histptr; /* for pointers to histogram cells */
261
262 typedef histcell hist1d[HIST_C2_ELEMS]; /* typedefs for the array */
263 typedef hist1d * hist2d; /* type for the 2nd-level pointers */
264 typedef hist2d * hist3d; /* type for top-level pointer */
265
266
267 /* Declarations for Floyd-Steinberg dithering.
268 *
269 * Errors are accumulated into the array fserrors[], at a resolution of
270 * 1/16th of a pixel count. The error at a given pixel is propagated
271 * to its not-yet-processed neighbors using the standard F-S fractions,
272 * ... (here) 7/16
273 * 3/16 5/16 1/16
274 * We work left-to-right on even rows, right-to-left on odd rows.
275 *
276 * We can get away with a single array (holding one row's worth of errors)
277 * by using it to store the current row's errors at pixel columns not yet
278 * processed, but the next row's errors at columns already processed. We
279 * need only a few extra variables to hold the errors immediately around the
280 * current column. (If we are lucky, those variables are in registers, but
281 * even if not, they're probably cheaper to access than array elements are.)
282 *
283 * The fserrors[] array has (#columns + 2) entries; the extra entry at
284 * each end saves us from special-casing the first and last pixels.
285 * Each entry is three values long, one value for each color component.
286 *
287 * Note: on a wide image, we might not have enough room in a PC's near data
288 * segment to hold the error array; so it is allocated with alloc_large.
289 */
290
291 #if BITS_IN_JSAMPLE == 8
292 typedef INT16 FSERROR; /* 16 bits should be enough */
293 typedef int LOCFSERROR; /* use 'int' for calculation temps */
294 #else
295 typedef INT32 FSERROR; /* may need more than 16 bits */
296 typedef INT32 LOCFSERROR; /* be sure calculation temps are big enough */
297 #endif
298
299 typedef FSERROR *FSERRPTR; /* pointer to error array (in storage!) */
300
301
302 /* Private subobject */
303
304 typedef struct {
305
306 struct {
307 void (*finish_pass)(j_decompress_ptr);
308 void (*color_quantize)(j_decompress_ptr, JSAMPARRAY, JSAMPARRAY, int);
309 void (*start_pass)(j_decompress_ptr, bool);
310 void (*new_color_map)(j_decompress_ptr);
311 } pub;
312
313 /* Space for the eventually created colormap is stashed here */
314 JSAMPARRAY sv_colormap; /* colormap allocated at init time */
315 int desired; /* desired # of colors = size of colormap */
316
317 /* Variables for accumulating image statistics */
318 hist3d histogram; /* pointer to the histogram */
319
320 bool needs_zeroed; /* true if next pass must zero histogram */
321
322 /* Variables for Floyd-Steinberg dithering */
323 FSERRPTR fserrors; /* accumulated errors */
324 bool on_odd_row; /* flag to remember which row we are on */
325 int * error_limiter; /* table for clamping the applied error */
326 } my_cquantizer;
327
328 typedef my_cquantizer * my_cquantize_ptr;
329
330
331 /*
332 * Prescan some rows of pixels.
333 * In this module the prescan simply updates the histogram, which has been
334 * initialized to zeroes by start_pass.
335 * An output_buf parameter is required by the method signature, but no data
336 * is actually output (in fact the buffer controller is probably passing a
337 * NULL pointer).
338 */
339
340 void
341 prescan_quantize (j_decompress_ptr cinfo, JSAMPARRAY input_buf,
342 JSAMPARRAY WXUNUSED(output_buf), int num_rows)
343 {
344 my_cquantize_ptr cquantize = (my_cquantize_ptr) cinfo->cquantize;
345 register JSAMPROW ptr;
346 register histptr histp;
347 register hist3d histogram = cquantize->histogram;
348 int row;
349 JDIMENSION col;
350 JDIMENSION width = cinfo->output_width;
351
352 for (row = 0; row < num_rows; row++) {
353 ptr = input_buf[row];
354 for (col = width; col > 0; col--) {
355
356 {
357
358 /* get pixel value and index into the histogram */
359 histp = & histogram[GETJSAMPLE(ptr[0]) >> C0_SHIFT]
360 [GETJSAMPLE(ptr[1]) >> C1_SHIFT]
361 [GETJSAMPLE(ptr[2]) >> C2_SHIFT];
362 /* increment, check for overflow and undo increment if so. */
363 if (++(*histp) <= 0)
364 (*histp)--;
365 }
366 ptr += 3;
367 }
368 }
369 }
370
371
372 /*
373 * Next we have the really interesting routines: selection of a colormap
374 * given the completed histogram.
375 * These routines work with a list of "boxes", each representing a rectangular
376 * subset of the input color space (to histogram precision).
377 */
378
379 typedef struct {
380 /* The bounds of the box (inclusive); expressed as histogram indexes */
381 int c0min, c0max;
382 int c1min, c1max;
383 int c2min, c2max;
384 /* The volume (actually 2-norm) of the box */
385 INT32 volume;
386 /* The number of nonzero histogram cells within this box */
387 long colorcount;
388 } box;
389
390 typedef box * boxptr;
391
392
393 boxptr
394 find_biggest_color_pop (boxptr boxlist, int numboxes)
395 /* Find the splittable box with the largest color population */
396 /* Returns NULL if no splittable boxes remain */
397 {
398 register boxptr boxp;
399 register int i;
400 register long maxc = 0;
401 boxptr which = NULL;
402
403 for (i = 0, boxp = boxlist; i < numboxes; i++, boxp++) {
404 if (boxp->colorcount > maxc && boxp->volume > 0) {
405 which = boxp;
406 maxc = boxp->colorcount;
407 }
408 }
409 return which;
410 }
411
412
413 boxptr
414 find_biggest_volume (boxptr boxlist, int numboxes)
415 /* Find the splittable box with the largest (scaled) volume */
416 /* Returns NULL if no splittable boxes remain */
417 {
418 register boxptr boxp;
419 register int i;
420 register INT32 maxv = 0;
421 boxptr which = NULL;
422
423 for (i = 0, boxp = boxlist; i < numboxes; i++, boxp++) {
424 if (boxp->volume > maxv) {
425 which = boxp;
426 maxv = boxp->volume;
427 }
428 }
429 return which;
430 }
431
432
433 void
434 update_box (j_decompress_ptr cinfo, boxptr boxp)
435 /* Shrink the min/max bounds of a box to enclose only nonzero elements, */
436 /* and recompute its volume and population */
437 {
438 my_cquantize_ptr cquantize = (my_cquantize_ptr) cinfo->cquantize;
439 hist3d histogram = cquantize->histogram;
440 histptr histp;
441 int c0,c1,c2;
442 int c0min,c0max,c1min,c1max,c2min,c2max;
443 INT32 dist0,dist1,dist2;
444 long ccount;
445
446 c0min = boxp->c0min; c0max = boxp->c0max;
447 c1min = boxp->c1min; c1max = boxp->c1max;
448 c2min = boxp->c2min; c2max = boxp->c2max;
449
450 if (c0max > c0min)
451 for (c0 = c0min; c0 <= c0max; c0++)
452 for (c1 = c1min; c1 <= c1max; c1++) {
453 histp = & histogram[c0][c1][c2min];
454 for (c2 = c2min; c2 <= c2max; c2++)
455 if (*histp++ != 0) {
456 boxp->c0min = c0min = c0;
457 goto have_c0min;
458 }
459 }
460 have_c0min:
461 if (c0max > c0min)
462 for (c0 = c0max; c0 >= c0min; c0--)
463 for (c1 = c1min; c1 <= c1max; c1++) {
464 histp = & histogram[c0][c1][c2min];
465 for (c2 = c2min; c2 <= c2max; c2++)
466 if (*histp++ != 0) {
467 boxp->c0max = c0max = c0;
468 goto have_c0max;
469 }
470 }
471 have_c0max:
472 if (c1max > c1min)
473 for (c1 = c1min; c1 <= c1max; c1++)
474 for (c0 = c0min; c0 <= c0max; c0++) {
475 histp = & histogram[c0][c1][c2min];
476 for (c2 = c2min; c2 <= c2max; c2++)
477 if (*histp++ != 0) {
478 boxp->c1min = c1min = c1;
479 goto have_c1min;
480 }
481 }
482 have_c1min:
483 if (c1max > c1min)
484 for (c1 = c1max; c1 >= c1min; c1--)
485 for (c0 = c0min; c0 <= c0max; c0++) {
486 histp = & histogram[c0][c1][c2min];
487 for (c2 = c2min; c2 <= c2max; c2++)
488 if (*histp++ != 0) {
489 boxp->c1max = c1max = c1;
490 goto have_c1max;
491 }
492 }
493 have_c1max:
494 if (c2max > c2min)
495 for (c2 = c2min; c2 <= c2max; c2++)
496 for (c0 = c0min; c0 <= c0max; c0++) {
497 histp = & histogram[c0][c1min][c2];
498 for (c1 = c1min; c1 <= c1max; c1++, histp += HIST_C2_ELEMS)
499 if (*histp != 0) {
500 boxp->c2min = c2min = c2;
501 goto have_c2min;
502 }
503 }
504 have_c2min:
505 if (c2max > c2min)
506 for (c2 = c2max; c2 >= c2min; c2--)
507 for (c0 = c0min; c0 <= c0max; c0++) {
508 histp = & histogram[c0][c1min][c2];
509 for (c1 = c1min; c1 <= c1max; c1++, histp += HIST_C2_ELEMS)
510 if (*histp != 0) {
511 boxp->c2max = c2max = c2;
512 goto have_c2max;
513 }
514 }
515 have_c2max:
516
517 /* Update box volume.
