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[chromium-blink-merge.git] / third_party / libwebp / enc / histogram.c
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1 // Copyright 2012 Google Inc. All Rights Reserved.
2 //
3 // Use of this source code is governed by a BSD-style license
4 // that can be found in the COPYING file in the root of the source
5 // tree. An additional intellectual property rights grant can be found
6 // in the file PATENTS. All contributing project authors may
7 // be found in the AUTHORS file in the root of the source tree.
8 // -----------------------------------------------------------------------------
9 //
10 // Author: Jyrki Alakuijala (jyrki@google.com)
12 #ifdef HAVE_CONFIG_H
13 #include "../webp/config.h"
14 #endif
16 #include <math.h>
18 #include "./backward_references.h"
19 #include "./histogram.h"
20 #include "../dsp/lossless.h"
21 #include "../utils/utils.h"
23 #define MAX_COST 1.e38
25 // Number of partitions for the three dominant (literal, red and blue) symbol
26 // costs.
27 #define NUM_PARTITIONS 4
28 // The size of the bin-hash corresponding to the three dominant costs.
29 #define BIN_SIZE (NUM_PARTITIONS * NUM_PARTITIONS * NUM_PARTITIONS)
31 static void HistogramClear(VP8LHistogram* const p) {
32 uint32_t* const literal = p->literal_;
33 const int cache_bits = p->palette_code_bits_;
34 const int histo_size = VP8LGetHistogramSize(cache_bits);
35 memset(p, 0, histo_size);
36 p->palette_code_bits_ = cache_bits;
37 p->literal_ = literal;
40 static void HistogramCopy(const VP8LHistogram* const src,
41 VP8LHistogram* const dst) {
42 uint32_t* const dst_literal = dst->literal_;
43 const int dst_cache_bits = dst->palette_code_bits_;
44 const int histo_size = VP8LGetHistogramSize(dst_cache_bits);
45 assert(src->palette_code_bits_ == dst_cache_bits);
46 memcpy(dst, src, histo_size);
47 dst->literal_ = dst_literal;
50 int VP8LGetHistogramSize(int cache_bits) {
51 const int literal_size = VP8LHistogramNumCodes(cache_bits);
52 const size_t total_size = sizeof(VP8LHistogram) + sizeof(int) * literal_size;
53 assert(total_size <= (size_t)0x7fffffff);
54 return (int)total_size;
57 void VP8LFreeHistogram(VP8LHistogram* const histo) {
58 WebPSafeFree(histo);
61 void VP8LFreeHistogramSet(VP8LHistogramSet* const histo) {
62 WebPSafeFree(histo);
65 void VP8LHistogramStoreRefs(const VP8LBackwardRefs* const refs,
66 VP8LHistogram* const histo) {
67 VP8LRefsCursor c = VP8LRefsCursorInit(refs);
68 while (VP8LRefsCursorOk(&c)) {
69 VP8LHistogramAddSinglePixOrCopy(histo, c.cur_pos);
70 VP8LRefsCursorNext(&c);
74 void VP8LHistogramCreate(VP8LHistogram* const p,
75 const VP8LBackwardRefs* const refs,
76 int palette_code_bits) {
77 if (palette_code_bits >= 0) {
78 p->palette_code_bits_ = palette_code_bits;
80 HistogramClear(p);
81 VP8LHistogramStoreRefs(refs, p);
84 void VP8LHistogramInit(VP8LHistogram* const p, int palette_code_bits) {
85 p->palette_code_bits_ = palette_code_bits;
86 HistogramClear(p);
89 VP8LHistogram* VP8LAllocateHistogram(int cache_bits) {
90 VP8LHistogram* histo = NULL;
91 const int total_size = VP8LGetHistogramSize(cache_bits);
92 uint8_t* const memory = (uint8_t*)WebPSafeMalloc(total_size, sizeof(*memory));
93 if (memory == NULL) return NULL;
94 histo = (VP8LHistogram*)memory;
95 // literal_ won't necessary be aligned.
