Annotation of embedaddon/php/ext/gd/libgd/gd_topal.c, revision 1.1.1.1
1.1 misho 1: /* TODO: oim and nim in the lower level functions;
2: correct use of stub (sigh). */
3:
4: /* 2.0.12: a new adaptation from the same original, this time
5: by Barend Gehrels. My attempt to incorporate alpha channel
6: into the result worked poorly and degraded the quality of
7: palette conversion even when the source contained no
8: alpha channel data. This version does not attempt to produce
9: an output file with transparency in some of the palette
10: indexes, which, in practice, doesn't look so hot anyway. TBB */
11:
12: /*
13: * gd_topal, adapted from 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: #ifdef ORIGINAL_LIB_JPEG
32:
33: #define JPEG_INTERNALS
34:
35: #include "jinclude.h"
36: #include "jpeglib.h"
37:
38: #else
39:
40: /*
41: * THOMAS BOUTELL & BAREND GEHRELS, february 2003
42: * adapted the code to work within gd rather than within libjpeg.
43: * If it is not working, it's not Thomas G. Lane's fault.
44: */
45:
46: /*
47: SETTING THIS ONE CAUSES STRIPED IMAGE
48: to be done: solve this
49: #define ORIGINAL_LIB_JPEG_REVERSE_ODD_ROWS
50: */
51:
52: #include <string.h>
53: #include "gd.h"
54: #include "gdhelpers.h"
55:
56: /* (Re)define some defines known by libjpeg */
57: #define QUANT_2PASS_SUPPORTED
58:
59: #define RGB_RED 0
60: #define RGB_GREEN 1
61: #define RGB_BLUE 2
62:
63: #define JSAMPLE unsigned char
64: #define MAXJSAMPLE (gdMaxColors-1)
65: #define BITS_IN_JSAMPLE 8
66:
67: #define JSAMPROW int*
68: #define JDIMENSION int
69:
70: #define METHODDEF(type) static type
71: #define LOCAL(type) static type
72:
73:
74: /* We assume that right shift corresponds to signed division by 2 with
75: * rounding towards minus infinity. This is correct for typical "arithmetic
76: * shift" instructions that shift in copies of the sign bit. But some
77: * C compilers implement >> with an unsigned shift. For these machines you
78: * must define RIGHT_SHIFT_IS_UNSIGNED.
79: * RIGHT_SHIFT provides a proper signed right shift of an INT32 quantity.
80: * It is only applied with constant shift counts. SHIFT_TEMPS must be
81: * included in the variables of any routine using RIGHT_SHIFT.
82: */
83:
84: #ifdef RIGHT_SHIFT_IS_UNSIGNED
85: #define SHIFT_TEMPS INT32 shift_temp;
86: #define RIGHT_SHIFT(x,shft) \
87: ((shift_temp = (x)) < 0 ? \
88: (shift_temp >> (shft)) | ((~((INT32) 0)) << (32-(shft))) : \
89: (shift_temp >> (shft)))
90: #else
91: #define SHIFT_TEMPS
92: #define RIGHT_SHIFT(x,shft) ((x) >> (shft))
93: #endif
94:
95:
96: #define range_limit(x) { if(x<0) x=0; if (x>255) x=255; }
97:
98:
99: #ifndef INT16
100: #define INT16 short
101: #endif
102:
103: #ifndef UINT16
104: #define UINT16 unsigned short
105: #endif
106:
107: #ifndef INT32
108: #define INT32 int
109: #endif
110:
111: #ifndef FAR
112: #define FAR
113: #endif
114:
115:
116:
117: #ifndef boolean
118: #define boolean int
119: #endif
120:
121: #ifndef TRUE
122: #define TRUE 1
123: #endif
124:
125: #ifndef FALSE
126: #define FALSE 0
127: #endif
128:
129:
130: #define input_buf (oim->tpixels)
131: #define output_buf (nim->pixels)
132:
133: #endif
134:
135: #ifdef QUANT_2PASS_SUPPORTED
136:
137:
138: /*
139: * This module implements the well-known Heckbert paradigm for color
140: * quantization. Most of the ideas used here can be traced back to
141: * Heckbert's seminal paper
142: * Heckbert, Paul. "Color Image Quantization for Frame Buffer Display",
143: * Proc. SIGGRAPH '82, Computer Graphics v.16 #3 (July 1982), pp 297-304.
144: *
145: * In the first pass over the image, we accumulate a histogram showing the
146: * usage count of each possible color. To keep the histogram to a reasonable
147: * size, we reduce the precision of the input; typical practice is to retain
148: * 5 or 6 bits per color, so that 8 or 4 different input values are counted
149: * in the same histogram cell.
150: *
151: * Next, the color-selection step begins with a box representing the whole
152: * color space, and repeatedly splits the "largest" remaining box until we
153: * have as many boxes as desired colors. Then the mean color in each
154: * remaining box becomes one of the possible output colors.
155: *
156: * The second pass over the image maps each input pixel to the closest output
157: * color (optionally after applying a Floyd-Steinberg dithering correction).
158: * This mapping is logically trivial, but making it go fast enough requires
159: * considerable care.
160: *
161: * Heckbert-style quantizers vary a good deal in their policies for choosing
162: * the "largest" box and deciding where to cut it. The particular policies
163: * used here have proved out well in experimental comparisons, but better ones
164: * may yet be found.
165: *
166: * In earlier versions of the IJG code, this module quantized in YCbCr color
167: * space, processing the raw upsampled data without a color conversion step.
168: * This allowed the color conversion math to be done only once per colormap
169: * entry, not once per pixel. However, that optimization precluded other
170: * useful optimizations (such as merging color conversion with upsampling)
171: * and it also interfered with desired capabilities such as quantizing to an
172: * externally-supplied colormap. We have therefore abandoned that approach.
173: * The present code works in the post-conversion color space, typically RGB.
174: *
175: * To improve the visual quality of the results, we actually work in scaled
176: * RGB space, giving G distances more weight than R, and R in turn more than
177: * B. To do everything in integer math, we must use integer scale factors.
178: * The 2/3/1 scale factors used here correspond loosely to the relative
179: * weights of the colors in the NTSC grayscale equation.
180: * If you want to use this code to quantize a non-RGB color space, you'll
181: * probably need to change these scale factors.
182: */
183:
184: #define R_SCALE 2 /* scale R distances by this much */
185: #define G_SCALE 3 /* scale G distances by this much */
186: #define B_SCALE 1 /* and B by this much */
187:
188: /* Relabel R/G/B as components 0/1/2, respecting the RGB ordering defined
189: * in jmorecfg.h. As the code stands, it will do the right thing for R,G,B
190: * and B,G,R orders. If you define some other weird order in jmorecfg.h,
191: * you'll get compile errors until you extend this logic. In that case
192: * you'll probably want to tweak the histogram sizes too.
193: */
194:
195: #if RGB_RED == 0
196: #define C0_SCALE R_SCALE
197: #endif
198: #if RGB_BLUE == 0
199: #define C0_SCALE B_SCALE
200: #endif
201: #if RGB_GREEN == 1
202: #define C1_SCALE G_SCALE
203: #endif
204: #if RGB_RED == 2
205: #define C2_SCALE R_SCALE
206: #endif
207: #if RGB_BLUE == 2
208: #define C2_SCALE B_SCALE
209: #endif
210:
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 FAR *histptr; /* for pointers to histogram cells */
261:
262: typedef histcell hist1d[HIST_C2_ELEMS]; /* typedefs for the array */
263: typedef hist1d FAR *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 FAR *FSERRPTR; /* pointer to error array (in FAR storage!) */
300:
301:
302: /* Private subobject */
303:
304: typedef struct
305: {
306: #ifdef ORIGINAL_LIB_JPEG
307: struct jpeg_color_quantizer pub; /* public fields */
308:
309: /* Space for the eventually created colormap is stashed here */
310: JSAMPARRAY sv_colormap; /* colormap allocated at init time */
311: int desired; /* desired # of colors = size of colormap */
312: boolean needs_zeroed; /* TRUE if next pass must zero histogram */
313: #endif
314:
315: /* Variables for accumulating image statistics */
316: hist3d histogram; /* pointer to the histogram */
317:
318:
319: /* Variables for Floyd-Steinberg dithering */
320: FSERRPTR fserrors; /* accumulated errors */
321:
322: boolean on_odd_row; /* flag to remember which row we are on */
323: int *error_limiter; /* table for clamping the applied error */
324: #ifndef ORIGINAL_LIB_JPEG
325: int *error_limiter_storage; /* gdMalloc'd storage for the above */
326: #endif
327: }
328: my_cquantizer;
329:
330: typedef my_cquantizer *my_cquantize_ptr;
331:
332:
333: /*
334: * Prescan some rows of pixels.
335: * In this module the prescan simply updates the histogram, which has been
336: * initialized to zeroes by start_pass.
337: * An output_buf parameter is required by the method signature, but no data
338: * is actually output (in fact the buffer controller is probably passing a
339: * NULL pointer).