518 * We use 2-norm rather than real volume here; this biases the method
519 * against making long narrow boxes, and it has the side benefit that
520 * a box is splittable iff norm > 0.
521 * Since the differences are expressed in histogram-cell units,
522 * we have to shift back to JSAMPLE units to get consistent distances;
523 * after which, we scale according to the selected distance scale factors.
524 */
525 dist0 = ((c0max - c0min) << C0_SHIFT) * C0_SCALE;
526 dist1 = ((c1max - c1min) << C1_SHIFT) * C1_SCALE;
527 dist2 = ((c2max - c2min) << C2_SHIFT) * C2_SCALE;
528 boxp->volume = dist0*dist0 + dist1*dist1 + dist2*dist2;
529
530 /* Now scan remaining volume of box and compute population */
531 ccount = 0;
532 for (c0 = c0min; c0 <= c0max; c0++)
533 for (c1 = c1min; c1 <= c1max; c1++) {
534 histp = & histogram[c0][c1][c2min];
535 for (c2 = c2min; c2 <= c2max; c2++, histp++)
536 if (*histp != 0) {
537 ccount++;
538 }
539 }
540 boxp->colorcount = ccount;
541 }
542
543
544 int
545 median_cut (j_decompress_ptr cinfo, boxptr boxlist, int numboxes,
546 int desired_colors)
547 /* Repeatedly select and split the largest box until we have enough boxes */
548 {
549 int n,lb;
550 int c0,c1,c2,cmax;
551 register boxptr b1,b2;
552
553 while (numboxes < desired_colors) {
554 /* Select box to split.
555 * Current algorithm: by population for first half, then by volume.
556 */
557 if ((numboxes*2) <= desired_colors) {
558 b1 = find_biggest_color_pop(boxlist, numboxes);
559 } else {
560 b1 = find_biggest_volume(boxlist, numboxes);
561 }
562 if (b1 == NULL) /* no splittable boxes left! */
563 break;
564 b2 = &boxlist[numboxes]; /* where new box will go */
565 /* Copy the color bounds to the new box. */
566 b2->c0max = b1->c0max; b2->c1max = b1->c1max; b2->c2max = b1->c2max;
567 b2->c0min = b1->c0min; b2->c1min = b1->c1min; b2->c2min = b1->c2min;
568 /* Choose which axis to split the box on.
569 * Current algorithm: longest scaled axis.
570 * See notes in update_box about scaling distances.
571 */
572 c0 = ((b1->c0max - b1->c0min) << C0_SHIFT) * C0_SCALE;
573 c1 = ((b1->c1max - b1->c1min) << C1_SHIFT) * C1_SCALE;
574 c2 = ((b1->c2max - b1->c2min) << C2_SHIFT) * C2_SCALE;
575 /* We want to break any ties in favor of green, then red, blue last.
576 * This code does the right thing for R,G,B or B,G,R color orders only.
577 */
578 #if defined(__VISAGECPP__)
579
580 #if RGB_RED_OS2 == 0
581 cmax = c1; n = 1;
582 if (c0 > cmax) { cmax = c0; n = 0; }
583 if (c2 > cmax) { n = 2; }
584 #else
585 cmax = c1; n = 1;
586 if (c2 > cmax) { cmax = c2; n = 2; }
587 if (c0 > cmax) { n = 0; }
588 #endif
589
590 #else
591
592 #if RGB_RED == 0
593 cmax = c1; n = 1;
594 if (c0 > cmax) { cmax = c0; n = 0; }
595 if (c2 > cmax) { n = 2; }
596 #else
597 cmax = c1; n = 1;
598 if (c2 > cmax) { cmax = c2; n = 2; }
599 if (c0 > cmax) { n = 0; }
600 #endif
601
602 #endif
603 /* Choose split point along selected axis, and update box bounds.
604 * Current algorithm: split at halfway point.
605 * (Since the box has been shrunk to minimum volume,
606 * any split will produce two nonempty subboxes.)
607 * Note that lb value is max for lower box, so must be < old max.