96 histo->literal_ = (uint32_t*)(memory + sizeof(VP8LHistogram));
97 VP8LHistogramInit(histo, cache_bits);
98 return histo;
101 VP8LHistogramSet* VP8LAllocateHistogramSet(int size, int cache_bits) {
102 int i;
103 VP8LHistogramSet* set;
104 const size_t total_size = sizeof(*set)
105 + sizeof(*set->histograms) * size
106 + (size_t)VP8LGetHistogramSize(cache_bits) * size;
107 uint8_t* memory = (uint8_t*)WebPSafeMalloc(total_size, sizeof(*memory));
108 if (memory == NULL) return NULL;
110 set = (VP8LHistogramSet*)memory;
111 memory += sizeof(*set);
112 set->histograms = (VP8LHistogram**)memory;
113 memory += size * sizeof(*set->histograms);
114 set->max_size = size;
115 set->size = size;
116 for (i = 0; i < size; ++i) {
117 set->histograms[i] = (VP8LHistogram*)memory;
118 // literal_ won't necessary be aligned.
119 set->histograms[i]->literal_ = (uint32_t*)(memory + sizeof(VP8LHistogram));
120 VP8LHistogramInit(set->histograms[i], cache_bits);
121 // There's no padding/alignment between successive histograms.
122 memory += VP8LGetHistogramSize(cache_bits);
124 return set;
127 // -----------------------------------------------------------------------------
129 void VP8LHistogramAddSinglePixOrCopy(VP8LHistogram* const histo,
130 const PixOrCopy* const v) {
131 if (PixOrCopyIsLiteral(v)) {
132 ++histo->alpha_[PixOrCopyLiteral(v, 3)];
133 ++histo->red_[PixOrCopyLiteral(v, 2)];
134 ++histo->literal_[PixOrCopyLiteral(v, 1)];
135 ++histo->blue_[PixOrCopyLiteral(v, 0)];
136 } else if (PixOrCopyIsCacheIdx(v)) {
137 const int literal_ix =
138 NUM_LITERAL_CODES + NUM_LENGTH_CODES + PixOrCopyCacheIdx(v);
139 ++histo->literal_[literal_ix];
140 } else {
141 int code, extra_bits;
142 VP8LPrefixEncodeBits(PixOrCopyLength(v), &code, &extra_bits);
143 ++histo->literal_[NUM_LITERAL_CODES + code];
144 VP8LPrefixEncodeBits(PixOrCopyDistance(v), &code, &extra_bits);
145 ++histo->distance_[code];
149 static WEBP_INLINE double BitsEntropyRefine(int nonzeros, int sum, int max_val,
150 double retval) {
151 double mix;
152 if (nonzeros < 5) {
153 if (nonzeros <= 1) {
154 return 0;
156 // Two symbols, they will be 0 and 1 in a Huffman code.
157 // Let's mix in a bit of entropy to favor good clustering when
158 // distributions of these are combined.
159 if (nonzeros == 2) {
160 return 0.99 * sum + 0.01 * retval;
162 // No matter what the entropy says, we cannot be better than min_limit
163 // with Huffman coding. I am mixing a bit of entropy into the
164 // min_limit since it produces much better (~0.5 %) compression results
165 // perhaps because of better entropy clustering.
166 if (nonzeros == 3) {
167 mix = 0.95;
168 } else {
169 mix = 0.7; // nonzeros == 4.