340: */
341:
342: METHODDEF (void)
343: #ifndef ORIGINAL_LIB_JPEG
344: prescan_quantize (gdImagePtr oim, gdImagePtr nim, my_cquantize_ptr cquantize)
345: {
346: #else
347: prescan_quantize (j_decompress_ptr cinfo, JSAMPARRAY input_buf,
348: JSAMPARRAY output_buf, int num_rows)
349: {
350: my_cquantize_ptr cquantize = (my_cquantize_ptr) cinfo->cquantize;
351: #endif
352: register JSAMPROW ptr;
353: register histptr histp;
354: register hist3d histogram = cquantize->histogram;
355: int row;
356: JDIMENSION col;
357: #ifdef ORIGINAL_LIB_JPEG
358: JDIMENSION width = cinfo->output_width;
359: #else
360: int width = oim->sx;
361: int num_rows = oim->sy;
362: #endif
363:
364: for (row = 0; row < num_rows; row++)
365: {
366: ptr = input_buf[row];
367: for (col = width; col > 0; col--)
368: {
369: #ifdef ORIGINAL_LIB_JPEG
370: int r = GETJSAMPLE (ptr[0]) >> C0_SHIFT;
371: int g = GETJSAMPLE (ptr[1]) >> C1_SHIFT;
372: int b = GETJSAMPLE (ptr[2]) >> C2_SHIFT;
373: #else
374: int r = gdTrueColorGetRed (*ptr) >> C0_SHIFT;
375: int g = gdTrueColorGetGreen (*ptr) >> C1_SHIFT;
376: int b = gdTrueColorGetBlue (*ptr) >> C2_SHIFT;
377: /* 2.0.12: Steven Brown: support a single totally transparent
378: color in the original. */
379: if ((oim->transparent >= 0) && (*ptr == oim->transparent))
380: {
381: ptr++;
382: continue;
383: }
384: #endif
385: /* get pixel value and index into the histogram */
386: histp = &histogram[r][g][b];
387: /* increment, check for overflow and undo increment if so. */
388: if (++(*histp) == 0)
389: (*histp)--;
390: #ifdef ORIGINAL_LIB_JPEG
391: ptr += 3;
392: #else
393: ptr++;
394: #endif
395: }
396: }
397: }
398:
399:
400: /*
401: * Next we have the really interesting routines: selection of a colormap
402: * given the completed histogram.
403: * These routines work with a list of "boxes", each representing a rectangular
404: * subset of the input color space (to histogram precision).
405: */
406:
407: typedef struct
408: {
409: /* The bounds of the box (inclusive); expressed as histogram indexes */
410: int c0min, c0max;
411: int c1min, c1max;
412: int c2min, c2max;
413: /* The volume (actually 2-norm) of the box */
414: INT32 volume;
415: /* The number of nonzero histogram cells within this box */
416: long colorcount;
417: }
418: box;
419:
420: typedef box *boxptr;
421:
422:
423: LOCAL (boxptr) find_biggest_color_pop (boxptr boxlist, int numboxes)
424: /* Find the splittable box with the largest color population */
425: /* Returns NULL if no splittable boxes remain */
426: {
427: register boxptr boxp;
428: register int i;
429: register long maxc = 0;
430: boxptr which = NULL;
431:
432: for (i = 0, boxp = boxlist; i < numboxes; i++, boxp++)
433: {
434: if (boxp->colorcount > maxc && boxp->volume > 0)
435: {
436: which = boxp;
437: maxc = boxp->colorcount;
438: }
439: }
440: return which;
441: }
442:
443:
444: LOCAL (boxptr) find_biggest_volume (boxptr boxlist, int numboxes)
445: /* Find the splittable box with the largest (scaled) volume */
446: /* Returns NULL if no splittable boxes remain */
447: {
448: register boxptr boxp;
449: register int i;
450: register INT32 maxv = 0;
451: boxptr which = NULL;
452:
453: for (i = 0, boxp = boxlist; i < numboxes; i++, boxp++)
454: {
455: if (boxp->volume > maxv)
456: {
457: which = boxp;
458: maxv = boxp->volume;
459: }
460: }
461: return which;
462: }
463:
464:
465: LOCAL (void)
466: #ifndef ORIGINAL_LIB_JPEG
467: update_box (gdImagePtr oim, gdImagePtr nim, my_cquantize_ptr cquantize, boxptr boxp)
468: {
469: #else
470: update_box (j_decompress_ptr cinfo, boxptr boxp)
471: /* Shrink the min/max bounds of a box to enclose only nonzero elements, */
472: /* and recompute its volume and population */
473: {
474: my_cquantize_ptr cquantize = (my_cquantize_ptr) cinfo->cquantize;
475: #endif
476: hist3d histogram = cquantize->histogram;
477: histptr histp;
478: int c0, c1, c2;
479: int c0min, c0max, c1min, c1max, c2min, c2max;
480: INT32 dist0, dist1, dist2;
481: long ccount;
482:
483: c0min = boxp->c0min;
484: c0max = boxp->c0max;
485: c1min = boxp->c1min;
486: c1max = boxp->c1max;
487: c2min = boxp->c2min;
488: c2max = boxp->c2max;
489:
490: if (c0max > c0min)
491: for (c0 = c0min; c0 <= c0max; c0++)
492: for (c1 = c1min; c1 <= c1max; c1++)
493: {
494: histp = &histogram[c0][c1][c2min];
495: for (c2 = c2min; c2 <= c2max; c2++)
496: if (*histp++ != 0)
497: {
498: boxp->c0min = c0min = c0;
499: goto have_c0min;
500: }
501: }
502: have_c0min:
503: if (c0max > c0min)
504: for (c0 = c0max; c0 >= c0min; c0--)
505: for (c1 = c1min; c1 <= c1max; c1++)
506: {
507: histp = &histogram[c0][c1][c2min];
508: for (c2 = c2min; c2 <= c2max; c2++)
509: if (*histp++ != 0)
510: {
511: boxp->c0max = c0max = c0;
512: goto have_c0max;
513: }
514: }
515: have_c0max:
516: if (c1max > c1min)
517: for (c1 = c1min; c1 <= c1max; c1++)
518: for (c0 = c0min; c0 <= c0max; c0++)
519: {
520: histp = &histogram[c0][c1][c2min];
521: for (c2 = c2min; c2 <= c2max; c2++)
522: if (*histp++ != 0)
523: {
524: boxp->c1min = c1min = c1;
525: goto have_c1min;
526: }
527: }
528: have_c1min:
529: if (c1max > c1min)
530: for (c1 = c1max; c1 >= c1min; c1--)
531: for (c0 = c0min; c0 <= c0max; c0++)
532: {
533: histp = &histogram[c0][c1][c2min];
534: for (c2 = c2min; c2 <= c2max; c2++)
535: if (*histp++ != 0)
536: {
537: boxp->c1max = c1max = c1;
538: goto have_c1max;
539: }
540: }
541: have_c1max:
542: if (c2max > c2min)
543: for (c2 = c2min; c2 <= c2max; c2++)
544: for (c0 = c0min; c0 <= c0max; c0++)
545: {
546: histp = &histogram[c0][c1min][c2];
547: for (c1 = c1min; c1 <= c1max; c1++, histp += HIST_C2_ELEMS)
548: if (*histp != 0)
549: {
550: boxp->c2min = c2min = c2;
551: goto have_c2min;
552: }
553: }
554: have_c2min:
555: if (c2max > c2min)
556: for (c2 = c2max; c2 >= c2min; c2--)
557: for (c0 = c0min; c0 <= c0max; c0++)
558: {
559: histp = &histogram[c0][c1min][c2];
560: for (c1 = c1min; c1 <= c1max; c1++, histp += HIST_C2_ELEMS)
561: if (*histp != 0)
562: {
563: boxp->c2max = c2max = c2;
564: goto have_c2max;
565: }
566: }
567: have_c2max:
568:
569: /* Update box volume.
570: * We use 2-norm rather than real volume here; this biases the method
571: * against making long narrow boxes, and it has the side benefit that
572: * a box is splittable iff norm > 0.
573: * Since the differences are expressed in histogram-cell units,
574: * we have to shift back to JSAMPLE units to get consistent distances;
575: * after which, we scale according to the selected distance scale factors.
576: */
577: dist0 = ((c0max - c0min) << C0_SHIFT) * C0_SCALE;
578: dist1 = ((c1max - c1min) << C1_SHIFT) * C1_SCALE;
579: dist2 = ((c2max - c2min) << C2_SHIFT) * C2_SCALE;
580: boxp->volume = dist0 * dist0 + dist1 * dist1 + dist2 * dist2;
581:
582: /* Now scan remaining volume of box and compute population */
583: ccount = 0;
584: for (c0 = c0min; c0 <= c0max; c0++)
585: for (c1 = c1min; c1 <= c1max; c1++)
586: {
587: histp = &histogram[c0][c1][c2min];
588: for (c2 = c2min; c2 <= c2max; c2++, histp++)
589: if (*histp != 0)
590: {
591: ccount++;
592: }
593: }
594: boxp->colorcount = ccount;
595: }
596:
597:
598: LOCAL (int)
599: #ifdef ORIGINAL_LIB_JPEG
600: median_cut (j_decompress_ptr cinfo, boxptr boxlist, int numboxes,
601: int desired_colors)
602: #else
603: median_cut (gdImagePtr oim, gdImagePtr nim, my_cquantize_ptr cquantize,
604: boxptr boxlist, int numboxes, int desired_colors)
605: #endif
606: /* Repeatedly select and split the largest box until we have enough boxes */
607: {
608: int n, lb;
609: int c0, c1, c2, cmax;
610: register boxptr b1, b2;
611:
612: while (numboxes < desired_colors)
613: {
614: /* Select box to split.
615: * Current algorithm: by population for first half, then by volume.
616: */
617: if (numboxes * 2 <= desired_colors)
618: {
619: b1 = find_biggest_color_pop (boxlist, numboxes);
620: }
621: else
622: {
623: b1 = find_biggest_volume (boxlist, numboxes);
624: }
625: if (b1 == NULL) /* no splittable boxes left! */
626: break;
627: b2 = &boxlist[numboxes]; /* where new box will go */
628: /* Copy the color bounds to the new box. */
629: b2->c0max = b1->c0max;
630: b2->c1max = b1->c1max;
631: b2->c2max = b1->c2max;
632: b2->c0min = b1->c0min;
633: b2->c1min = b1->c1min;
634: b2->c2min = b1->c2min;
635: /* Choose which axis to split the box on.
636: * Current algorithm: longest scaled axis.
637: * See notes in update_box about scaling distances.
638: */
639: c0 = ((b1->c0max - b1->c0min) << C0_SHIFT) * C0_SCALE;
640: c1 = ((b1->c1max - b1->c1min) << C1_SHIFT) * C1_SCALE;
641: c2 = ((b1->c2max - b1->c2min) << C2_SHIFT) * C2_SCALE;
642: /* We want to break any ties in favor of green, then red, blue last.
643: * This code does the right thing for R,G,B or B,G,R color orders only.
