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)
11//
12#ifdef HAVE_CONFIG_H
13#include "src/webp/config.h"
14#endif
15
16#include <math.h>
17
18#include "src/enc/backward_references_enc.h"
19#include "src/enc/histogram_enc.h"
20#include "src/dsp/lossless.h"
21#include "src/dsp/lossless_common.h"
22#include "src/utils/utils.h"
23
24#define MAX_COST 1.e38
25
26// Number of partitions for the three dominant (literal, red and blue) symbol
27// costs.
28#define NUM_PARTITIONS 4
29// The size of the bin-hash corresponding to the three dominant costs.
30#define BIN_SIZE (NUM_PARTITIONS * NUM_PARTITIONS * NUM_PARTITIONS)
31// Maximum number of histograms allowed in greedy combining algorithm.
32#define MAX_HISTO_GREEDY 100
33
34static void HistogramClear(VP8LHistogram* const p) {
35 uint32_t* const literal = p->literal_;
36 const int cache_bits = p->palette_code_bits_;
37 const int histo_size = VP8LGetHistogramSize(cache_bits);
38 memset(p, 0, histo_size);
39 p->palette_code_bits_ = cache_bits;
40 p->literal_ = literal;
41}
42
43// Swap two histogram pointers.
44static void HistogramSwap(VP8LHistogram** const A, VP8LHistogram** const B) {
45 VP8LHistogram* const tmp = *A;
46 *A = *B;
47 *B = tmp;
48}
49
50static void HistogramCopy(const VP8LHistogram* const src,
51 VP8LHistogram* const dst) {
52 uint32_t* const dst_literal = dst->literal_;
53 const int dst_cache_bits = dst->palette_code_bits_;
54 const int literal_size = VP8LHistogramNumCodes(dst_cache_bits);
55 const int histo_size = VP8LGetHistogramSize(dst_cache_bits);
56 assert(src->palette_code_bits_ == dst_cache_bits);
57 memcpy(dst, src, histo_size);
58 dst->literal_ = dst_literal;
59 memcpy(dst->literal_, src->literal_, literal_size * sizeof(*dst->literal_));
60}
61
62int VP8LGetHistogramSize(int cache_bits) {
63 const int literal_size = VP8LHistogramNumCodes(cache_bits);
64 const size_t total_size = sizeof(VP8LHistogram) + sizeof(int) * literal_size;
65 assert(total_size <= (size_t)0x7fffffff);
66 return (int)total_size;
67}
68
69void VP8LFreeHistogram(VP8LHistogram* const histo) {
70 WebPSafeFree(histo);
71}
72
73void VP8LFreeHistogramSet(VP8LHistogramSet* const histo) {
74 WebPSafeFree(histo);
75}
76
77void VP8LHistogramStoreRefs(const VP8LBackwardRefs* const refs,
78 VP8LHistogram* const histo) {
79 VP8LRefsCursor c = VP8LRefsCursorInit(refs);
80 while (VP8LRefsCursorOk(&c)) {
81 VP8LHistogramAddSinglePixOrCopy(histo, c.cur_pos, NULL, 0);
82 VP8LRefsCursorNext(&c);
83 }
84}
85
86void VP8LHistogramCreate(VP8LHistogram* const p,
87 const VP8LBackwardRefs* const refs,
88 int palette_code_bits) {
89 if (palette_code_bits >= 0) {
90 p->palette_code_bits_ = palette_code_bits;
91 }
92 HistogramClear(p);
93 VP8LHistogramStoreRefs(refs, p);
94}
95
96void VP8LHistogramInit(VP8LHistogram* const p, int palette_code_bits,
97 int init_arrays) {
98 p->palette_code_bits_ = palette_code_bits;
99 if (init_arrays) {
100 HistogramClear(p);
101 } else {
102 p->trivial_symbol_ = 0;
103 p->bit_cost_ = 0.;
104 p->literal_cost_ = 0.;
105 p->red_cost_ = 0.;
106 p->blue_cost_ = 0.;
107 memset(p->is_used_, 0, sizeof(p->is_used_));
108 }
109}
110
111VP8LHistogram* VP8LAllocateHistogram(int cache_bits) {
112 VP8LHistogram* histo = NULL;
113 const int total_size = VP8LGetHistogramSize(cache_bits);
114 uint8_t* const memory = (uint8_t*)WebPSafeMalloc(total_size, sizeof(*memory));
115 if (memory == NULL) return NULL;
116 histo = (VP8LHistogram*)memory;
117 // literal_ won't necessary be aligned.