171 } else {
172 mix = 0.627;
176 double min_limit = 2 * sum - max_val;
177 min_limit = mix * min_limit + (1.0 - mix) * retval;
178 return (retval < min_limit) ? min_limit : retval;
182 static double BitsEntropy(const uint32_t* const array, int n) {
183 double retval = 0.;
184 uint32_t sum = 0;
185 int nonzeros = 0;
186 uint32_t max_val = 0;
187 int i;
188 for (i = 0; i < n; ++i) {
189 if (array[i] != 0) {
190 sum += array[i];
191 ++nonzeros;
192 retval -= VP8LFastSLog2(array[i]);
193 if (max_val < array[i]) {
194 max_val = array[i];
198 retval += VP8LFastSLog2(sum);
199 return BitsEntropyRefine(nonzeros, sum, max_val, retval);
202 static double BitsEntropyCombined(const uint32_t* const X,
203 const uint32_t* const Y, int n) {
204 double retval = 0.;
205 int sum = 0;
206 int nonzeros = 0;
207 int max_val = 0;
208 int i;
209 for (i = 0; i < n; ++i) {
210 const int xy = X[i] + Y[i];
211 if (xy != 0) {
212 sum += xy;
213 ++nonzeros;
214 retval -= VP8LFastSLog2(xy);
215 if (max_val < xy) {
216 max_val = xy;
220 retval += VP8LFastSLog2(sum);
221 return BitsEntropyRefine(nonzeros, sum, max_val, retval);
224 static double InitialHuffmanCost(void) {
225 // Small bias because Huffman code length is typically not stored in
226 // full length.
227 static const int kHuffmanCodeOfHuffmanCodeSize = CODE_LENGTH_CODES * 3;
228 static const double kSmallBias = 9.1;
229 return kHuffmanCodeOfHuffmanCodeSize - kSmallBias;
232 // Finalize the Huffman cost based on streak numbers and length type (<3 or >=3)
233 static double FinalHuffmanCost(const VP8LStreaks* const stats) {
234 double retval = InitialHuffmanCost();
235 retval += stats->counts[0] * 1.5625 + 0.234375 * stats->streaks[0][1];
236 retval += stats->counts[1] * 2.578125 + 0.703125 * stats->streaks[1][1];
237 retval += 1.796875 * stats->streaks[0][0];
238 retval += 3.28125 * stats->streaks[1][0];
239 return retval;
242 // Trampolines
243 static double HuffmanCost(const uint32_t* const population, int length) {
244 const VP8LStreaks stats = VP8LHuffmanCostCount(population, length);
245 return FinalHuffmanCost(&stats);
248 static double HuffmanCostCombined(const uint32_t* const X,
249 const uint32_t* const Y, int length) {
250 const VP8LStreaks stats = VP8LHuffmanCostCombinedCount(X, Y, length);
251 return FinalHuffmanCost(&stats);
254 // Aggregated costs
255 static double PopulationCost(const uint32_t* const population, int length) {
256 return BitsEntropy(population, length) + HuffmanCost(population, length);
259 static double GetCombinedEntropy(const uint32_t* const X,
260 const uint32_t* const Y, int length) {
261 return BitsEntropyCombined(X, Y, length) + HuffmanCostCombined(X, Y, length);
264 // Estimates the Entropy + Huffman + other block overhead size cost.
265 double VP8LHistogramEstimateBits(const VP8LHistogram* const p) {
266 return
267 PopulationCost(p->literal_, VP8LHistogramNumCodes(p->palette_code_bits_))
268 + PopulationCost(p->red_, NUM_LITERAL_CODES)
269 + PopulationCost(p->blue_, NUM_LITERAL_CODES)
270 + PopulationCost(p->alpha_, NUM_LITERAL_CODES)
271 + PopulationCost(p->distance_, NUM_DISTANCE_CODES)
272 + VP8LExtraCost(p->literal_ + NUM_LITERAL_CODES, NUM_LENGTH_CODES)
273 + VP8LExtraCost(p->distance_, NUM_DISTANCE_CODES);
276 double VP8LHistogramEstimateBitsBulk(const VP8LHistogram* const p) {