644: */
645: #if RGB_RED == 0
646: cmax = c1;
647: n = 1;
648: if (c0 > cmax)
649: {
650: cmax = c0;
651: n = 0;
652: }
653: if (c2 > cmax)
654: {
655: n = 2;
656: }
657: #else
658: cmax = c1;
659: n = 1;
660: if (c2 > cmax)
661: {
662: cmax = c2;
663: n = 2;
664: }
665: if (c0 > cmax)
666: {
667: n = 0;
668: }
669: #endif
670: /* Choose split point along selected axis, and update box bounds.
671: * Current algorithm: split at halfway point.
672: * (Since the box has been shrunk to minimum volume,
673: * any split will produce two nonempty subboxes.)
674: * Note that lb value is max for lower box, so must be < old max.
675: */
676: switch (n)
677: {
678: case 0:
679: lb = (b1->c0max + b1->c0min) / 2;
680: b1->c0max = lb;
681: b2->c0min = lb + 1;
682: break;
683: case 1:
684: lb = (b1->c1max + b1->c1min) / 2;
685: b1->c1max = lb;
686: b2->c1min = lb + 1;
687: break;
688: case 2:
689: lb = (b1->c2max + b1->c2min) / 2;
690: b1->c2max = lb;
691: b2->c2min = lb + 1;
692: break;
693: }
694: /* Update stats for boxes */
695: #ifdef ORIGINAL_LIB_JPEG
696: update_box (cinfo, b1);
697: update_box (cinfo, b2);
698: #else
699: update_box (oim, nim, cquantize, b1);
700: update_box (oim, nim, cquantize, b2);
701: #endif
702: numboxes++;
703: }
704: return numboxes;
705: }
706:
707:
708: LOCAL (void)
709: #ifndef ORIGINAL_LIB_JPEG
710: compute_color (gdImagePtr oim, gdImagePtr nim, my_cquantize_ptr cquantize,
711: boxptr boxp, int icolor)
712: {
713: #else
714: compute_color (j_decompress_ptr cinfo, boxptr boxp, int icolor)
715: /* Compute representative color for a box, put it in colormap[icolor] */
716: {
717: /* Current algorithm: mean weighted by pixels (not colors) */
718: /* Note it is important to get the rounding correct! */
719: my_cquantize_ptr cquantize = (my_cquantize_ptr) cinfo->cquantize;
720: #endif
721: hist3d histogram = cquantize->histogram;
722: histptr histp;
723: int c0, c1, c2;
724: int c0min, c0max, c1min, c1max, c2min, c2max;
725: long count = 0; /* 2.0.28: = 0 */
726: long total = 0;
727: long c0total = 0;
728: long c1total = 0;
729: long c2total = 0;
730:
731: c0min = boxp->c0min;
732: c0max = boxp->c0max;
733: c1min = boxp->c1min;
734: c1max = boxp->c1max;
735: c2min = boxp->c2min;
736: c2max = boxp->c2max;
737:
738: for (c0 = c0min; c0 <= c0max; c0++)
739: for (c1 = c1min; c1 <= c1max; c1++)
740: {
741: histp = &histogram[c0][c1][c2min];
742: for (c2 = c2min; c2 <= c2max; c2++)
743: {
744: if ((count = *histp++) != 0)
745: {
746: total += count;
747: c0total +=
748: ((c0 << C0_SHIFT) + ((1 << C0_SHIFT) >> 1)) * count;
749: c1total +=
750: ((c1 << C1_SHIFT) + ((1 << C1_SHIFT) >> 1)) * count;
751: c2total +=
752: ((c2 << C2_SHIFT) + ((1 << C2_SHIFT) >> 1)) * count;
753: }
754: }
755: }
756:
757: #ifdef ORIGINAL_LIB_JPEG
758: cinfo->colormap[0][icolor] = (JSAMPLE) ((c0total + (total >> 1)) / total);
759: cinfo->colormap[1][icolor] = (JSAMPLE) ((c1total + (total >> 1)) / total);
760: cinfo->colormap[2][icolor] = (JSAMPLE) ((c2total + (total >> 1)) / total);
761: #else
762: /* 2.0.16: Paul den Dulk found an occasion where total can be 0 */
763: if (count)
764: {
765: nim->red[icolor] = (int) ((c0total + (total >> 1)) / total);
766: nim->green[icolor] = (int) ((c1total + (total >> 1)) / total);
767: nim->blue[icolor] = (int) ((c2total + (total >> 1)) / total);
768: }
769: else
770: {
771: nim->red[icolor] = 255;
772: nim->green[icolor] = 255;
773: nim->blue[icolor] = 255;
774: }
775: nim->open[icolor] = 0;
776: #endif
777: }
778:
779:
780: LOCAL (void)
781: #ifdef ORIGINAL_LIB_JPEG
782: select_colors (j_decompress_ptr cinfo, int desired_colors)
783: #else
784: select_colors (gdImagePtr oim, gdImagePtr nim, my_cquantize_ptr cquantize, int desired_colors)
785: #endif
786: /* Master routine for color selection */
787: {
788: boxptr boxlist;
789: int numboxes;
790: int i;
791:
792: /* Allocate workspace for box list */
793: #ifdef ORIGINAL_LIB_JPEG
794: boxlist = (boxptr) (*cinfo->mem->alloc_small)
795: ((j_common_ptr) cinfo, JPOOL_IMAGE, desired_colors * SIZEOF (box));
796: #else
797: boxlist = (boxptr) safe_emalloc(desired_colors, sizeof (box), 1);
798: #endif
799: /* Initialize one box containing whole space */
800: numboxes = 1;
801: boxlist[0].c0min = 0;
802: boxlist[0].c0max = MAXJSAMPLE >> C0_SHIFT;
803: boxlist[0].c1min = 0;
804: boxlist[0].c1max = MAXJSAMPLE >> C1_SHIFT;
805: boxlist[0].c2min = 0;
806: boxlist[0].c2max = MAXJSAMPLE >> C2_SHIFT;
807: #ifdef ORIGINAL_LIB_JPEG
808: /* Shrink it to actually-used volume and set its statistics */
809: update_box (cinfo, &boxlist[0]);
810: /* Perform median-cut to produce final box list */
811: numboxes = median_cut (cinfo, boxlist, numboxes, desired_colors);
812: /* Compute the representative color for each box, fill colormap */
813: for (i = 0; i < numboxes; i++)
814: compute_color (cinfo, &boxlist[i], i);
815: cinfo->actual_number_of_colors = numboxes;
816: TRACEMS1 (cinfo, 1, JTRC_QUANT_SELECTED, numboxes);
817: #else
818: /* Shrink it to actually-used volume and set its statistics */
819: update_box (oim, nim, cquantize, &boxlist[0]);
820: /* Perform median-cut to produce final box list */
821: numboxes = median_cut (oim, nim, cquantize, boxlist, numboxes, desired_colors);
822: /* Compute the representative color for each box, fill colormap */
823: for (i = 0; i < numboxes; i++)
824: compute_color (oim, nim, cquantize, &boxlist[i], i);
825: nim->colorsTotal = numboxes;
826:
827: /* If we had a pure transparency color, add it as the last palette entry.
828: * Skip incrementing the color count so that the dither / matching phase
829: * won't use it on pixels that shouldn't have been transparent. We'll
830: * increment it after all that finishes. */
831: if (oim->transparent >= 0)
832: {
833: /* Save the transparent color. */
834: nim->red[nim->colorsTotal] = gdTrueColorGetRed (oim->transparent);
835: nim->green[nim->colorsTotal] = gdTrueColorGetGreen (oim->transparent);
836: nim->blue[nim->colorsTotal] = gdTrueColorGetBlue (oim->transparent);
837: nim->alpha[nim->colorsTotal] = gdAlphaTransparent;
838: nim->open[nim->colorsTotal] = 0;
839: }
840:
841: gdFree (boxlist);
842: #endif
843: }
844:
845:
846: /*
847: * These routines are concerned with the time-critical task of mapping input
848: * colors to the nearest color in the selected colormap.
849: *
850: * We re-use the histogram space as an "inverse color map", essentially a
851: * cache for the results of nearest-color searches. All colors within a
852: * histogram cell will be mapped to the same colormap entry, namely the one
853: * closest to the cell's center. This may not be quite the closest entry to
854: * the actual input color, but it's almost as good. A zero in the cache
855: * indicates we haven't found the nearest color for that cell yet; the array
856: * is cleared to zeroes before starting the mapping pass. When we find the
857: * nearest color for a cell, its colormap index plus one is recorded in the
858: * cache for future use. The pass2 scanning routines call fill_inverse_cmap
859: * when they need to use an unfilled entry in the cache.
860: *
861: * Our method of efficiently finding nearest colors is based on the "locally
862: * sorted search" idea described by Heckbert and on the incremental distance
863: * calculation described by Spencer W. Thomas in chapter III.1 of Graphics
864: * Gems II (James Arvo, ed. Academic Press, 1991). Thomas points out that
865: * the distances from a given colormap entry to each cell of the histogram can
866: * be computed quickly using an incremental method: the differences between
867: * distances to adjacent cells themselves differ by a constant. This allows a
868: * fairly fast implementation of the "brute force" approach of computing the
869: * distance from every colormap entry to every histogram cell. Unfortunately,
870: * it needs a work array to hold the best-distance-so-far for each histogram
871: * cell (because the inner loop has to be over cells, not colormap entries).
872: * The work array elements have to be INT32s, so the work array would need
873: * 256Kb at our recommended precision. This is not feasible in DOS machines.
874: *
875: * To get around these problems, we apply Thomas' method to compute the
876: * nearest colors for only the cells within a small subbox of the histogram.
877: * The work array need be only as big as the subbox, so the memory usage
878: * problem is solved. Furthermore, we need not fill subboxes that are never
879: * referenced in pass2; many images use only part of the color gamut, so a
880: * fair amount of work is saved. An additional advantage of this
881: * approach is that we can apply Heckbert's locality criterion to quickly
882: * eliminate colormap entries that are far away from the subbox; typically
883: * three-fourths of the colormap entries are rejected by Heckbert's criterion,
884: * and we need not compute their distances to individual cells in the subbox.
885: * The speed of this approach is heavily influenced by the subbox size: too
886: * small means too much overhead, too big loses because Heckbert's criterion
887: * can't eliminate as many colormap entries. Empirically the best subbox
888: * size seems to be about 1/512th of the histogram (1/8th in each direction).