608 */
609 switch (n) {
610 case 0:
611 lb = (b1->c0max + b1->c0min) / 2;
612 b1->c0max = lb;
613 b2->c0min = lb+1;
614 break;
615 case 1:
616 lb = (b1->c1max + b1->c1min) / 2;
617 b1->c1max = lb;
618 b2->c1min = lb+1;
619 break;
620 case 2:
621 lb = (b1->c2max + b1->c2min) / 2;
622 b1->c2max = lb;
623 b2->c2min = lb+1;
624 break;
625 }
626 /* Update stats for boxes */
627 update_box(cinfo, b1);
628 update_box(cinfo, b2);
629 numboxes++;
630 }
631 return numboxes;
632 }
633
634
635 void
636 compute_color (j_decompress_ptr cinfo, boxptr boxp, int icolor)
637 /* Compute representative color for a box, put it in colormap[icolor] */
638 {
639 /* Current algorithm: mean weighted by pixels (not colors) */
640 /* Note it is important to get the rounding correct! */
641 my_cquantize_ptr cquantize = (my_cquantize_ptr) cinfo->cquantize;
642 hist3d histogram = cquantize->histogram;
643 histptr histp;
644 int c0,c1,c2;
645 int c0min,c0max,c1min,c1max,c2min,c2max;
646 long count;
647 long total = 0;
648 long c0total = 0;
649 long c1total = 0;
650 long c2total = 0;
651
652 c0min = boxp->c0min; c0max = boxp->c0max;
653 c1min = boxp->c1min; c1max = boxp->c1max;
654 c2min = boxp->c2min; c2max = boxp->c2max;
655
656 for (c0 = c0min; c0 <= c0max; c0++)
657 for (c1 = c1min; c1 <= c1max; c1++) {
658 histp = & histogram[c0][c1][c2min];
659 for (c2 = c2min; c2 <= c2max; c2++) {
660 if ((count = *histp++) != 0) {
661 total += count;
662 c0total += ((c0 << C0_SHIFT) + ((1<<C0_SHIFT)>>1)) * count;
663 c1total += ((c1 << C1_SHIFT) + ((1<<C1_SHIFT)>>1)) * count;
664 c2total += ((c2 << C2_SHIFT) + ((1<<C2_SHIFT)>>1)) * count;
665 }
666 }
667 }
668
669 cinfo->colormap[0][icolor] = (JSAMPLE) ((c0total + (total>>1)) / total);
670 cinfo->colormap[1][icolor] = (JSAMPLE) ((c1total + (total>>1)) / total);
671 cinfo->colormap[2][icolor] = (JSAMPLE) ((c2total + (total>>1)) / total);
672 }
673
674
675 static void
676 select_colors (j_decompress_ptr cinfo, int desired_colors)
677 /* Master routine for color selection */
678 {
679 boxptr boxlist;
680 int numboxes;
681 int i;
682
683 /* Allocate workspace for box list */
684 boxlist = (boxptr) malloc(desired_colors * sizeof(box));
685 /* Initialize one box containing whole space */
686 numboxes = 1;
687 boxlist[0].c0min = 0;
688 boxlist[0].c0max = MAXJSAMPLE >> C0_SHIFT;
689 boxlist[0].c1min = 0;
690 boxlist[0].c1max = MAXJSAMPLE >> C1_SHIFT;
691 boxlist[0].c2min = 0;
692 boxlist[0].c2max = MAXJSAMPLE >> C2_SHIFT;
693 /* Shrink it to actually-used volume and set its statistics */
694 update_box(cinfo, & boxlist[0]);
695 /* Perform median-cut to produce final box list */
696 numboxes = median_cut(cinfo, boxlist, numboxes, desired_colors);
697 /* Compute the representative color for each box, fill colormap */
698 for (i = 0; i < numboxes; i++)
699 compute_color(cinfo, & boxlist[i], i);
700 cinfo->actual_number_of_colors = numboxes;
701
702 free(boxlist); //FIXME?? I don't know if this is correct - VS
703 }
704
705
706 /*
707 * These routines are concerned with the time-critical task of mapping input
708 * colors to the nearest color in the selected colormap.
709 *
710 * We re-use the histogram space as an "inverse color map", essentially a
711 * cache for the results of nearest-color searches. All colors within a
712 * histogram cell will be mapped to the same colormap entry, namely the one
713 * closest to the cell's center. This may not be quite the closest entry to
714 * the actual input color, but it's almost as good. A zero in the cache
715 * indicates we haven't found the nearest color for that cell yet; the array
716 * is cleared to zeroes before starting the mapping pass. When we find the
717 * nearest color for a cell, its colormap index plus one is recorded in the
718 * cache for future use. The pass2 scanning routines call fill_inverse_cmap
719 * when they need to use an unfilled entry in the cache.
720 *
721 * Our method of efficiently finding nearest colors is based on the "locally
722 * sorted search" idea described by Heckbert and on the incremental distance
723 * calculation described by Spencer W. Thomas in chapter III.1 of Graphics
724 * Gems II (James Arvo, ed. Academic Press, 1991). Thomas points out that
725 * the distances from a given colormap entry to each cell of the histogram can
726 * be computed quickly using an incremental method: the differences between
727 * distances to adjacent cells themselves differ by a constant. This allows a
728 * fairly fast implementation of the "brute force" approach of computing the
729 * distance from every colormap entry to every histogram cell. Unfortunately,
730 * it needs a work array to hold the best-distance-so-far for each histogram
731 * cell (because the inner loop has to be over cells, not colormap entries).
732 * The work array elements have to be INT32s, so the work array would need
733 * 256Kb at our recommended precision. This is not feasible in DOS machines.
734 *
735 * To get around these problems, we apply Thomas' method to compute the
736 * nearest colors for only the cells within a small subbox of the histogram.
737 * The work array need be only as big as the subbox, so the memory usage
738 * problem is solved. Furthermore, we need not fill subboxes that are never
739 * referenced in pass2; many images use only part of the color gamut, so a
740 * fair amount of work is saved. An additional advantage of this
741 * approach is that we can apply Heckbert's locality criterion to quickly
742 * eliminate colormap entries that are far away from the subbox; typically
743 * three-fourths of the colormap entries are rejected by Heckbert's criterion,
744 * and we need not compute their distances to individual cells in the subbox.
745 * The speed of this approach is heavily influenced by the subbox size: too
746 * small means too much overhead, too big loses because Heckbert's criterion
747 * can't eliminate as many colormap entries. Empirically the best subbox
748 * size seems to be about 1/512th of the histogram (1/8th in each direction).
749 *
750 * Thomas' article also describes a refined method which is asymptotically
751 * faster than the brute-force method, but it is also far more complex and
752 * cannot efficiently be applied to small subboxes. It is therefore not
753 * useful for programs intended to be portable to DOS machines. On machines
754 * with plenty of memory, filling the whole histogram in one shot with Thomas'
755 * refined method might be faster than the present code --- but then again,
756 * it might not be any faster, and it's certainly more complicated.
757 */
758
759
760 /* log2(histogram cells in update box) for each axis; this can be adjusted */
761 #define BOX_C0_LOG (HIST_C0_BITS-3)
762 #define BOX_C1_LOG (HIST_C1_BITS-3)
763 #define BOX_C2_LOG (HIST_C2_BITS-3)
764
765 #define BOX_C0_ELEMS (1<<BOX_C0_LOG) /* # of hist cells in update box */
766 #define BOX_C1_ELEMS (1<<BOX_C1_LOG)
767 #define BOX_C2_ELEMS (1<<BOX_C2_LOG)
768
769 #define BOX_C0_SHIFT (C0_SHIFT + BOX_C0_LOG)
770 #define BOX_C1_SHIFT (C1_SHIFT + BOX_C1_LOG)
771 #define BOX_C2_SHIFT (C2_SHIFT + BOX_C2_LOG)
772
773
774 /*
775 * The next three routines implement inverse colormap filling. They could
776 * all be folded into one big routine, but splitting them up this way saves
777 * some stack space (the mindist[] and bestdist[] arrays need not coexist)
778 * and may allow some compilers to produce better code by registerizing more
779 * inner-loop variables.
780 */
781
782 static int
783 find_nearby_colors (j_decompress_ptr cinfo, int minc0, int minc1, int minc2,
784 JSAMPLE colorlist[])
785 /* Locate the colormap entries close enough to an update box to be candidates
786 * for the nearest entry to some cell(s) in the update box. The update box
787 * is specified by the center coordinates of its first cell. The number of
788 * candidate colormap entries is returned, and their colormap indexes are
789 * placed in colorlist[].
790 * This routine uses Heckbert's "locally sorted search" criterion to select
791 * the colors that need further consideration.
792 */
793 {
794 int numcolors = cinfo->actual_number_of_colors;
795 int maxc0, maxc1, maxc2;
796 int centerc0, centerc1, centerc2;
797 int i, x, ncolors;
798 INT32 minmaxdist, min_dist, max_dist, tdist;
799 INT32 mindist[MAXNUMCOLORS]; /* min distance to colormap entry i */
800
801 /* Compute true coordinates of update box's upper corner and center.
802 * Actually we compute the coordinates of the center of the upper-corner
803 * histogram cell, which are the upper bounds of the volume we care about.
804 * Note that since ">>" rounds down, the "center" values may be closer to
805 * min than to max; hence comparisons to them must be "<=", not "<".