277 return
278 BitsEntropy(p->literal_, VP8LHistogramNumCodes(p->palette_code_bits_))
279 + BitsEntropy(p->red_, NUM_LITERAL_CODES)
280 + BitsEntropy(p->blue_, NUM_LITERAL_CODES)
281 + BitsEntropy(p->alpha_, NUM_LITERAL_CODES)
282 + BitsEntropy(p->distance_, NUM_DISTANCE_CODES)
283 + VP8LExtraCost(p->literal_ + NUM_LITERAL_CODES, NUM_LENGTH_CODES)
284 + VP8LExtraCost(p->distance_, NUM_DISTANCE_CODES);
287 // -----------------------------------------------------------------------------
288 // Various histogram combine/cost-eval functions
290 static int GetCombinedHistogramEntropy(const VP8LHistogram* const a,
291 const VP8LHistogram* const b,
292 double cost_threshold,
293 double* cost) {
294 const int palette_code_bits = a->palette_code_bits_;
295 assert(a->palette_code_bits_ == b->palette_code_bits_);
296 *cost += GetCombinedEntropy(a->literal_, b->literal_,
297 VP8LHistogramNumCodes(palette_code_bits));
298 *cost += VP8LExtraCostCombined(a->literal_ + NUM_LITERAL_CODES,
299 b->literal_ + NUM_LITERAL_CODES,
300 NUM_LENGTH_CODES);
301 if (*cost > cost_threshold) return 0;
303 *cost += GetCombinedEntropy(a->red_, b->red_, NUM_LITERAL_CODES);
304 if (*cost > cost_threshold) return 0;
306 *cost += GetCombinedEntropy(a->blue_, b->blue_, NUM_LITERAL_CODES);
307 if (*cost > cost_threshold) return 0;
309 *cost += GetCombinedEntropy(a->alpha_, b->alpha_, NUM_LITERAL_CODES);
310 if (*cost > cost_threshold) return 0;
312 *cost += GetCombinedEntropy(a->distance_, b->distance_, NUM_DISTANCE_CODES);
313 *cost += VP8LExtraCostCombined(a->distance_, b->distance_,
314 NUM_DISTANCE_CODES);
315 if (*cost > cost_threshold) return 0;
317 return 1;
320 // Performs out = a + b, computing the cost C(a+b) - C(a) - C(b) while comparing
321 // to the threshold value 'cost_threshold'. The score returned is
322 // Score = C(a+b) - C(a) - C(b), where C(a) + C(b) is known and fixed.
323 // Since the previous score passed is 'cost_threshold', we only need to compare
324 // the partial cost against 'cost_threshold + C(a) + C(b)' to possibly bail-out
325 // early.
326 static double HistogramAddEval(const VP8LHistogram* const a,
327 const VP8LHistogram* const b,
328 VP8LHistogram* const out,
329 double cost_threshold) {
330 double cost = 0;
331 const double sum_cost = a->bit_cost_ + b->bit_cost_;
332 cost_threshold += sum_cost;
334 if (GetCombinedHistogramEntropy(a, b, cost_threshold, &cost)) {
335 VP8LHistogramAdd(a, b, out);
336 out->bit_cost_ = cost;
337 out->palette_code_bits_ = a->palette_code_bits_;
340 return cost - sum_cost;
343 // Same as HistogramAddEval(), except that the resulting histogram
344 // is not stored. Only the cost C(a+b) - C(a) is evaluated. We omit
345 // the term C(b) which is constant over all the evaluations.
346 static double HistogramAddThresh(const VP8LHistogram* const a,
347 const VP8LHistogram* const b,
348 double cost_threshold) {
349 double cost = -a->bit_cost_;
350 GetCombinedHistogramEntropy(a, b, cost_threshold, &cost);
351 return cost;
354 // -----------------------------------------------------------------------------
356 // The structure to keep track of cost range for the three dominant entropy
357 // symbols.
358 // TODO(skal): Evaluate if float can be used here instead of double for
359 // representing the entropy costs.