889: *
890: * Thomas' article also describes a refined method which is asymptotically
891: * faster than the brute-force method, but it is also far more complex and
892: * cannot efficiently be applied to small subboxes. It is therefore not
893: * useful for programs intended to be portable to DOS machines. On machines
894: * with plenty of memory, filling the whole histogram in one shot with Thomas'
895: * refined method might be faster than the present code --- but then again,
896: * it might not be any faster, and it's certainly more complicated.
897: */
898:
899:
900: /* log2(histogram cells in update box) for each axis; this can be adjusted */
901: #define BOX_C0_LOG (HIST_C0_BITS-3)
902: #define BOX_C1_LOG (HIST_C1_BITS-3)
903: #define BOX_C2_LOG (HIST_C2_BITS-3)
904:
905: #define BOX_C0_ELEMS (1<<BOX_C0_LOG) /* # of hist cells in update box */
906: #define BOX_C1_ELEMS (1<<BOX_C1_LOG)
907: #define BOX_C2_ELEMS (1<<BOX_C2_LOG)
908:
909: #define BOX_C0_SHIFT (C0_SHIFT + BOX_C0_LOG)
910: #define BOX_C1_SHIFT (C1_SHIFT + BOX_C1_LOG)
911: #define BOX_C2_SHIFT (C2_SHIFT + BOX_C2_LOG)
912:
913:
914: /*
915: * The next three routines implement inverse colormap filling. They could
916: * all be folded into one big routine, but splitting them up this way saves
917: * some stack space (the mindist[] and bestdist[] arrays need not coexist)
918: * and may allow some compilers to produce better code by registerizing more
919: * inner-loop variables.
920: */
921:
922: LOCAL (int)
923: find_nearby_colors (
924: #ifdef ORIGINAL_LIB_JPEG
925: j_decompress_ptr cinfo,
926: #else
927: gdImagePtr oim, gdImagePtr nim, my_cquantize_ptr cquantize,
928: #endif
929: int minc0, int minc1, int minc2, JSAMPLE colorlist[])
930: /* Locate the colormap entries close enough to an update box to be candidates
931: * for the nearest entry to some cell(s) in the update box. The update box
932: * is specified by the center coordinates of its first cell. The number of
933: * candidate colormap entries is returned, and their colormap indexes are
934: * placed in colorlist[].
935: * This routine uses Heckbert's "locally sorted search" criterion to select
936: * the colors that need further consideration.
937: */
938: {
939: #ifdef ORIGINAL_LIB_JPEG
940: int numcolors = cinfo->actual_number_of_colors;
941: #else
942: int numcolors = nim->colorsTotal;
943: #endif
944: int maxc0, maxc1, maxc2;
945: int centerc0, centerc1, centerc2;
946: int i, x, ncolors;
947: INT32 minmaxdist, min_dist, max_dist, tdist;
948: INT32 mindist[MAXNUMCOLORS]; /* min distance to colormap entry i */
949:
950: /* Compute true coordinates of update box's upper corner and center.
951: * Actually we compute the coordinates of the center of the upper-corner
952: * histogram cell, which are the upper bounds of the volume we care about.
953: * Note that since ">>" rounds down, the "center" values may be closer to
954: * min than to max; hence comparisons to them must be "<=", not "<".
955: */
956: maxc0 = minc0 + ((1 << BOX_C0_SHIFT) - (1 << C0_SHIFT));
957: centerc0 = (minc0 + maxc0) >> 1;
958: maxc1 = minc1 + ((1 << BOX_C1_SHIFT) - (1 << C1_SHIFT));
959: centerc1 = (minc1 + maxc1) >> 1;
960: maxc2 = minc2 + ((1 << BOX_C2_SHIFT) - (1 << C2_SHIFT));
961: centerc2 = (minc2 + maxc2) >> 1;
962:
963: /* For each color in colormap, find:
964: * 1. its minimum squared-distance to any point in the update box
965: * (zero if color is within update box);
966: * 2. its maximum squared-distance to any point in the update box.
967: * Both of these can be found by considering only the corners of the box.
968: * We save the minimum distance for each color in mindist[];
969: * only the smallest maximum distance is of interest.
970: */
971: minmaxdist = 0x7FFFFFFFL;
972:
973: for (i = 0; i < numcolors; i++)
974: {
975: /* We compute the squared-c0-distance term, then add in the other two. */
976: #ifdef ORIGINAL_LIB_JPEG
977: x = GETJSAMPLE (cinfo->colormap[0][i]);
978: #else
979: x = nim->red[i];
980: #endif
981: if (x < minc0)
982: {
983: tdist = (x - minc0) * C0_SCALE;
984: min_dist = tdist * tdist;
985: tdist = (x - maxc0) * C0_SCALE;
986: max_dist = tdist * tdist;
987: }
988: else if (x > maxc0)
989: {
990: tdist = (x - maxc0) * C0_SCALE;
991: min_dist = tdist * tdist;
992: tdist = (x - minc0) * C0_SCALE;
993: max_dist = tdist * tdist;
994: }
995: else
996: {
997: /* within cell range so no contribution to min_dist */
998: min_dist = 0;
999: if (x <= centerc0)
1000: {
1001: tdist = (x - maxc0) * C0_SCALE;
1002: max_dist = tdist * tdist;
1003: }
1004: else
1005: {
1006: tdist = (x - minc0) * C0_SCALE;
1007: max_dist = tdist * tdist;
1008: }
1009: }
1010:
1011: #ifdef ORIGINAL_LIB_JPEG
1012: x = GETJSAMPLE (cinfo->colormap[1][i]);
1013: #else
1014: x = nim->green[i];
1015: #endif
1016: if (x < minc1)
1017: {
1018: tdist = (x - minc1) * C1_SCALE;
1019: min_dist += tdist * tdist;
1020: tdist = (x - maxc1) * C1_SCALE;
1021: max_dist += tdist * tdist;
1022: }
1023: else if (x > maxc1)
1024: {
1025: tdist = (x - maxc1) * C1_SCALE;
1026: min_dist += tdist * tdist;
1027: tdist = (x - minc1) * C1_SCALE;
1028: max_dist += tdist * tdist;
1029: }
1030: else
1031: {
1032: /* within cell range so no contribution to min_dist */
1033: if (x <= centerc1)
1034: {
1035: tdist = (x - maxc1) * C1_SCALE;
1036: max_dist += tdist * tdist;
1037: }
1038: else
1039: {
1040: tdist = (x - minc1) * C1_SCALE;
1041: max_dist += tdist * tdist;
1042: }
1043: }
1044:
1045: #ifdef ORIGINAL_LIB_JPEG
1046: x = GETJSAMPLE (cinfo->colormap[2][i]);
1047: #else
1048: x = nim->blue[i];
1049: #endif
1050: if (x < minc2)
1051: {
1052: tdist = (x - minc2) * C2_SCALE;
1053: min_dist += tdist * tdist;
1054: tdist = (x - maxc2) * C2_SCALE;
1055: max_dist += tdist * tdist;
1056: }
1057: else if (x > maxc2)
1058: {
1059: tdist = (x - maxc2) * C2_SCALE;
1060: min_dist += tdist * tdist;
1061: tdist = (x - minc2) * C2_SCALE;
1062: max_dist += tdist * tdist;
1063: }
1064: else
1065: {
1066: /* within cell range so no contribution to min_dist */
1067: if (x <= centerc2)
1068: {
1069: tdist = (x - maxc2) * C2_SCALE;
1070: max_dist += tdist * tdist;
1071: }
1072: else
1073: {
1074: tdist = (x - minc2) * C2_SCALE;
1075: max_dist += tdist * tdist;
1076: }
1077: }
1078:
1079: mindist[i] = min_dist; /* save away the results */
1080: if (max_dist < minmaxdist)
1081: minmaxdist = max_dist;
1082: }
1083:
1084: /* Now we know that no cell in the update box is more than minmaxdist
1085: * away from some colormap entry. Therefore, only colors that are
1086: * within minmaxdist of some part of the box need be considered.
1087: */
1088: ncolors = 0;
1089: for (i = 0; i < numcolors; i++)
1090: {
1091: if (mindist[i] <= minmaxdist)
1092: colorlist[ncolors++] = (JSAMPLE) i;
1093: }
1094: return ncolors;
1095: }
1096:
1097:
1098: LOCAL (void) find_best_colors (
1099: #ifdef ORIGINAL_LIB_JPEG
1100: j_decompress_ptr cinfo,
1101: #else
1102: gdImagePtr oim, gdImagePtr nim, my_cquantize_ptr cquantize,
1103: #endif
1104: int minc0, int minc1, int minc2,
1105: int numcolors, JSAMPLE colorlist[],
1106: JSAMPLE bestcolor[])
1107: /* Find the closest colormap entry for each cell in the update box,
1108: * given the list of candidate colors prepared by find_nearby_colors.
1109: * Return the indexes of the closest entries in the bestcolor[] array.
1110: * This routine uses Thomas' incremental distance calculation method to
1111: * find the distance from a colormap entry to successive cells in the box.
1112: */
1113: {
1114: int ic0, ic1, ic2;
1115: int i, icolor;
1116: register INT32 *bptr; /* pointer into bestdist[] array */
1117: JSAMPLE *cptr; /* pointer into bestcolor[] array */
1118: INT32 dist0, dist1; /* initial distance values */
1119: register INT32 dist2; /* current distance in inner loop */
1120: INT32 xx0, xx1; /* distance increments */
1121: register INT32 xx2;
1122: INT32 inc0, inc1, inc2; /* initial values for increments */
1123: /* This array holds the distance to the nearest-so-far color for each cell */
1124: INT32 bestdist[BOX_C0_ELEMS * BOX_C1_ELEMS * BOX_C2_ELEMS];
1125:
1126: /* Initialize best-distance for each cell of the update box */
1127: bptr = bestdist;
1128: for (i = BOX_C0_ELEMS * BOX_C1_ELEMS * BOX_C2_ELEMS - 1; i >= 0; i--)
1129: *bptr++ = 0x7FFFFFFFL;
1130:
1131: /* For each color selected by find_nearby_colors,
1132: * compute its distance to the center of each cell in the box.