806 */
807 maxc0 = minc0 + ((1 << BOX_C0_SHIFT) - (1 << C0_SHIFT));
808 centerc0 = (minc0 + maxc0) >> 1;
809 maxc1 = minc1 + ((1 << BOX_C1_SHIFT) - (1 << C1_SHIFT));
810 centerc1 = (minc1 + maxc1) >> 1;
811 maxc2 = minc2 + ((1 << BOX_C2_SHIFT) - (1 << C2_SHIFT));
812 centerc2 = (minc2 + maxc2) >> 1;
813
814 /* For each color in colormap, find:
815 * 1. its minimum squared-distance to any point in the update box
816 * (zero if color is within update box);
817 * 2. its maximum squared-distance to any point in the update box.
818 * Both of these can be found by considering only the corners of the box.
819 * We save the minimum distance for each color in mindist[];
820 * only the smallest maximum distance is of interest.
821 */
822 minmaxdist = 0x7FFFFFFFL;
823
824 for (i = 0; i < numcolors; i++) {
825 /* We compute the squared-c0-distance term, then add in the other two. */
826 x = GETJSAMPLE(cinfo->colormap[0][i]);
827 if (x < minc0) {
828 tdist = (x - minc0) * C0_SCALE;
829 min_dist = tdist*tdist;
830 tdist = (x - maxc0) * C0_SCALE;
831 max_dist = tdist*tdist;
832 } else if (x > maxc0) {
833 tdist = (x - maxc0) * C0_SCALE;
834 min_dist = tdist*tdist;
835 tdist = (x - minc0) * C0_SCALE;
836 max_dist = tdist*tdist;
837 } else {
838 /* within cell range so no contribution to min_dist */
839 min_dist = 0;
840 if (x <= centerc0) {
841 tdist = (x - maxc0) * C0_SCALE;
842 max_dist = tdist*tdist;
843 } else {
844 tdist = (x - minc0) * C0_SCALE;
845 max_dist = tdist*tdist;
846 }
847 }
848
849 x = GETJSAMPLE(cinfo->colormap[1][i]);
850 if (x < minc1) {
851 tdist = (x - minc1) * C1_SCALE;
852 min_dist += tdist*tdist;
853 tdist = (x - maxc1) * C1_SCALE;
854 max_dist += tdist*tdist;
855 } else if (x > maxc1) {
856 tdist = (x - maxc1) * C1_SCALE;
857 min_dist += tdist*tdist;
858 tdist = (x - minc1) * C1_SCALE;
859 max_dist += tdist*tdist;
860 } else {
861 /* within cell range so no contribution to min_dist */
862 if (x <= centerc1) {
863 tdist = (x - maxc1) * C1_SCALE;
864 max_dist += tdist*tdist;
865 } else {
866 tdist = (x - minc1) * C1_SCALE;
867 max_dist += tdist*tdist;
868 }
869 }
870
871 x = GETJSAMPLE(cinfo->colormap[2][i]);
872 if (x < minc2) {
873 tdist = (x - minc2) * C2_SCALE;
874 min_dist += tdist*tdist;
875 tdist = (x - maxc2) * C2_SCALE;
876 max_dist += tdist*tdist;
877 } else if (x > maxc2) {
878 tdist = (x - maxc2) * C2_SCALE;
879 min_dist += tdist*tdist;
880 tdist = (x - minc2) * C2_SCALE;
881 max_dist += tdist*tdist;
882 } else {
883 /* within cell range so no contribution to min_dist */
884 if (x <= centerc2) {
885 tdist = (x - maxc2) * C2_SCALE;
886 max_dist += tdist*tdist;
887 } else {
888 tdist = (x - minc2) * C2_SCALE;
889 max_dist += tdist*tdist;
890 }
891 }
892
893 mindist[i] = min_dist; /* save away the results */
894 if (max_dist < minmaxdist)
895 minmaxdist = max_dist;
896 }
897
898 /* Now we know that no cell in the update box is more than minmaxdist
899 * away from some colormap entry. Therefore, only colors that are
900 * within minmaxdist of some part of the box need be considered.
901 */
902 ncolors = 0;
903 for (i = 0; i < numcolors; i++) {
904 if (mindist[i] <= minmaxdist)
905 colorlist[ncolors++] = (JSAMPLE) i;
906 }
907 return ncolors;
908 }
909
910
911 static void
912 find_best_colors (j_decompress_ptr cinfo, int minc0, int minc1, int minc2,
913 int numcolors, JSAMPLE colorlist[], JSAMPLE bestcolor[])
914 /* Find the closest colormap entry for each cell in the update box,
915 * given the list of candidate colors prepared by find_nearby_colors.
916 * Return the indexes of the closest entries in the bestcolor[] array.
917 * This routine uses Thomas' incremental distance calculation method to
918 * find the distance from a colormap entry to successive cells in the box.
919 */
920 {
921 int ic0, ic1, ic2;
922 int i, icolor;
923 register INT32 * bptr; /* pointer into bestdist[] array */
924 JSAMPLE * cptr; /* pointer into bestcolor[] array */
925 INT32 dist0, dist1; /* initial distance values */
926 register INT32 dist2; /* current distance in inner loop */
927 INT32 xx0, xx1; /* distance increments */
928 register INT32 xx2;
929 INT32 inc0, inc1, inc2; /* initial values for increments */
930 /* This array holds the distance to the nearest-so-far color for each cell */
931 INT32 bestdist[BOX_C0_ELEMS * BOX_C1_ELEMS * BOX_C2_ELEMS];
932
933 /* Initialize best-distance for each cell of the update box */
934 bptr = bestdist;
935 for (i = BOX_C0_ELEMS*BOX_C1_ELEMS*BOX_C2_ELEMS-1; i >= 0; i--)
936 *bptr++ = 0x7FFFFFFFL;
937
938 /* For each color selected by find_nearby_colors,
939 * compute its distance to the center of each cell in the box.
940 * If that's less than best-so-far, update best distance and color number.