360 typedef struct {
361 double literal_max_;
362 double literal_min_;
363 double red_max_;
364 double red_min_;
365 double blue_max_;
366 double blue_min_;
367 } DominantCostRange;
369 static void DominantCostRangeInit(DominantCostRange* const c) {
370 c->literal_max_ = 0.;
371 c->literal_min_ = MAX_COST;
372 c->red_max_ = 0.;
373 c->red_min_ = MAX_COST;
374 c->blue_max_ = 0.;
375 c->blue_min_ = MAX_COST;
378 static void UpdateDominantCostRange(
379 const VP8LHistogram* const h, DominantCostRange* const c) {
380 if (c->literal_max_ < h->literal_cost_) c->literal_max_ = h->literal_cost_;
381 if (c->literal_min_ > h->literal_cost_) c->literal_min_ = h->literal_cost_;
382 if (c->red_max_ < h->red_cost_) c->red_max_ = h->red_cost_;
383 if (c->red_min_ > h->red_cost_) c->red_min_ = h->red_cost_;
384 if (c->blue_max_ < h->blue_cost_) c->blue_max_ = h->blue_cost_;
385 if (c->blue_min_ > h->blue_cost_) c->blue_min_ = h->blue_cost_;
388 static void UpdateHistogramCost(VP8LHistogram* const h) {
389 const double alpha_cost = PopulationCost(h->alpha_, NUM_LITERAL_CODES);
390 const double distance_cost =
391 PopulationCost(h->distance_, NUM_DISTANCE_CODES) +
392 VP8LExtraCost(h->distance_, NUM_DISTANCE_CODES);
393 const int num_codes = VP8LHistogramNumCodes(h->palette_code_bits_);
394 h->literal_cost_ = PopulationCost(h->literal_, num_codes) +
395 VP8LExtraCost(h->literal_ + NUM_LITERAL_CODES,
396 NUM_LENGTH_CODES);
397 h->red_cost_ = PopulationCost(h->red_, NUM_LITERAL_CODES);
398 h->blue_cost_ = PopulationCost(h->blue_, NUM_LITERAL_CODES);
399 h->bit_cost_ = h->literal_cost_ + h->red_cost_ + h->blue_cost_ +
400 alpha_cost + distance_cost;
403 static int GetBinIdForEntropy(double min, double max, double val) {
404 const double range = max - min + 1e-6;
405 const double delta = val - min;
406 return (int)(NUM_PARTITIONS * delta / range);
409 // TODO(vikasa): Evaluate, if there's any correlation between red & blue.
410 static int GetHistoBinIndex(
411 const VP8LHistogram* const h, const DominantCostRange* const c) {
412 const int bin_id =
413 GetBinIdForEntropy(c->blue_min_, c->blue_max_, h->blue_cost_) +
414 NUM_PARTITIONS * GetBinIdForEntropy(c->red_min_, c->red_max_,
415 h->red_cost_) +
416 NUM_PARTITIONS * NUM_PARTITIONS * GetBinIdForEntropy(c->literal_min_,
417 c->literal_max_,
418 h->literal_cost_);
419 assert(bin_id < BIN_SIZE);
420 return bin_id;
423 // Construct the histograms from backward references.
424 static void HistogramBuild(
425 int xsize, int histo_bits, const VP8LBackwardRefs* const backward_refs,
426 VP8LHistogramSet* const image_histo) {
427 int x = 0, y = 0;
428 const int histo_xsize = VP8LSubSampleSize(xsize, histo_bits);
429 VP8LHistogram** const histograms = image_histo->histograms;
430 VP8LRefsCursor c = VP8LRefsCursorInit(backward_refs);
431 assert(histo_bits > 0);
432 // Construct the Histo from a given backward references.
433 while (VP8LRefsCursorOk(&c)) {
434 const PixOrCopy* const v = c.cur_pos;
435 const int ix = (y >> histo_bits) * histo_xsize + (x >> histo_bits);
436 VP8LHistogramAddSinglePixOrCopy(histograms[ix], v);
437 x += PixOrCopyLength(v);
438 while (x >= xsize) {
439 x -= xsize;
440 ++y;
442 VP8LRefsCursorNext(&c);
446 // Copies the histograms and computes its bit_cost.
447 static void HistogramCopyAndAnalyze(
448 VP8LHistogramSet* const orig_histo, VP8LHistogramSet* const image_histo) {
449 int i;
450 const int histo_size = orig_histo->size;
451 VP8LHistogram** const orig_histograms = orig_histo->histograms;
452 VP8LHistogram** const histograms = image_histo->histograms;
453 for (i = 0; i < histo_size; ++i) {
454 VP8LHistogram* const histo = orig_histograms[i];
455 UpdateHistogramCost(histo);
456 // Copy histograms from orig_histo[] to image_histo[].