1133: * If that's less than best-so-far, update best distance and color number.
1134: */
1135:
1136: /* Nominal steps between cell centers ("x" in Thomas article) */
1137: #define STEP_C0 ((1 << C0_SHIFT) * C0_SCALE)
1138: #define STEP_C1 ((1 << C1_SHIFT) * C1_SCALE)
1139: #define STEP_C2 ((1 << C2_SHIFT) * C2_SCALE)
1140:
1141: for (i = 0; i < numcolors; i++)
1142: {
1143: int r, g, b;
1144: #ifdef ORIGINAL_LIB_JPEG
1145:
1146: icolor = GETJSAMPLE (colorlist[i]);
1147: r = GETJSAMPLE (cinfo->colormap[0][icolor]);
1148: g = GETJSAMPLE (cinfo->colormap[1][icolor]);
1149: b = GETJSAMPLE (cinfo->colormap[2][icolor]);
1150: #else
1151: icolor = colorlist[i];
1152: r = nim->red[icolor];
1153: g = nim->green[icolor];
1154: b = nim->blue[icolor];
1155: #endif
1156:
1157: /* Compute (square of) distance from minc0/c1/c2 to this color */
1158: inc0 = (minc0 - r) * C0_SCALE;
1159: dist0 = inc0 * inc0;
1160: inc1 = (minc1 - g) * C1_SCALE;
1161: dist0 += inc1 * inc1;
1162: inc2 = (minc2 - b) * C2_SCALE;
1163: dist0 += inc2 * inc2;
1164: /* Form the initial difference increments */
1165: inc0 = inc0 * (2 * STEP_C0) + STEP_C0 * STEP_C0;
1166: inc1 = inc1 * (2 * STEP_C1) + STEP_C1 * STEP_C1;
1167: inc2 = inc2 * (2 * STEP_C2) + STEP_C2 * STEP_C2;
1168: /* Now loop over all cells in box, updating distance per Thomas method */
1169: bptr = bestdist;
1170: cptr = bestcolor;
1171: xx0 = inc0;
1172: for (ic0 = BOX_C0_ELEMS - 1; ic0 >= 0; ic0--)
1173: {
1174: dist1 = dist0;
1175: xx1 = inc1;
1176: for (ic1 = BOX_C1_ELEMS - 1; ic1 >= 0; ic1--)
1177: {
1178: dist2 = dist1;
1179: xx2 = inc2;
1180: for (ic2 = BOX_C2_ELEMS - 1; ic2 >= 0; ic2--)
1181: {
1182: if (dist2 < *bptr)
1183: {
1184: *bptr = dist2;
1185: *cptr = (JSAMPLE) icolor;
1186: }
1187: dist2 += xx2;
1188: xx2 += 2 * STEP_C2 * STEP_C2;
1189: bptr++;
1190: cptr++;
1191: }
1192: dist1 += xx1;
1193: xx1 += 2 * STEP_C1 * STEP_C1;
1194: }
1195: dist0 += xx0;
1196: xx0 += 2 * STEP_C0 * STEP_C0;
1197: }
1198: }
1199: }
1200:
1201:
1202: LOCAL (void)
1203: fill_inverse_cmap (
1204: #ifdef ORIGINAL_LIB_JPEG
1205: j_decompress_ptr cinfo,
1206: #else
1207: gdImagePtr oim, gdImagePtr nim, my_cquantize_ptr cquantize,
1208: #endif
1209: int c0, int c1, int c2)
1210: /* Fill the inverse-colormap entries in the update box that contains */
1211: /* histogram cell c0/c1/c2. (Only that one cell MUST be filled, but */
1212: /* we can fill as many others as we wish.) */
1213: {
1214: #ifdef ORIGINAL_LIB_JPEG
1215: my_cquantize_ptr cquantize = (my_cquantize_ptr) cinfo->cquantize;
1216: #endif
1217: hist3d histogram = cquantize->histogram;
1218: int minc0, minc1, minc2; /* lower left corner of update box */
1219: int ic0, ic1, ic2;
1220: register JSAMPLE *cptr; /* pointer into bestcolor[] array */
1221: register histptr cachep; /* pointer into main cache array */
1222: /* This array lists the candidate colormap indexes. */
1223: JSAMPLE colorlist[MAXNUMCOLORS];
1224: int numcolors; /* number of candidate colors */
1225: /* This array holds the actually closest colormap index for each cell. */
1226: JSAMPLE bestcolor[BOX_C0_ELEMS * BOX_C1_ELEMS * BOX_C2_ELEMS];
1227:
1228: /* Convert cell coordinates to update box ID */
1229: c0 >>= BOX_C0_LOG;
1230: c1 >>= BOX_C1_LOG;
1231: c2 >>= BOX_C2_LOG;
1232:
1233: /* Compute true coordinates of update box's origin corner.
1234: * Actually we compute the coordinates of the center of the corner
1235: * histogram cell, which are the lower bounds of the volume we care about.
1236: */
1237: minc0 = (c0 << BOX_C0_SHIFT) + ((1 << C0_SHIFT) >> 1);
1238: minc1 = (c1 << BOX_C1_SHIFT) + ((1 << C1_SHIFT) >> 1);
1239: minc2 = (c2 << BOX_C2_SHIFT) + ((1 << C2_SHIFT) >> 1);
1240:
1241: /* Determine which colormap entries are close enough to be candidates
1242: * for the nearest entry to some cell in the update box.
1243: */
1244: #ifdef ORIGINAL_LIB_JPEG
1245: numcolors = find_nearby_colors (cinfo, minc0, minc1, minc2, colorlist);
1246:
1247: /* Determine the actually nearest colors. */
1248: find_best_colors (cinfo, minc0, minc1, minc2, numcolors, colorlist,
1249: bestcolor);
1250: #else
1251: numcolors =
1252: find_nearby_colors (oim, nim, cquantize, minc0, minc1, minc2, colorlist);
1253: find_best_colors (oim, nim, cquantize, minc0, minc1, minc2, numcolors,
1254: colorlist, bestcolor);
1255: #endif
1256:
1257: /* Save the best color numbers (plus 1) in the main cache array */
1258: c0 <<= BOX_C0_LOG; /* convert ID back to base cell indexes */
1259: c1 <<= BOX_C1_LOG;
1260: c2 <<= BOX_C2_LOG;
1261: cptr = bestcolor;
1262: for (ic0 = 0; ic0 < BOX_C0_ELEMS; ic0++)
1263: {
1264: for (ic1 = 0; ic1 < BOX_C1_ELEMS; ic1++)
1265: {
1266: cachep = &histogram[c0 + ic0][c1 + ic1][c2];
1267: for (ic2 = 0; ic2 < BOX_C2_ELEMS; ic2++)
1268: {
1269: #ifdef ORIGINAL_LIB_JPEG
1270: *cachep++ = (histcell) (GETJSAMPLE (*cptr++) + 1);
1271: #else
1272: *cachep++ = (histcell) ((*cptr++) + 1);
1273: #endif
1274: }
1275: }
1276: }
1277: }
1278:
1279:
1280: /*
1281: * Map some rows of pixels to the output colormapped representation.
1282: */
1283:
1284: METHODDEF (void)
1285: #ifndef ORIGINAL_LIB_JPEG
1286: pass2_no_dither (gdImagePtr oim, gdImagePtr nim, my_cquantize_ptr cquantize)
1287: {
1288: register int *inptr;
1289: register unsigned char *outptr;
1290: int width = oim->sx;
1291: int num_rows = oim->sy;
1292: #else
1293: pass2_no_dither (j_decompress_ptr cinfo,
1294: JSAMPARRAY input_buf, JSAMPARRAY output_buf, int num_rows)
1295: /* This version performs no dithering */
1296: {
1297: my_cquantize_ptr cquantize = (my_cquantize_ptr) cinfo->cquantize;
1298: register JSAMPROW inptr, outptr;
1299: JDIMENSION width = cinfo->output_width;
1300: #endif
1301: hist3d histogram = cquantize->histogram;
1302: register int c0, c1, c2;
1303: int row;
1304: JDIMENSION col;
1305: register histptr cachep;
1306:
1307:
1308: for (row = 0; row < num_rows; row++)
1309: {
1310: inptr = input_buf[row];
1311: outptr = output_buf[row];
1312: for (col = width; col > 0; col--)
1313: {
1314: /* get pixel value and index into the cache */
1315: int r, g, b;
1316: #ifdef ORIGINAL_LIB_JPEG
1317: r = GETJSAMPLE (*inptr++);
1318: g = GETJSAMPLE (*inptr++);
1319: b = GETJSAMPLE (*inptr++);
1320: #else
1321: r = gdTrueColorGetRed (*inptr);
1322: g = gdTrueColorGetGreen (*inptr);
1323: /*
1324: 2.0.24: inptr must not be incremented until after
1325: transparency check, if any. Thanks to "Super Pikeman."