941 */
942
943 /* Nominal steps between cell centers ("x" in Thomas article) */
944 #define STEP_C0 ((1 << C0_SHIFT) * C0_SCALE)
945 #define STEP_C1 ((1 << C1_SHIFT) * C1_SCALE)
946 #define STEP_C2 ((1 << C2_SHIFT) * C2_SCALE)
947
948 for (i = 0; i < numcolors; i++) {
949 icolor = GETJSAMPLE(colorlist[i]);
950 /* Compute (square of) distance from minc0/c1/c2 to this color */
951 inc0 = (minc0 - GETJSAMPLE(cinfo->colormap[0][icolor])) * C0_SCALE;
952 dist0 = inc0*inc0;
953 inc1 = (minc1 - GETJSAMPLE(cinfo->colormap[1][icolor])) * C1_SCALE;
954 dist0 += inc1*inc1;
955 inc2 = (minc2 - GETJSAMPLE(cinfo->colormap[2][icolor])) * C2_SCALE;
956 dist0 += inc2*inc2;
957 /* Form the initial difference increments */
958 inc0 = inc0 * (2 * STEP_C0) + STEP_C0 * STEP_C0;
959 inc1 = inc1 * (2 * STEP_C1) + STEP_C1 * STEP_C1;
960 inc2 = inc2 * (2 * STEP_C2) + STEP_C2 * STEP_C2;
961 /* Now loop over all cells in box, updating distance per Thomas method */
962 bptr = bestdist;
963 cptr = bestcolor;
964 xx0 = inc0;
965 for (ic0 = BOX_C0_ELEMS-1; ic0 >= 0; ic0--) {
966 dist1 = dist0;
967 xx1 = inc1;
968 for (ic1 = BOX_C1_ELEMS-1; ic1 >= 0; ic1--) {
969 dist2 = dist1;
970 xx2 = inc2;
971 for (ic2 = BOX_C2_ELEMS-1; ic2 >= 0; ic2--) {
972 if (dist2 < *bptr) {
973 *bptr = dist2;
974 *cptr = (JSAMPLE) icolor;
975 }
976 dist2 += xx2;
977 xx2 += 2 * STEP_C2 * STEP_C2;
978 bptr++;
979 cptr++;
980 }
981 dist1 += xx1;
982 xx1 += 2 * STEP_C1 * STEP_C1;
983 }
984 dist0 += xx0;
985 xx0 += 2 * STEP_C0 * STEP_C0;
986 }
987 }
988 }
989
990
991 static void
992 fill_inverse_cmap (j_decompress_ptr cinfo, int c0, int c1, int c2)
993 /* Fill the inverse-colormap entries in the update box that contains */
994 /* histogram cell c0/c1/c2. (Only that one cell MUST be filled, but */
995 /* we can fill as many others as we wish.) */
996 {
997 my_cquantize_ptr cquantize = (my_cquantize_ptr) cinfo->cquantize;
998 hist3d histogram = cquantize->histogram;
999 int minc0, minc1, minc2; /* lower left corner of update box */
1000 int ic0, ic1, ic2;
1001 register JSAMPLE * cptr; /* pointer into bestcolor[] array */
1002 register histptr cachep; /* pointer into main cache array */
1003 /* This array lists the candidate colormap indexes. */
1004 JSAMPLE colorlist[MAXNUMCOLORS];
1005 int numcolors; /* number of candidate colors */
1006 /* This array holds the actually closest colormap index for each cell. */
1007 JSAMPLE bestcolor[BOX_C0_ELEMS * BOX_C1_ELEMS * BOX_C2_ELEMS];
1008
1009 /* Convert cell coordinates to update box ID */
1010 c0 >>= BOX_C0_LOG;
1011 c1 >>= BOX_C1_LOG;
1012 c2 >>= BOX_C2_LOG;
1013
1014 /* Compute true coordinates of update box's origin corner.
1015 * Actually we compute the coordinates of the center of the corner
1016 * histogram cell, which are the lower bounds of the volume we care about.
1017 */
1018 minc0 = (c0 << BOX_C0_SHIFT) + ((1 << C0_SHIFT) >> 1);
1019 minc1 = (c1 << BOX_C1_SHIFT) + ((1 << C1_SHIFT) >> 1);
1020 minc2 = (c2 << BOX_C2_SHIFT) + ((1 << C2_SHIFT) >> 1);
1021
1022 /* Determine which colormap entries are close enough to be candidates
1023 * for the nearest entry to some cell in the update box.
1024 */
1025 numcolors = find_nearby_colors(cinfo, minc0, minc1, minc2, colorlist);
1026
1027 /* Determine the actually nearest colors. */
1028 find_best_colors(cinfo, minc0, minc1, minc2, numcolors, colorlist,
1029 bestcolor);
1030
1031 /* Save the best color numbers (plus 1) in the main cache array */
1032 c0 <<= BOX_C0_LOG; /* convert ID back to base cell indexes */
1033 c1 <<= BOX_C1_LOG;
1034 c2 <<= BOX_C2_LOG;
1035 cptr = bestcolor;
1036 for (ic0 = 0; ic0 < BOX_C0_ELEMS; ic0++) {
1037 for (ic1 = 0; ic1 < BOX_C1_ELEMS; ic1++) {
1038 cachep = & histogram[c0+ic0][c1+ic1][c2];
1039 for (ic2 = 0; ic2 < BOX_C2_ELEMS; ic2++) {
1040 *cachep++ = (histcell) (GETJSAMPLE(*cptr++) + 1);
1041 }
1042 }
1043 }
1044 }
1045
1046
1047 /*
1048 * Map some rows of pixels to the output colormapped representation.
1049 */
1050
1051 void
1052 pass2_no_dither (j_decompress_ptr cinfo,
1053 JSAMPARRAY input_buf, JSAMPARRAY output_buf, int num_rows)
1054 /* This version performs no dithering */
1055 {
1056 my_cquantize_ptr cquantize = (my_cquantize_ptr) cinfo->cquantize;
1057 hist3d histogram = cquantize->histogram;
1058 register JSAMPROW inptr, outptr;
1059 register histptr cachep;
1060 register int c0, c1, c2;
1061 int row;
1062 JDIMENSION col;
1063 JDIMENSION width = cinfo->output_width;
1064
1065 for (row = 0; row < num_rows; row++) {
1066 inptr = input_buf[row];
1067 outptr = output_buf[row];
1068 for (col = width; col > 0; col--) {
1069 /* get pixel value and index into the cache */
1070 c0 = GETJSAMPLE(*inptr++) >> C0_SHIFT;
1071 c1 = GETJSAMPLE(*inptr++) >> C1_SHIFT;
1072 c2 = GETJSAMPLE(*inptr++) >> C2_SHIFT;
1073 cachep = & histogram[c0][c1][c2];
1074 /* If we have not seen this color before, find nearest colormap entry */
1075 /* and update the cache */
1076 if (*cachep == 0)
1077 fill_inverse_cmap(cinfo, c0,c1,c2);
1078 /* Now emit the colormap index for this cell */
1079 *outptr++ = (JSAMPLE) (*cachep - 1);
1080 }
1081 }
1082 }
1083
1084
1085 void
1086 pass2_fs_dither (j_decompress_ptr cinfo,
1087 JSAMPARRAY input_buf, JSAMPARRAY output_buf, int num_rows)
1088 /* This version performs Floyd-Steinberg dithering */
1089 {
1090 my_cquantize_ptr cquantize = (my_cquantize_ptr) cinfo->cquantize;
1091 hist3d histogram = cquantize->histogram;
1092 register LOCFSERROR cur0, cur1, cur2; /* current error or pixel value */
1093 LOCFSERROR belowerr0, belowerr1, belowerr2; /* error for pixel below cur */
1094 LOCFSERROR bpreverr0, bpreverr1, bpreverr2; /* error for below/prev col */
1095 register FSERRPTR errorptr; /* => fserrors[] at column before current */
1096 JSAMPROW inptr; /* => current input pixel */
1097 JSAMPROW outptr; /* => current output pixel */
1098 histptr cachep;
1099 int dir; /* +1 or -1 depending on direction */
1100 int dir3; /* 3*dir, for advancing inptr & errorptr */
1101 int row;
1102 JDIMENSION col;
1103 JDIMENSION width = cinfo->output_width;
1104 JSAMPLE *range_limit = cinfo->sample_range_limit;
1105 int *error_limit = cquantize->error_limiter;
1106 JSAMPROW colormap0 = cinfo->colormap[0];
1107 JSAMPROW colormap1 = cinfo->colormap[1];
1108 JSAMPROW colormap2 = cinfo->colormap[2];
1109
1110
1111 for (row = 0; row < num_rows; row++) {
1112 inptr = input_buf[row];
1113 outptr = output_buf[row];
1114 if (cquantize->on_odd_row) {
1115 /* work right to left in this row */
1116 inptr += (width-1) * 3; /* so point to rightmost pixel */
1117 outptr += width-1;
1118 dir = -1;
1119 dir3 = -3;
1120 errorptr = cquantize->fserrors + (width+1)*3; /* => entry after last column */
1121 cquantize->on_odd_row = false; /* flip for next time */
1122 } else {
1123 /* work left to right in this row */
1124 dir = 1;
1125 dir3 = 3;
1126 errorptr = cquantize->fserrors; /* => entry before first real column */
1127 cquantize->on_odd_row = true; /* flip for next time */
1128 }
1129 /* Preset error values: no error propagated to first pixel from left */
1130 cur0 = cur1 = cur2 = 0;
1131 /* and no error propagated to row below yet */
1132 belowerr0 = belowerr1 = belowerr2 = 0;
1133 bpreverr0 = bpreverr1 = bpreverr2 = 0;
1134
1135 for (col = width; col > 0; col--) {
1136 /* curN holds the error propagated from the previous pixel on the
1137 * current line. Add the error propagated from the previous line
1138 * to form the complete error correction term for this pixel, and
1139 * round the error term (which is expressed * 16) to an integer.