457 HistogramCopy(histo, histograms[i]);
461 // Partition histograms to different entropy bins for three dominant (literal,
462 // red and blue) symbol costs and compute the histogram aggregate bit_cost.
463 static void HistogramAnalyzeEntropyBin(
464 VP8LHistogramSet* const image_histo, int16_t* const bin_map) {
465 int i;
466 VP8LHistogram** const histograms = image_histo->histograms;
467 const int histo_size = image_histo->size;
468 const int bin_depth = histo_size + 1;
469 DominantCostRange cost_range;
470 DominantCostRangeInit(&cost_range);
472 // Analyze the dominant (literal, red and blue) entropy costs.
473 for (i = 0; i < histo_size; ++i) {
474 VP8LHistogram* const histo = histograms[i];
475 UpdateDominantCostRange(histo, &cost_range);
478 // bin-hash histograms on three of the dominant (literal, red and blue)
479 // symbol costs.
480 for (i = 0; i < histo_size; ++i) {
481 int num_histos;
482 VP8LHistogram* const histo = histograms[i];
483 const int16_t bin_id = (int16_t)GetHistoBinIndex(histo, &cost_range);
484 const int bin_offset = bin_id * bin_depth;
485 // bin_map[n][0] for every bin 'n' maintains the counter for the number of
486 // histograms in that bin.
487 // Get and increment the num_histos in that bin.
488 num_histos = ++bin_map[bin_offset];
489 assert(bin_offset + num_histos < bin_depth * BIN_SIZE);
490 // Add histogram i'th index at num_histos (last) position in the bin_map.
491 bin_map[bin_offset + num_histos] = i;
495 // Compact the histogram set by moving the valid one left in the set to the
496 // head and moving the ones that have been merged to other histograms towards
497 // the end.
498 // TODO(vikasa): Evaluate if this method can be avoided by altering the code
499 // logic of HistogramCombineEntropyBin main loop.
500 static void HistogramCompactBins(VP8LHistogramSet* const image_histo) {
501 int start = 0;
502 int end = image_histo->size - 1;
503 VP8LHistogram** const histograms = image_histo->histograms;
504 while (start < end) {
505 while (start <= end && histograms[start] != NULL &&
506 histograms[start]->bit_cost_ != 0.) {
507 ++start;
509 while (start <= end && histograms[end]->bit_cost_ == 0.) {
510 histograms[end] = NULL;
511 --end;
513 if (start < end) {
514 assert(histograms[start] != NULL);
515 assert(histograms[end] != NULL);
516 HistogramCopy(histograms[end], histograms[start]);
517 histograms[end] = NULL;
518 --end;
521 image_histo->size = end + 1;
524 static void HistogramCombineEntropyBin(VP8LHistogramSet* const image_histo,
525 VP8LHistogram* const histos,
526 int16_t* const bin_map, int bin_depth,
527 double combine_cost_factor) {
528 int bin_id;
529 VP8LHistogram* cur_combo = histos;
530 VP8LHistogram** const histograms = image_histo->histograms;
532 for (bin_id = 0; bin_id < BIN_SIZE; ++bin_id) {
533 const int bin_offset = bin_id * bin_depth;
534 const int num_histos = bin_map[bin_offset];
535 const int idx1 = bin_map[bin_offset + 1];
536 int n;
537 for (n = 2; n <= num_histos; ++n) {
538 const int idx2 = bin_map[bin_offset + n];
539 const double bit_cost_idx2 = histograms[idx2]->bit_cost_;
540 if (bit_cost_idx2 > 0.) {
541 const double bit_cost_thresh = -bit_cost_idx2 * combine_cost_factor;
542 const double curr_cost_diff =
543 HistogramAddEval(histograms[idx1], histograms[idx2],
544 cur_combo, bit_cost_thresh);
545 if (curr_cost_diff < bit_cost_thresh) {
546 HistogramCopy(cur_combo, histograms[idx1]);
547 histograms[idx2]->bit_cost_ = 0.;
552 HistogramCompactBins(image_histo);