1326: */
1327: b = gdTrueColorGetBlue (*inptr);
1328:
1329: /* If the pixel is transparent, we assign it the palette index that
1330: * will later be added at the end of the palette as the transparent
1331: * index. */
1332: if ((oim->transparent >= 0) && (oim->transparent == *(inptr - 1)))
1333: {
1334: *outptr++ = nim->colorsTotal;
1335: inptr++;
1336: continue;
1337: }
1338: inptr++;
1339: #endif
1340: c0 = r >> C0_SHIFT;
1341: c1 = g >> C1_SHIFT;
1342: c2 = b >> C2_SHIFT;
1343: cachep = &histogram[c0][c1][c2];
1344: /* If we have not seen this color before, find nearest colormap entry */
1345: /* and update the cache */
1346: if (*cachep == 0)
1347: #ifdef ORIGINAL_LIB_JPEG
1348: fill_inverse_cmap (cinfo, c0, c1, c2);
1349: #else
1350: fill_inverse_cmap (oim, nim, cquantize, c0, c1, c2);
1351: #endif
1352: /* Now emit the colormap index for this cell */
1353: #ifdef ORIGINAL_LIB_JPEG
1354: *outptr++ = (JSAMPLE) (*cachep - 1);
1355: #else
1356: *outptr++ = (*cachep - 1);
1357: #endif
1358: }
1359: }
1360: }
1361:
1362:
1363: METHODDEF (void)
1364: #ifndef ORIGINAL_LIB_JPEG
1365: pass2_fs_dither (gdImagePtr oim, gdImagePtr nim, my_cquantize_ptr cquantize)
1366: {
1367: #else
1368: pass2_fs_dither (j_decompress_ptr cinfo,
1369: JSAMPARRAY input_buf, JSAMPARRAY output_buf, int num_rows)
1370: /* This version performs Floyd-Steinberg dithering */
1371: {
1372: my_cquantize_ptr cquantize = (my_cquantize_ptr) cinfo->cquantize;
1373: JSAMPROW inptr; /* => current input pixel */
1374: #endif
1375: hist3d histogram = cquantize->histogram;
1376: register LOCFSERROR cur0, cur1, cur2; /* current error or pixel value */
1377: LOCFSERROR belowerr0, belowerr1, belowerr2; /* error for pixel below cur */
1378: LOCFSERROR bpreverr0, bpreverr1, bpreverr2; /* error for below/prev col */
1379: register FSERRPTR errorptr; /* => fserrors[] at column before current */
1380: histptr cachep;
1381: int dir; /* +1 or -1 depending on direction */
1382: int dir3; /* 3*dir, for advancing inptr & errorptr */
1383: int row;
1384: JDIMENSION col;
1385: #ifdef ORIGINAL_LIB_JPEG
1386: JSAMPROW outptr; /* => current output pixel */
1387: JDIMENSION width = cinfo->output_width;
1388: JSAMPLE *range_limit = cinfo->sample_range_limit;
1389: JSAMPROW colormap0 = cinfo->colormap[0];
1390: JSAMPROW colormap1 = cinfo->colormap[1];
1391: JSAMPROW colormap2 = cinfo->colormap[2];
1392: #else
1393: int *inptr; /* => current input pixel */
1394: unsigned char *outptr; /* => current output pixel */
1395: int width = oim->sx;
1396: int num_rows = oim->sy;
1397: int *colormap0 = nim->red;
1398: int *colormap1 = nim->green;
1399: int *colormap2 = nim->blue;
1400: #endif
1401: int *error_limit = cquantize->error_limiter;
1402:
1403:
1404: SHIFT_TEMPS for (row = 0; row < num_rows; row++)
1405: {
1406: inptr = input_buf[row];
1407: outptr = output_buf[row];
1408: if (cquantize->on_odd_row)
1409: {
1410: /* work right to left in this row */
1411: inptr += (width - 1) * 3; /* so point to rightmost pixel */
1412: outptr += width - 1;
1413: dir = -1;
1414: dir3 = -3;
1415: errorptr = cquantize->fserrors + (width + 1) * 3; /* => entry after last column */
1416: #ifdef ORIGINAL_LIB_JPEG_REVERSE_ODD_ROWS
1417: cquantize->on_odd_row = FALSE; /* flip for next time */
1418: #endif
1419: }
1420: else
1421: {
1422: /* work left to right in this row */
1423: dir = 1;
1424: dir3 = 3;
1425: errorptr = cquantize->fserrors; /* => entry before first real column */
1426: #ifdef ORIGINAL_LIB_JPEG_REVERSE_ODD_ROWS
1427: cquantize->on_odd_row = TRUE; /* flip for next time */
1428: #endif
1429: }
1430: /* Preset error values: no error propagated to first pixel from left */
1431: cur0 = cur1 = cur2 = 0;
1432: /* and no error propagated to row below yet */
1433: belowerr0 = belowerr1 = belowerr2 = 0;
1434: bpreverr0 = bpreverr1 = bpreverr2 = 0;
1435:
1436: for (col = width; col > 0; col--)
1437: {
1438:
1439: /* If this pixel is transparent, we want to assign it to the special
1440: * transparency color index past the end of the palette rather than
1441: * go through matching / dithering. */
1442: if ((oim->transparent >= 0) && (*inptr == oim->transparent))
1443: {
1444: *outptr = nim->colorsTotal;
1445: errorptr[0] = 0;
1446: errorptr[1] = 0;
1447: errorptr[2] = 0;
1448: errorptr[3] = 0;
1449: inptr += dir;
1450: outptr += dir;
1451: errorptr += dir3;
1452: continue;
1453: }
1454: /* curN holds the error propagated from the previous pixel on the
1455: * current line. Add the error propagated from the previous line
1456: * to form the complete error correction term for this pixel, and
1457: * round the error term (which is expressed * 16) to an integer.
1458: * RIGHT_SHIFT rounds towards minus infinity, so adding 8 is correct
1459: * for either sign of the error value.
1460: * Note: errorptr points to *previous* column's array entry.
1461: */
1462: cur0 = RIGHT_SHIFT (cur0 + errorptr[dir3 + 0] + 8, 4);
1463: cur1 = RIGHT_SHIFT (cur1 + errorptr[dir3 + 1] + 8, 4);
1464: cur2 = RIGHT_SHIFT (cur2 + errorptr[dir3 + 2] + 8, 4);
1465: /* Limit the error using transfer function set by init_error_limit.
1466: * See comments with init_error_limit for rationale.
1467: */
1468: cur0 = error_limit[cur0];
1469: cur1 = error_limit[cur1];
1470: cur2 = error_limit[cur2];
1471: /* Form pixel value + error, and range-limit to 0..MAXJSAMPLE.
1472: * The maximum error is +- MAXJSAMPLE (or less with error limiting);
1473: * this sets the required size of the range_limit array.
1474: */
1475: #ifdef ORIGINAL_LIB_JPEG
1476: cur0 += GETJSAMPLE (inptr[0]);
1477: cur1 += GETJSAMPLE (inptr[1]);
1478: cur2 += GETJSAMPLE (inptr[2]);
1479: cur0 = GETJSAMPLE (range_limit[cur0]);
1480: cur1 = GETJSAMPLE (range_limit[cur1]);
1481: cur2 = GETJSAMPLE (range_limit[cur2]);
1482: #else
1483: cur0 += gdTrueColorGetRed (*inptr);
1484: cur1 += gdTrueColorGetGreen (*inptr);
1485: cur2 += gdTrueColorGetBlue (*inptr);
1486: range_limit (cur0);
1487: range_limit (cur1);
1488: range_limit (cur2);
1489: #endif
1490:
1491: /* Index into the cache with adjusted pixel value */
1492: cachep =
1493: &histogram[cur0 >> C0_SHIFT][cur1 >> C1_SHIFT][cur2 >> C2_SHIFT];
1494: /* If we have not seen this color before, find nearest colormap */
1495: /* entry and update the cache */
1496: if (*cachep == 0)
1497: #ifdef ORIGINAL_LIB_JPEG
1498: fill_inverse_cmap (cinfo, cur0 >> C0_SHIFT, cur1 >> C1_SHIFT,
1499: cur2 >> C2_SHIFT);
1500: #else
1501: fill_inverse_cmap (oim, nim, cquantize, cur0 >> C0_SHIFT,
1502: cur1 >> C1_SHIFT, cur2 >> C2_SHIFT);
1503: #endif
1504: /* Now emit the colormap index for this cell */
1505: {
1506: register int pixcode = *cachep - 1;
1507: *outptr = (JSAMPLE) pixcode;
1508: /* Compute representation error for this pixel */
1509: #define GETJSAMPLE
1510: cur0 -= GETJSAMPLE (colormap0[pixcode]);
1511: cur1 -= GETJSAMPLE (colormap1[pixcode]);
1512: cur2 -= GETJSAMPLE (colormap2[pixcode]);
1513: #undef GETJSAMPLE
1514: }
1515: /* Compute error fractions to be propagated to adjacent pixels.
1516: * Add these into the running sums, and simultaneously shift the
1517: * next-line error sums left by 1 column.
1518: */
1519: {
1520: register LOCFSERROR bnexterr, delta;
1521:
1522: bnexterr = cur0; /* Process component 0 */
1523: delta = cur0 * 2;
1524: cur0 += delta; /* form error * 3 */
1525: errorptr[0] = (FSERROR) (bpreverr0 + cur0);
1526: cur0 += delta; /* form error * 5 */
1527: bpreverr0 = belowerr0 + cur0;
1528: belowerr0 = bnexterr;
1529: cur0 += delta; /* form error * 7 */
1530: bnexterr = cur1; /* Process component 1 */
1531: delta = cur1 * 2;
1532: cur1 += delta; /* form error * 3 */
1533: errorptr[1] = (FSERROR) (bpreverr1 + cur1);
1534: cur1 += delta; /* form error * 5 */
1535: bpreverr1 = belowerr1 + cur1;
1536: belowerr1 = bnexterr;
1537: cur1 += delta; /* form error * 7 */
1538: bnexterr = cur2; /* Process component 2 */
1539: delta = cur2 * 2;
1540: cur2 += delta; /* form error * 3 */
1541: errorptr[2] = (FSERROR) (bpreverr2 + cur2);
1542: cur2 += delta; /* form error * 5 */
1543: bpreverr2 = belowerr2 + cur2;
1544: belowerr2 = bnexterr;
1545: cur2 += delta; /* form error * 7 */
1546: }
1547: /* At this point curN contains the 7/16 error value to be propagated
1548: * to the next pixel on the current line, and all the errors for the
1549: * next line have been shifted over. We are therefore ready to move on.
1550: */
1551: #ifdef ORIGINAL_LIB_JPEG
1552: inptr += dir3; /* Advance pixel pointers to next column */
1553: #else
1554: inptr += dir; /* Advance pixel pointers to next column */
1555: #endif
1556: outptr += dir;
1557: errorptr += dir3; /* advance errorptr to current column */
1558: }
1559: /* Post-loop cleanup: we must unload the final error values into the
1560: * final fserrors[] entry. Note we need not unload belowerrN because
1561: * it is for the dummy column before or after the actual array.