1140 * RIGHT_SHIFT rounds towards minus infinity, so adding 8 is correct
1141 * for either sign of the error value.
1142 * Note: errorptr points to *previous* column's array entry.
1143 */
1144 cur0 = RIGHT_SHIFT(cur0 + errorptr[dir3+0] + 8, 4);
1145 cur1 = RIGHT_SHIFT(cur1 + errorptr[dir3+1] + 8, 4);
1146 cur2 = RIGHT_SHIFT(cur2 + errorptr[dir3+2] + 8, 4);
1147 /* Limit the error using transfer function set by init_error_limit.
1148 * See comments with init_error_limit for rationale.
1149 */
1150 cur0 = error_limit[cur0];
1151 cur1 = error_limit[cur1];
1152 cur2 = error_limit[cur2];
1153 /* Form pixel value + error, and range-limit to 0..MAXJSAMPLE.
1154 * The maximum error is +- MAXJSAMPLE (or less with error limiting);
1155 * this sets the required size of the range_limit array.
1156 */
1157 cur0 += GETJSAMPLE(inptr[0]);
1158 cur1 += GETJSAMPLE(inptr[1]);
1159 cur2 += GETJSAMPLE(inptr[2]);
1160 cur0 = GETJSAMPLE(range_limit[cur0]);
1161 cur1 = GETJSAMPLE(range_limit[cur1]);
1162 cur2 = GETJSAMPLE(range_limit[cur2]);
1163 /* Index into the cache with adjusted pixel value */
1164 cachep = & histogram[cur0>>C0_SHIFT][cur1>>C1_SHIFT][cur2>>C2_SHIFT];
1165 /* If we have not seen this color before, find nearest colormap */
1166 /* entry and update the cache */
1167 if (*cachep == 0)
1168 fill_inverse_cmap(cinfo, cur0>>C0_SHIFT,cur1>>C1_SHIFT,cur2>>C2_SHIFT);
1169 /* Now emit the colormap index for this cell */
1170 { register int pixcode = *cachep - 1;
1171 *outptr = (JSAMPLE) pixcode;
1172 /* Compute representation error for this pixel */
1173 cur0 -= GETJSAMPLE(colormap0[pixcode]);
1174 cur1 -= GETJSAMPLE(colormap1[pixcode]);
1175 cur2 -= GETJSAMPLE(colormap2[pixcode]);
1176 }
1177 /* Compute error fractions to be propagated to adjacent pixels.
1178 * Add these into the running sums, and simultaneously shift the
1179 * next-line error sums left by 1 column.
1180 */
1181 { register LOCFSERROR bnexterr, delta;
1182
1183 bnexterr = cur0; /* Process component 0 */
1184 delta = cur0 * 2;
1185 cur0 += delta; /* form error * 3 */
1186 errorptr[0] = (FSERROR) (bpreverr0 + cur0);
1187 cur0 += delta; /* form error * 5 */
1188 bpreverr0 = belowerr0 + cur0;
1189 belowerr0 = bnexterr;
1190 cur0 += delta; /* form error * 7 */
1191 bnexterr = cur1; /* Process component 1 */
1192 delta = cur1 * 2;
1193 cur1 += delta; /* form error * 3 */
1194 errorptr[1] = (FSERROR) (bpreverr1 + cur1);
1195 cur1 += delta; /* form error * 5 */
1196 bpreverr1 = belowerr1 + cur1;
1197 belowerr1 = bnexterr;
1198 cur1 += delta; /* form error * 7 */
1199 bnexterr = cur2; /* Process component 2 */
1200 delta = cur2 * 2;
1201 cur2 += delta; /* form error * 3 */
1202 errorptr[2] = (FSERROR) (bpreverr2 + cur2);
1203 cur2 += delta; /* form error * 5 */
1204 bpreverr2 = belowerr2 + cur2;
1205 belowerr2 = bnexterr;
1206 cur2 += delta; /* form error * 7 */
1207 }
1208 /* At this point curN contains the 7/16 error value to be propagated
1209 * to the next pixel on the current line, and all the errors for the
1210 * next line have been shifted over. We are therefore ready to move on.
1211 */
1212 inptr += dir3; /* Advance pixel pointers to next column */
1213 outptr += dir;
1214 errorptr += dir3; /* advance errorptr to current column */
1215 }
1216 /* Post-loop cleanup: we must unload the final error values into the
1217 * final fserrors[] entry. Note we need not unload belowerrN because
1218 * it is for the dummy column before or after the actual array.
1219 */
1220 errorptr[0] = (FSERROR) bpreverr0; /* unload prev errs into array */
1221 errorptr[1] = (FSERROR) bpreverr1;
1222 errorptr[2] = (FSERROR) bpreverr2;
1223 }
1224 }
1225
1226
1227 /*
1228 * Initialize the error-limiting transfer function (lookup table).
1229 * The raw F-S error computation can potentially compute error values of up to
1230 * +- MAXJSAMPLE. But we want the maximum correction applied to a pixel to be
1231 * much less, otherwise obviously wrong pixels will be created. (Typical
1232 * effects include weird fringes at color-area boundaries, isolated bright
1233 * pixels in a dark area, etc.) The standard advice for avoiding this problem
1234 * is to ensure that the "corners" of the color cube are allocated as output
1235 * colors; then repeated errors in the same direction cannot cause cascading
1236 * error buildup. However, that only prevents the error from getting
1237 * completely out of hand; Aaron Giles reports that error limiting improves
1238 * the results even with corner colors allocated.
1239 * A simple clamping of the error values to about +- MAXJSAMPLE/8 works pretty
1240 * well, but the smoother transfer function used below is even better. Thanks
1241 * to Aaron Giles for this idea.
1242 */
1243
1244 static void
1245 init_error_limit (j_decompress_ptr cinfo)
1246 /* Allocate and fill in the error_limiter table */
1247 {
1248 my_cquantize_ptr cquantize = (my_cquantize_ptr) cinfo->cquantize;
1249 int * table;
1250 int in, out;
1251
1252 table = (int *) malloc((MAXJSAMPLE*2+1) * sizeof(int));
1253 table += MAXJSAMPLE; /* so can index -MAXJSAMPLE .. +MAXJSAMPLE */
1254 cquantize->error_limiter = table;
1255
1256 #define STEPSIZE ((MAXJSAMPLE+1)/16)
1257 /* Map errors 1:1 up to +- MAXJSAMPLE/16 */
1258 out = 0;
1259 for (in = 0; in < STEPSIZE; in++, out++) {
1260 table[in] = out; table[-in] = -out;
1261 }
1262 /* Map errors 1:2 up to +- 3*MAXJSAMPLE/16 */
1263 for (; in < STEPSIZE*3; in++, out += (in&1) ? 0 : 1) {
1264 table[in] = out; table[-in] = -out;
1265 }
1266 /* Clamp the rest to final out value (which is (MAXJSAMPLE+1)/8) */
1267 for (; in <= MAXJSAMPLE; in++) {
1268 table[in] = out; table[-in] = -out;
1269 }
1270 #undef STEPSIZE
1271 }
1272
1273
1274 /*
1275 * Finish up at the end of each pass.