555 static uint32_t MyRand(uint32_t *seed) {
556 *seed *= 16807U;
557 if (*seed == 0) {
558 *seed = 1;
560 return *seed;
563 static void HistogramCombine(VP8LHistogramSet* const image_histo,
564 VP8LHistogramSet* const histos, int quality) {
565 int iter;
566 uint32_t seed = 0;
567 int tries_with_no_success = 0;
568 int image_histo_size = image_histo->size;
569 const int iter_mult = (quality < 25) ? 2 : 2 + (quality - 25) / 8;
570 const int outer_iters = image_histo_size * iter_mult;
571 const int num_pairs = image_histo_size / 2;
572 const int num_tries_no_success = outer_iters / 2;
573 const int min_cluster_size = 2;
574 VP8LHistogram** const histograms = image_histo->histograms;
575 VP8LHistogram* cur_combo = histos->histograms[0]; // trial histogram
576 VP8LHistogram* best_combo = histos->histograms[1]; // best histogram so far
578 // Collapse similar histograms in 'image_histo'.
579 for (iter = 0;
580 iter < outer_iters && image_histo_size >= min_cluster_size;
581 ++iter) {
582 double best_cost_diff = 0.;
583 int best_idx1 = -1, best_idx2 = 1;
584 int j;
585 const int num_tries =
586 (num_pairs < image_histo_size) ? num_pairs : image_histo_size;
587 seed += iter;
588 for (j = 0; j < num_tries; ++j) {
589 double curr_cost_diff;
590 // Choose two histograms at random and try to combine them.
591 const uint32_t idx1 = MyRand(&seed) % image_histo_size;
592 const uint32_t tmp = (j & 7) + 1;
593 const uint32_t diff =
594 (tmp < 3) ? tmp : MyRand(&seed) % (image_histo_size - 1);
595 const uint32_t idx2 = (idx1 + diff + 1) % image_histo_size;
596 if (idx1 == idx2) {
597 continue;
600 // Calculate cost reduction on combining.
601 curr_cost_diff = HistogramAddEval(histograms[idx1], histograms[idx2],
602 cur_combo, best_cost_diff);
603 if (curr_cost_diff < best_cost_diff) { // found a better pair?
604 { // swap cur/best combo histograms
605 VP8LHistogram* const tmp_histo = cur_combo;
606 cur_combo = best_combo;
607 best_combo = tmp_histo;
609 best_cost_diff = curr_cost_diff;
610 best_idx1 = idx1;
611 best_idx2 = idx2;
615 if (best_idx1 >= 0) {
616 HistogramCopy(best_combo, histograms[best_idx1]);
617 // swap best_idx2 slot with last one (which is now unused)
618 --image_histo_size;
619 if (best_idx2 != image_histo_size) {
620 HistogramCopy(histograms[image_histo_size], histograms[best_idx2]);
621 histograms[image_histo_size] = NULL;
623 tries_with_no_success = 0;
625 if (++tries_with_no_success >= num_tries_no_success) {
626 break;
629 image_histo->size = image_histo_size;
632 // -----------------------------------------------------------------------------
633 // Histogram refinement
635 // Find the best 'out' histogram for each of the 'in' histograms.
636 // Note: we assume that out[]->bit_cost_ is already up-to-date.
637 static void HistogramRemap(const VP8LHistogramSet* const orig_histo,
638 const VP8LHistogramSet* const image_histo,
639 uint16_t* const symbols) {
640 int i;
641 VP8LHistogram** const orig_histograms = orig_histo->histograms;
642 VP8LHistogram** const histograms = image_histo->histograms;
643 for (i = 0; i < orig_histo->size; ++i) {
644 int best_out = 0;
645 double best_bits =
646 HistogramAddThresh(histograms[0], orig_histograms[i], MAX_COST);
647 int k;
648 for (k = 1; k < image_histo->size; ++k) {
649 const double cur_bits =
650 HistogramAddThresh(histograms[k], orig_histograms[i], best_bits);
651 if (cur_bits < best_bits) {
652 best_bits = cur_bits;
653 best_out = k;
656 symbols[i] = best_out;
659 // Recompute each out based on raw and symbols.