1562: */
1563: errorptr[0] = (FSERROR) bpreverr0; /* unload prev errs into array */
1564: errorptr[1] = (FSERROR) bpreverr1;
1565: errorptr[2] = (FSERROR) bpreverr2;
1566: }
1567: }
1568:
1569:
1570: /*
1571: * Initialize the error-limiting transfer function (lookup table).
1572: * The raw F-S error computation can potentially compute error values of up to
1573: * +- MAXJSAMPLE. But we want the maximum correction applied to a pixel to be
1574: * much less, otherwise obviously wrong pixels will be created. (Typical
1575: * effects include weird fringes at color-area boundaries, isolated bright
1576: * pixels in a dark area, etc.) The standard advice for avoiding this problem
1577: * is to ensure that the "corners" of the color cube are allocated as output
1578: * colors; then repeated errors in the same direction cannot cause cascading
1579: * error buildup. However, that only prevents the error from getting
1580: * completely out of hand; Aaron Giles reports that error limiting improves
1581: * the results even with corner colors allocated.
1582: * A simple clamping of the error values to about +- MAXJSAMPLE/8 works pretty
1583: * well, but the smoother transfer function used below is even better. Thanks
1584: * to Aaron Giles for this idea.
1585: */
1586:
1587: LOCAL (void)
1588: #ifdef ORIGINAL_LIB_JPEG
1589: init_error_limit (j_decompress_ptr cinfo)
1590: #else
1591: init_error_limit (gdImagePtr oim, gdImagePtr nim, my_cquantize_ptr cquantize)
1592: #endif
1593: /* Allocate and fill in the error_limiter table */
1594: {
1595: int *table;
1596: int in, out;
1597: #ifdef ORIGINAL_LIB_JPEG
1598: my_cquantize_ptr cquantize = (my_cquantize_ptr) cinfo->cquantize;
1599: table = (int *) (*cinfo->mem->alloc_small)
1600: ((j_common_ptr) cinfo, JPOOL_IMAGE, (MAXJSAMPLE * 2 + 1) * SIZEOF (int));
1601: #else
1602: cquantize->error_limiter_storage =
1603: (int *) safe_emalloc ((MAXJSAMPLE * 2 + 1), sizeof (int), 0);
1604: if (!cquantize->error_limiter_storage)
1605: {
1606: return;
1607: }
1608: table = cquantize->error_limiter_storage;
1609: #endif
1610:
1611: table += MAXJSAMPLE; /* so can index -MAXJSAMPLE .. +MAXJSAMPLE */
1612: cquantize->error_limiter = table;
1613:
1614: #define STEPSIZE ((MAXJSAMPLE+1)/16)
1615: /* Map errors 1:1 up to +- MAXJSAMPLE/16 */
1616: out = 0;
1617: for (in = 0; in < STEPSIZE; in++, out++)
1618: {
1619: table[in] = out;
1620: table[-in] = -out;
1621: }
1622: /* Map errors 1:2 up to +- 3*MAXJSAMPLE/16 */
1623: for (; in < STEPSIZE * 3; in++, out += (in & 1) ? 0 : 1)
1624: {
1625: table[in] = out;
1626: table[-in] = -out;
1627: }
1628: /* Clamp the rest to final out value (which is (MAXJSAMPLE+1)/8) */
1629: for (; in <= MAXJSAMPLE; in++)
1630: {
1631: table[in] = out;
1632: table[-in] = -out;
1633: }
1634: #undef STEPSIZE
1635: }
1636:
1637:
1638: /*
1639: * Finish up at the end of each pass.
1640: */
1641:
1642: #ifdef ORIGINAL_LIB_JPEG
1643: METHODDEF (void)
1644: finish_pass1 (j_decompress_ptr cinfo)
1645: {
1646: my_cquantize_ptr cquantize = (my_cquantize_ptr) cinfo->cquantize;
1647:
1648: /* Select the representative colors and fill in cinfo->colormap */
1649: cinfo->colormap = cquantize->sv_colormap;
1650: select_colors (cinfo, cquantize->desired);
1651: /* Force next pass to zero the color index table */
1652: cquantize->needs_zeroed = TRUE;
1653: }
1654:
1655:
1656: METHODDEF (void)
1657: finish_pass2 (j_decompress_ptr cinfo)
1658: {
1659: /* no work */
1660: }
1661:
1662: /*
1663: * Initialize for each processing pass.
1664: */
1665:
1666: METHODDEF (void)
1667: start_pass_2_quant (j_decompress_ptr cinfo, boolean is_pre_scan)
1668: {
1669: my_cquantize_ptr cquantize = (my_cquantize_ptr) cinfo->cquantize;
1670: hist3d histogram = cquantize->histogram;
1671: int i;
1672:
1673: /* Only F-S dithering or no dithering is supported. */
1674: /* If user asks for ordered dither, give him F-S. */
1675: if (cinfo->dither_mode != JDITHER_NONE)
1676: cinfo->dither_mode = JDITHER_FS;
1677:
1678: if (is_pre_scan)
1679: {
1680: /* Set up method pointers */
1681: cquantize->pub.color_quantize = prescan_quantize;
1682: cquantize->pub.finish_pass = finish_pass1;
1683: cquantize->needs_zeroed = TRUE; /* Always zero histogram */
1684: }
1685: else
1686: {
1687: /* Set up method pointers */
1688: if (cinfo->dither_mode == JDITHER_FS)
1689: cquantize->pub.color_quantize = pass2_fs_dither;
1690: else
1691: cquantize->pub.color_quantize = pass2_no_dither;
1692: cquantize->pub.finish_pass = finish_pass2;
1693:
1694: /* Make sure color count is acceptable */
1695: i = cinfo->actual_number_of_colors;
1696: if (i < 1)
1697: ERREXIT1 (cinfo, JERR_QUANT_FEW_COLORS, 1);
1698: if (i > MAXNUMCOLORS)
1699: ERREXIT1 (cinfo, JERR_QUANT_MANY_COLORS, MAXNUMCOLORS);
1700:
1701: if (cinfo->dither_mode == JDITHER_FS)
1702: {
1703: size_t arraysize = (size_t) ((cinfo->output_width + 2) *
1704: (3 * SIZEOF (FSERROR)));
1705: /* Allocate Floyd-Steinberg workspace if we didn't already. */
1706: if (cquantize->fserrors == NULL)
1707: cquantize->fserrors = (FSERRPTR) (*cinfo->mem->alloc_large)
1708: ((j_common_ptr) cinfo, JPOOL_IMAGE, arraysize);
1709: /* Initialize the propagated errors to zero. */
1710: jzero_far ((void FAR *) cquantize->fserrors, arraysize);
1711: /* Make the error-limit table if we didn't already. */
1712: if (cquantize->error_limiter == NULL)
1713: init_error_limit (cinfo);
1714: cquantize->on_odd_row = FALSE;
1715: }
1716:
1717: }
1718: /* Zero the histogram or inverse color map, if necessary */
1719: if (cquantize->needs_zeroed)
1720: {
1721: for (i = 0; i < HIST_C0_ELEMS; i++)
1722: {
1723: jzero_far ((void FAR *) histogram[i],
1724: HIST_C1_ELEMS * HIST_C2_ELEMS * SIZEOF (histcell));
1725: }
1726: cquantize->needs_zeroed = FALSE;
1727: }
1728: }
1729:
1730:
1731: /*
1732: * Switch to a new external colormap between output passes.
1733: */
1734:
1735: METHODDEF (void)
1736: new_color_map_2_quant (j_decompress_ptr cinfo)
1737: {
1738: my_cquantize_ptr cquantize = (my_cquantize_ptr) cinfo->cquantize;
1739:
1740: /* Reset the inverse color map */
1741: cquantize->needs_zeroed = TRUE;
1742: }
1743: #else
1744: static void
1745: zeroHistogram (hist3d histogram)
1746: {
1747: int i;
1748: /* Zero the histogram or inverse color map */
1749: for (i = 0; i < HIST_C0_ELEMS; i++)
1750: {
1751: memset (histogram[i],
1752: 0, HIST_C1_ELEMS * HIST_C2_ELEMS * sizeof (histcell));
1753: }
1754: }
1755: #endif
1756:
1757: static void gdImageTrueColorToPaletteBody (gdImagePtr oim, int dither, int colorsWanted, gdImagePtr *cimP);
1758:
1759: gdImagePtr gdImageCreatePaletteFromTrueColor (gdImagePtr im, int dither, int colorsWanted)
1760: {
1761: gdImagePtr nim;
1762: gdImageTrueColorToPaletteBody(im, dither, colorsWanted, &nim);
1763: return nim;
1764: }
1765:
1766: void gdImageTrueColorToPalette (gdImagePtr im, int dither, int colorsWanted)
1767: {
1768: gdImageTrueColorToPaletteBody(im, dither, colorsWanted, 0);
1769: }
1770:
1771: /*
1772: * Module initialization routine for 2-pass color quantization.