1276 */
1277
1278 void
1279 finish_pass1 (j_decompress_ptr cinfo)
1280 {
1281 my_cquantize_ptr cquantize = (my_cquantize_ptr) cinfo->cquantize;
1282
1283 /* Select the representative colors and fill in cinfo->colormap */
1284 cinfo->colormap = cquantize->sv_colormap;
1285 select_colors(cinfo, cquantize->desired);
1286 /* Force next pass to zero the color index table */
1287 cquantize->needs_zeroed = true;
1288 }
1289
1290
1291 void
1292 finish_pass2 (j_decompress_ptr WXUNUSED(cinfo))
1293 {
1294 /* no work */
1295 }
1296
1297
1298 /*
1299 * Initialize for each processing pass.
1300 */
1301
1302 void
1303 start_pass_2_quant (j_decompress_ptr cinfo, bool is_pre_scan)
1304 {
1305 my_cquantize_ptr cquantize = (my_cquantize_ptr) cinfo->cquantize;
1306 hist3d histogram = cquantize->histogram;
1307
1308 if (is_pre_scan) {
1309 /* Set up method pointers */
1310 cquantize->pub.color_quantize = prescan_quantize;
1311 cquantize->pub.finish_pass = finish_pass1;
1312 cquantize->needs_zeroed = true; /* Always zero histogram */
1313 } else {
1314 /* Set up method pointers */
1315 cquantize->pub.color_quantize = pass2_fs_dither;
1316 cquantize->pub.finish_pass = finish_pass2;
1317
1318 {
1319 size_t arraysize = (size_t) ((cinfo->output_width + 2) *
1320 (3 * sizeof(FSERROR)));
1321 /* Allocate Floyd-Steinberg workspace if we didn't already. */
1322 if (cquantize->fserrors == NULL)
1323 cquantize->fserrors = (INT16*) malloc(arraysize);
1324 /* Initialize the propagated errors to zero. */
1325 memset((void *) cquantize->fserrors, 0, arraysize);
1326 /* Make the error-limit table if we didn't already. */
1327 if (cquantize->error_limiter == NULL)
1328 init_error_limit(cinfo);
1329 cquantize->on_odd_row = false;
1330 }
1331
1332 }
1333 /* Zero the histogram or inverse color map, if necessary */
1334 if (cquantize->needs_zeroed) {
1335 for (int i = 0; i < HIST_C0_ELEMS; i++) {
1336 memset((void *) histogram[i], 0,
1337 HIST_C1_ELEMS*HIST_C2_ELEMS * sizeof(histcell));
1338 }
1339 cquantize->needs_zeroed = false;
1340 }
1341 }
1342
1343
1344 /*
1345 * Switch to a new external colormap between output passes.
1346 */
1347
1348 void
1349 new_color_map_2_quant (j_decompress_ptr cinfo)
1350 {
1351 my_cquantize_ptr cquantize = (my_cquantize_ptr) cinfo->cquantize;
1352
1353 /* Reset the inverse color map */
1354 cquantize->needs_zeroed = true;
1355 }
1356
1357
1358 /*
1359 * Module initialization routine for 2-pass color quantization.
1360 */
1361
1362 void
1363 jinit_2pass_quantizer (j_decompress_ptr cinfo)
1364 {
1365 my_cquantize_ptr cquantize;
1366 int i;
1367
1368 cquantize = (my_cquantize_ptr) malloc(sizeof(my_cquantizer));
1369 cinfo->cquantize = (jpeg_color_quantizer *) cquantize;
1370 cquantize->pub.start_pass = start_pass_2_quant;
1371 cquantize->pub.new_color_map = new_color_map_2_quant;
1372 cquantize->fserrors = NULL; /* flag optional arrays not allocated */
1373 cquantize->error_limiter = NULL;
1374
1375
1376 /* Allocate the histogram/inverse colormap storage */
1377 cquantize->histogram = (hist3d) malloc(HIST_C0_ELEMS * sizeof(hist2d));
1378 for (i = 0; i < HIST_C0_ELEMS; i++) {
1379 cquantize->histogram[i] = (hist2d) malloc(HIST_C1_ELEMS*HIST_C2_ELEMS * sizeof(histcell));
1380 }
1381 cquantize->needs_zeroed = true; /* histogram is garbage now */
1382
1383 /* Allocate storage for the completed colormap, if required.
1384 * We do this now since it is storage and may affect
1385 * the memory manager's space calculations.
1386 */
1387 {
1388 /* Make sure color count is acceptable */
1389 int desired = cinfo->desired_number_of_colors;
1390
1391 cquantize->sv_colormap = (JSAMPARRAY) malloc(sizeof(JSAMPROW) * 3);
1392 cquantize->sv_colormap[0] = (JSAMPROW) malloc(sizeof(JSAMPLE) * desired);
1393 cquantize->sv_colormap[1] = (JSAMPROW) malloc(sizeof(JSAMPLE) * desired);
1394 cquantize->sv_colormap[2] = (JSAMPROW) malloc(sizeof(JSAMPLE) * desired);
1395
1396 cquantize->desired = desired;
1397 }
1398
1399 /* Allocate Floyd-Steinberg workspace if necessary.
1400 * This isn't really needed until pass 2, but again it is storage.
1401 * Although we will cope with a later change in dither_mode,
1402 * we do not promise to honor max_memory_to_use if dither_mode changes.
1403 */
1404 {
1405 cquantize->fserrors = (FSERRPTR) malloc(
1406 (size_t) ((cinfo->output_width + 2) * (3 * sizeof(FSERROR))));
1407 /* Might as well create the error-limiting table too. */
1408 init_error_limit(cinfo);
1409 }
1410 }
1411
1412
1413
1414
1415
1416
1417
1418
1419
1420
1421 void
1422 prepare_range_limit_table (j_decompress_ptr cinfo)
1423 /* Allocate and fill in the sample_range_limit table */
1424 {
1425 JSAMPLE * table;
1426 int i;
1427
1428 table = (JSAMPLE *) malloc((5 * (MAXJSAMPLE+1) + CENTERJSAMPLE) * sizeof(JSAMPLE));
1429 cinfo->srl_orig = table;
1430 table += (MAXJSAMPLE+1); /* allow negative subscripts of simple table */
1431 cinfo->sample_range_limit = table;
1432 /* First segment of "simple" table: limit[x] = 0 for x < 0 */
1433 memset(table - (MAXJSAMPLE+1), 0, (MAXJSAMPLE+1) * sizeof(JSAMPLE));
1434 /* Main part of "simple" table: limit[x] = x */
1435 for (i = 0; i <= MAXJSAMPLE; i++)
1436 table[i] = (JSAMPLE) i;
1437 table += CENTERJSAMPLE; /* Point to where post-IDCT table starts */
1438 /* End of simple table, rest of first half of post-IDCT table */
1439 for (i = CENTERJSAMPLE; i < 2*(MAXJSAMPLE+1); i++)
1440 table[i] = MAXJSAMPLE;
1441 /* Second half of post-IDCT table */
1442 memset(table + (2 * (MAXJSAMPLE+1)), 0,
1443 (2 * (MAXJSAMPLE+1) - CENTERJSAMPLE) * sizeof(JSAMPLE));
1444 memcpy(table + (4 * (MAXJSAMPLE+1) - CENTERJSAMPLE),
1445 cinfo->sample_range_limit, CENTERJSAMPLE * sizeof(JSAMPLE));
1446 }
1447
1448
1449
1450
1451 /*
1452 * wxQuantize
1453 */
1454
1455 IMPLEMENT_DYNAMIC_CLASS(wxQuantize, wxObject)
1456
1457 void wxQuantize::DoQuantize(unsigned w, unsigned h, unsigned char **in_rows, unsigned char **out_rows,
1458 unsigned char *palette, int desiredNoColours)
1459 {
1460 j_decompress dec;
1461 my_cquantize_ptr cquantize;
1462
1463 dec.output_width = w;
1464 dec.desired_number_of_colors = desiredNoColours;
1465 prepare_range_limit_table(&dec);
1466 jinit_2pass_quantizer(&dec);
1467 cquantize = (my_cquantize_ptr) dec.cquantize;
1468
1469
1470 cquantize->pub.start_pass(&dec, true);
1471 cquantize->pub.color_quantize(&dec, in_rows, out_rows, h);
1472 cquantize->pub.finish_pass(&dec);
1473
1474 cquantize->pub.start_pass(&dec, false);
1475 cquantize->pub.color_quantize(&dec, in_rows, out_rows, h);
1476 cquantize->pub.finish_pass(&dec);
1477
1478
1479 for (int i = 0; i < dec.desired_number_of_colors; i++) {
1480 palette[3 * i + 0] = dec.colormap[0][i];
1481 palette[3 * i + 1] = dec.colormap[1][i];
1482 palette[3 * i + 2] = dec.colormap[2][i];
1483 }
1484
1485 for (int ii = 0; ii < HIST_C0_ELEMS; ii++) free(cquantize->histogram[ii]);
1486 free(cquantize->histogram);
1487 free(dec.colormap[0]);
1488 free(dec.colormap[1]);
1489 free(dec.colormap[2]);
1490 free(dec.colormap);
1491 free(dec.srl_orig);
1492
1493 //free(cquantize->error_limiter);
1494 free((void*)(cquantize->error_limiter - MAXJSAMPLE)); // To reverse what was done to it
1495
1496 free(cquantize->fserrors);
1497 free(cquantize);
1498 }
1499
1500 // TODO: somehow make use of the Windows system colours, rather than ignoring them for the
1501 // purposes of quantization.