660 for (i = 0; i < image_histo->size; ++i) {
661 HistogramClear(histograms[i]);
664 for (i = 0; i < orig_histo->size; ++i) {
665 const int idx = symbols[i];
666 VP8LHistogramAdd(orig_histograms[i], histograms[idx], histograms[idx]);
670 static double GetCombineCostFactor(int histo_size, int quality) {
671 double combine_cost_factor = 0.16;
672 if (histo_size > 256) combine_cost_factor /= 2.;
673 if (histo_size > 512) combine_cost_factor /= 2.;
674 if (histo_size > 1024) combine_cost_factor /= 2.;
675 if (quality <= 50) combine_cost_factor /= 2.;
676 return combine_cost_factor;
679 int VP8LGetHistoImageSymbols(int xsize, int ysize,
680 const VP8LBackwardRefs* const refs,
681 int quality, int histo_bits, int cache_bits,
682 VP8LHistogramSet* const image_histo,
683 uint16_t* const histogram_symbols) {
684 int ok = 0;
685 const int histo_xsize = histo_bits ? VP8LSubSampleSize(xsize, histo_bits) : 1;
686 const int histo_ysize = histo_bits ? VP8LSubSampleSize(ysize, histo_bits) : 1;
687 const int image_histo_raw_size = histo_xsize * histo_ysize;
689 // The bin_map for every bin follows following semantics:
690 // bin_map[n][0] = num_histo; // The number of histograms in that bin.
691 // bin_map[n][1] = index of first histogram in that bin;
692 // bin_map[n][num_histo] = index of last histogram in that bin;
693 // bin_map[n][num_histo + 1] ... bin_map[n][bin_depth - 1] = un-used indices.
694 const int bin_depth = image_histo_raw_size + 1;
695 int16_t* bin_map = NULL;
696 VP8LHistogramSet* const histos = VP8LAllocateHistogramSet(2, cache_bits);
697 VP8LHistogramSet* const orig_histo =
698 VP8LAllocateHistogramSet(image_histo_raw_size, cache_bits);
700 if (orig_histo == NULL || histos == NULL) {
701 goto Error;
704 // Don't attempt linear bin-partition heuristic for:
705 // histograms of small sizes, as bin_map will be very sparse and;
706 // Higher qualities (> 90), to preserve the compression gains at those
707 // quality settings.
708 if (orig_histo->size > 2 * BIN_SIZE && quality < 90) {
709 const int bin_map_size = bin_depth * BIN_SIZE;
710 bin_map = (int16_t*)WebPSafeCalloc(bin_map_size, sizeof(*bin_map));
711 if (bin_map == NULL) goto Error;
714 // Construct the histograms from backward references.
715 HistogramBuild(xsize, histo_bits, refs, orig_histo);
716 // Copies the histograms and computes its bit_cost.
717 HistogramCopyAndAnalyze(orig_histo, image_histo);
719 if (bin_map != NULL) {
720 const double combine_cost_factor =
721 GetCombineCostFactor(image_histo_raw_size, quality);
722 HistogramAnalyzeEntropyBin(orig_histo, bin_map);
723 // Collapse histograms with similar entropy.
724 HistogramCombineEntropyBin(image_histo, histos->histograms[0],
725 bin_map, bin_depth, combine_cost_factor);
728 // Collapse similar histograms by random histogram-pair compares.
729 HistogramCombine(image_histo, histos, quality);
731 // Find the optimal map from original histograms to the final ones.
732 HistogramRemap(orig_histo, image_histo, histogram_symbols);
734 ok = 1;
736 Error:
737 WebPSafeFree(bin_map);
738 VP8LFreeHistogramSet(orig_histo);
739 VP8LFreeHistogramSet(histos);
740 return ok;