1773: */
1774:
1775: #ifdef ORIGINAL_LIB_JPEG
1776: GLOBAL (void)
1777: jinit_2pass_quantizer (j_decompress_ptr cinfo)
1778: #else
1779: static void gdImageTrueColorToPaletteBody (gdImagePtr oim, int dither, int colorsWanted, gdImagePtr *cimP)
1780: #endif
1781: {
1782: my_cquantize_ptr cquantize = NULL;
1783: int i;
1784:
1785: #ifndef ORIGINAL_LIB_JPEG
1786: /* Allocate the JPEG palette-storage */
1787: size_t arraysize;
1788: int maxColors = gdMaxColors;
1789: gdImagePtr nim;
1790: if (cimP) {
1791: nim = gdImageCreate(oim->sx, oim->sy);
1792: *cimP = nim;
1793: if (!nim) {
1794: return;
1795: }
1796: } else {
1797: nim = oim;
1798: }
1799: if (!oim->trueColor)
1800: {
1801: /* (Almost) nothing to do! */
1802: if (cimP) {
1803: gdImageCopy(nim, oim, 0, 0, 0, 0, oim->sx, oim->sy);
1804: *cimP = nim;
1805: }
1806: return;
1807: }
1808:
1809: /* If we have a transparent color (the alphaless mode of transparency), we
1810: * must reserve a palette entry for it at the end of the palette. */
1811: if (oim->transparent >= 0)
1812: {
1813: maxColors--;
1814: }
1815: if (colorsWanted > maxColors)
1816: {
1817: colorsWanted = maxColors;
1818: }
1819: if (!cimP) {
1820: nim->pixels = gdCalloc (sizeof (unsigned char *), oim->sy);
1821: if (!nim->pixels)
1822: {
1823: /* No can do */
1824: goto outOfMemory;
1825: }
1826: for (i = 0; (i < nim->sy); i++)
1827: {
1828: nim->pixels[i] = gdCalloc (sizeof (unsigned char *), oim->sx);
1829: if (!nim->pixels[i])
1830: {
1831: goto outOfMemory;
1832: }
1833: }
1834: }
1835: #endif
1836:
1837: #ifdef ORIGINAL_LIB_JPEG
1838: cquantize = (my_cquantize_ptr)
1839: (*cinfo->mem->alloc_small) ((j_common_ptr) cinfo, JPOOL_IMAGE,
1840: SIZEOF (my_cquantizer));
1841: cinfo->cquantize = (struct jpeg_color_quantizer *) cquantize;
1842: cquantize->pub.start_pass = start_pass_2_quant;
1843: cquantize->pub.new_color_map = new_color_map_2_quant;
1844: /* Make sure jdmaster didn't give me a case I can't handle */
1845: if (cinfo->out_color_components != 3)
1846: ERREXIT (cinfo, JERR_NOTIMPL);
1847: #else
1848: cquantize = (my_cquantize_ptr) gdCalloc (sizeof (my_cquantizer), 1);
1849: if (!cquantize)
1850: {
1851: /* No can do */
1852: goto outOfMemory;
1853: }
1854: #endif
1855: cquantize->fserrors = NULL; /* flag optional arrays not allocated */
1856: cquantize->error_limiter = NULL;
1857:
1858:
1859: /* Allocate the histogram/inverse colormap storage */
1860: #ifdef ORIGINAL_LIB_JPEG
1861: cquantize->histogram = (hist3d) (*cinfo->mem->alloc_small)
1862: ((j_common_ptr) cinfo, JPOOL_IMAGE, HIST_C0_ELEMS * SIZEOF (hist2d));
1863: for (i = 0; i < HIST_C0_ELEMS; i++)
1864: {
1865: cquantize->histogram[i] = (hist2d) (*cinfo->mem->alloc_large)
1866: ((j_common_ptr) cinfo, JPOOL_IMAGE,
1867: HIST_C1_ELEMS * HIST_C2_ELEMS * SIZEOF (histcell));
1868: }
1869: cquantize->needs_zeroed = TRUE; /* histogram is garbage now */
1870: #else
1871: cquantize->histogram = (hist3d) safe_emalloc (HIST_C0_ELEMS, sizeof (hist2d), 0);
1872: for (i = 0; i < HIST_C0_ELEMS; i++)
1873: {
1874: cquantize->histogram[i] =
1875: (hist2d) safe_emalloc (HIST_C1_ELEMS * HIST_C2_ELEMS, sizeof (histcell), 0);
1876: if (!cquantize->histogram[i])
1877: {
1878: goto outOfMemory;
1879: }
1880: }
1881: #endif
1882:
1883: #ifdef ORIGINAL_LIB_JPEG
1884: /* Allocate storage for the completed colormap, if required.
1885: * We do this now since it is FAR storage and may affect
1886: * the memory manager's space calculations.
1887: */
1888: if (cinfo->enable_2pass_quant)
1889: {
1890: /* Make sure color count is acceptable */
1891: int desired = cinfo->desired_number_of_colors;
1892: /* Lower bound on # of colors ... somewhat arbitrary as long as > 0 */
1893: if (desired < 8)
1894: ERREXIT1 (cinfo, JERR_QUANT_FEW_COLORS, 8);
1895: /* Make sure colormap indexes can be represented by JSAMPLEs */
1896: if (desired > MAXNUMCOLORS)
1897: ERREXIT1 (cinfo, JERR_QUANT_MANY_COLORS, MAXNUMCOLORS);
1898: cquantize->sv_colormap = (*cinfo->mem->alloc_sarray)
1899: ((j_common_ptr) cinfo, JPOOL_IMAGE, (JDIMENSION) desired,
1900: (JDIMENSION) 3);
1901: cquantize->desired = desired;
1902: }
1903: else
1904: cquantize->sv_colormap = NULL;
1905:
1906: /* Only F-S dithering or no dithering is supported. */
1907: /* If user asks for ordered dither, give him F-S. */
1908: if (cinfo->dither_mode != JDITHER_NONE)
1909: cinfo->dither_mode = JDITHER_FS;
1910:
1911: /* Allocate Floyd-Steinberg workspace if necessary.
1912: * This isn't really needed until pass 2, but again it is FAR storage.
1913: * Although we will cope with a later change in dither_mode,
1914: * we do not promise to honor max_memory_to_use if dither_mode changes.
1915: */
1916: if (cinfo->dither_mode == JDITHER_FS)
1917: {
1918: cquantize->fserrors = (FSERRPTR) (*cinfo->mem->alloc_large)
1919: ((j_common_ptr) cinfo, JPOOL_IMAGE,
1920: (size_t) ((cinfo->output_width + 2) * (3 * SIZEOF (FSERROR))));
1921: /* Might as well create the error-limiting table too. */
1922: init_error_limit (cinfo);
1923: }
1924: #else
1925:
1926: cquantize->fserrors = (FSERRPTR) safe_emalloc (3, sizeof (FSERROR), 0);
1927: init_error_limit (oim, nim, cquantize);
1928: arraysize = (size_t) ((nim->sx + 2) * (3 * sizeof (FSERROR)));
1929: /* Allocate Floyd-Steinberg workspace. */
1930: cquantize->fserrors = gdRealloc(cquantize->fserrors, arraysize);
1931: memset(cquantize->fserrors, 0, arraysize);
1932: if (!cquantize->fserrors)
1933: {
1934: goto outOfMemory;
1935: }
1936: cquantize->on_odd_row = FALSE;
1937:
1938: /* Do the work! */
1939: zeroHistogram (cquantize->histogram);
1940: prescan_quantize (oim, nim, cquantize);
1941: /* TBB 2.0.5: pass colorsWanted, not 256! */
1942: select_colors (oim, nim, cquantize, colorsWanted);
1943: zeroHistogram (cquantize->histogram);
1944: if (dither)
1945: {
1946: pass2_fs_dither (oim, nim, cquantize);
1947: }
1948: else
1949: {
1950: pass2_no_dither (oim, nim, cquantize);
1951: }
1952: #if 0 /* 2.0.12; we no longer attempt full alpha in palettes */
1953: if (cquantize->transparentIsPresent)
1954: {
1955: int mt = -1;
1956: int mtIndex = -1;
1957: for (i = 0; (i < im->colorsTotal); i++)
1958: {
1959: if (im->alpha[i] > mt)
1960: {
1961: mtIndex = i;
1962: mt = im->alpha[i];
1963: }
1964: }
1965: for (i = 0; (i < im->colorsTotal); i++)
1966: {
1967: if (im->alpha[i] == mt)
1968: {
1969: im->alpha[i] = gdAlphaTransparent;
1970: }
1971: }
1972: }
1973: if (cquantize->opaqueIsPresent)
1974: {
1975: int mo = 128;
1976: int moIndex = -1;
1977: for (i = 0; (i < im->colorsTotal); i++)
1978: {
1979: if (im->alpha[i] < mo)
1980: {
1981: moIndex = i;
1982: mo = im->alpha[i];
1983: }
1984: }
1985: for (i = 0; (i < im->colorsTotal); i++)
1986: {
1987: if (im->alpha[i] == mo)
1988: {
1989: im->alpha[i] = gdAlphaOpaque;
1990: }
1991: }
1992: }
1993: #endif
1994:
1995: /* If we had a 'transparent' color, increment the color count so it's
1996: * officially in the palette and convert the transparent variable to point to
1997: * an index rather than a color (Its data already exists and transparent
1998: * pixels have already been mapped to it by this point, it is done late as to
1999: * avoid color matching / dithering with it). */
2000: if (oim->transparent >= 0)
2001: {
2002: nim->transparent = nim->colorsTotal;
2003: nim->colorsTotal++;
2004: }
2005:
2006: /* Success! Get rid of the truecolor image data. */
2007: if (!cimP) {
2008: oim->trueColor = 0;
2009: /* Junk the truecolor pixels */
2010: for (i = 0; i < oim->sy; i++)
2011: {
2012: gdFree (oim->tpixels[i]);
2013: }
2014: gdFree (oim->tpixels);
2015: oim->tpixels = 0;
2016: }
2017: goto success;
2018: /* Tediously free stuff. */
2019: outOfMemory:
2020: if (oim->trueColor)
2021: {
2022: if (!cimP) {
2023: /* On failure only */
2024: for (i = 0; i < nim->sy; i++)
2025: {
2026: if (nim->pixels[i])
2027: {
2028: gdFree (nim->pixels[i]);
2029: }
2030: }
2031: if (nim->pixels)
2032: {
2033: gdFree (nim->pixels);
2034: }
2035: nim->pixels = 0;
2036: } else {
2037: gdImageDestroy(nim);
2038: *cimP = 0;
2039: }
2040: }
2041: success:
2042: for (i = 0; i < HIST_C0_ELEMS; i++)
2043: {
2044: if (cquantize->histogram[i])
2045: {
2046: gdFree (cquantize->histogram[i]);
2047: }
2048: }
2049: if (cquantize->histogram)
2050: {
2051: gdFree (cquantize->histogram);
2052: }
2053: if (cquantize->fserrors)
2054: {
2055: gdFree (cquantize->fserrors);
2056: }
2057: if (cquantize->error_limiter_storage)
2058: {
2059: gdFree (cquantize->error_limiter_storage);
2060: }
2061: if (cquantize)
2062: {
2063: gdFree (cquantize);
2064: }
2065:
2066: #endif
2067: }
2068:
2069:
2070: #endif
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