1502
1503 bool wxQuantize::Quantize(const wxImage& src, wxImage& dest,
1504 wxPalette** pPalette,
1505 int desiredNoColours,
1506 unsigned char** eightBitData,
1507 int flags)
1508
1509 {
1510 int i;
1511
1512 int windowsSystemColourCount = 20;
1513
1514 int paletteShift = 0;
1515
1516 // Shift the palette up by the number of Windows system colours,
1517 // if necessary
1518 if (flags & wxQUANTIZE_INCLUDE_WINDOWS_COLOURS)
1519 paletteShift = windowsSystemColourCount;
1520
1521 // Make room for the Windows system colours
1522 #ifdef __WXMSW__
1523 if ((flags & wxQUANTIZE_INCLUDE_WINDOWS_COLOURS) && (desiredNoColours > (256 - windowsSystemColourCount)))
1524 desiredNoColours = 256 - windowsSystemColourCount;
1525 #endif
1526
1527 // create rows info:
1528 int h = src.GetHeight();
1529 int w = src.GetWidth();
1530 unsigned char **rows = new unsigned char *[h];
1531 unsigned char *imgdt = src.GetData();
1532 for (i = 0; i < h; i++)
1533 rows[i] = imgdt + 3/*RGB*/ * w * i;
1534
1535 unsigned char palette[3*256];
1536
1537 // This is the image as represented by palette indexes.
1538 unsigned char *data8bit = new unsigned char[w * h];
1539 unsigned char **outrows = new unsigned char *[h];
1540 for (i = 0; i < h; i++)
1541 outrows[i] = data8bit + w * i;
1542
1543 //RGB->palette
1544 DoQuantize(w, h, rows, outrows, palette, desiredNoColours);
1545
1546 delete[] rows;
1547 delete[] outrows;
1548
1549 // palette->RGB(max.256)
1550
1551 if (flags & wxQUANTIZE_FILL_DESTINATION_IMAGE)
1552 {
1553 if (!dest.Ok())
1554 dest.Create(w, h);
1555
1556 imgdt = dest.GetData();
1557 for (i = 0; i < w * h; i++)
1558 {
1559 unsigned char c = data8bit[i];
1560 imgdt[3 * i + 0/*R*/] = palette[3 * c + 0];
1561 imgdt[3 * i + 1/*G*/] = palette[3 * c + 1];
1562 imgdt[3 * i + 2/*B*/] = palette[3 * c + 2];
1563 }
1564 }
1565
1566 if (eightBitData && (flags & wxQUANTIZE_RETURN_8BIT_DATA))
1567 {
1568 #ifdef __WXMSW__
1569 if (flags & wxQUANTIZE_INCLUDE_WINDOWS_COLOURS)
1570 {
1571 // We need to shift the palette entries up
1572 // to make room for the Windows system colours.
1573 for (i = 0; i < w * h; i++)
1574 data8bit[i] = (unsigned char)(data8bit[i] + paletteShift);
1575 }
1576 #endif
1577 *eightBitData = data8bit;
1578 }
1579 else
1580 delete[] data8bit;
1581
1582 #if wxUSE_PALETTE
1583 // Make a wxWidgets palette
1584 if (pPalette)
1585 {
1586 unsigned char* r = new unsigned char[256];
1587 unsigned char* g = new unsigned char[256];
1588 unsigned char* b = new unsigned char[256];
1589
1590 #ifdef __WXMSW__
1591 // Fill the first 20 entries with Windows system colours
1592 if (flags & wxQUANTIZE_INCLUDE_WINDOWS_COLOURS)
1593 {
1594 HDC hDC = ::GetDC(NULL);
1595 PALETTEENTRY* entries = new PALETTEENTRY[windowsSystemColourCount];
1596 ::GetSystemPaletteEntries(hDC, 0, windowsSystemColourCount, entries);
1597 ::ReleaseDC(NULL, hDC);
1598
1599 for (i = 0; i < windowsSystemColourCount; i++)
1600 {
1601 r[i] = entries[i].peRed;
1602 g[i] = entries[i].peGreen;
1603 b[i] = entries[i].peBlue;
1604 }
1605 delete[] entries;
1606 }
1607 #endif
1608
1609 for (i = 0; i < desiredNoColours; i++)
1610 {
1611 r[i+paletteShift] = palette[i*3 + 0];
1612 g[i+paletteShift] = palette[i*3 + 1];
1613 b[i+paletteShift] = palette[i*3 + 2];
1614 }
1615
1616 // Blank out any remaining palette entries
1617 for (i = desiredNoColours+paletteShift; i < 256; i++)
1618 {
1619 r[i] = 0;
1620 g[i] = 0;
1621 b[i] = 0;
1622 }
1623 *pPalette = new wxPalette(256, r, g, b);
1624 delete[] r;
1625 delete[] g;
1626 delete[] b;
1627 }
1628 #endif // wxUSE_PALETTE
1629
1630 return true;
1631 }
1632
1633 // This version sets a palette in the destination image so you don't
1634 // have to manage it yourself.
1635
1636 bool wxQuantize::Quantize(const wxImage& src,
1637 wxImage& dest,
1638 int desiredNoColours,
1639 unsigned char** eightBitData,
1640 int flags)
1641 {
1642 wxPalette* palette = NULL;
1643 if ( !Quantize(src, dest, & palette, desiredNoColours, eightBitData, flags) )
1644 return false;
1645
1646 #if wxUSE_PALETTE
1647 if (palette)
1648 {
1649 dest.SetPalette(* palette);
1650 delete palette;
1651 }
1652 #endif // wxUSE_PALETTE
1653
1654 return true;
1655 }
1656
1657 #endif
1658 // wxUSE_IMAGE
1659