118 histo->literal_ = (uint32_t*)(memory + sizeof(VP8LHistogram));
119 VP8LHistogramInit(histo, cache_bits, /*init_arrays=*/ 0);
120 return histo;
121}
122
123// Resets the pointers of the histograms to point to the bit buffer in the set.
124static void HistogramSetResetPointers(VP8LHistogramSet* const set,
125 int cache_bits) {
126 int i;
127 const int histo_size = VP8LGetHistogramSize(cache_bits);
128 uint8_t* memory = (uint8_t*) (set->histograms);
129 memory += set->max_size * sizeof(*set->histograms);
130 for (i = 0; i < set->max_size; ++i) {
131 memory = (uint8_t*) WEBP_ALIGN(memory);
132 set->histograms[i] = (VP8LHistogram*) memory;
133 // literal_ won't necessary be aligned.
134 set->histograms[i]->literal_ = (uint32_t*)(memory + sizeof(VP8LHistogram));
135 memory += histo_size;
136 }
137}
138
139// Returns the total size of the VP8LHistogramSet.
140static size_t HistogramSetTotalSize(int size, int cache_bits) {
141 const int histo_size = VP8LGetHistogramSize(cache_bits);
142 return (sizeof(VP8LHistogramSet) + size * (sizeof(VP8LHistogram*) +
143 histo_size + WEBP_ALIGN_CST));
144}
145
146VP8LHistogramSet* VP8LAllocateHistogramSet(int size, int cache_bits) {
147 int i;
148 VP8LHistogramSet* set;
149 const size_t total_size = HistogramSetTotalSize(size, cache_bits);
150 uint8_t* memory = (uint8_t*)WebPSafeMalloc(total_size, sizeof(*memory));
151 if (memory == NULL) return NULL;
152
153 set = (VP8LHistogramSet*)memory;
154 memory += sizeof(*set);
155 set->histograms = (VP8LHistogram**)memory;
156 set->max_size = size;
157 set->size = size;
158 HistogramSetResetPointers(set, cache_bits);
159 for (i = 0; i < size; ++i) {
160 VP8LHistogramInit(set->histograms[i], cache_bits, /*init_arrays=*/ 0);
161 }
162 return set;
163}
164
165void VP8LHistogramSetClear(VP8LHistogramSet* const set) {
166 int i;
167 const int cache_bits = set->histograms[0]->palette_code_bits_;
168 const int size = set->max_size;
169 const size_t total_size = HistogramSetTotalSize(size, cache_bits);
170 uint8_t* memory = (uint8_t*)set;
171
172 memset(memory, 0, total_size);
173 memory += sizeof(*set);
174 set->histograms = (VP8LHistogram**)memory;
175 set->max_size = size;
176 set->size = size;
177 HistogramSetResetPointers(set, cache_bits);
178 for (i = 0; i < size; ++i) {
179 set->histograms[i]->palette_code_bits_ = cache_bits;
180 }
181}
182
183// Removes the histogram 'i' from 'set' by setting it to NULL.
184static void HistogramSetRemoveHistogram(VP8LHistogramSet* const set, int i,
185 int* const num_used) {
186 assert(set->histograms[i] != NULL);
187 set->histograms[i] = NULL;
188 --*num_used;
189 // If we remove the last valid one, shrink until the next valid one.
190 if (i == set->size - 1) {
191 while (set->size >= 1 && set->histograms[set->size - 1] == NULL) {
192 --set->size;
193 }
194 }
195}
196
197// -----------------------------------------------------------------------------
198
199void VP8LHistogramAddSinglePixOrCopy(VP8LHistogram* const histo,
200 const PixOrCopy* const v,
201 int (*const distance_modifier)(int, int),
202 int distance_modifier_arg0) {
203 if (PixOrCopyIsLiteral(v)) {
204 ++histo->alpha_[PixOrCopyLiteral(v, 3)];
205 ++histo->red_[PixOrCopyLiteral(v, 2)];
206 ++histo->literal_[PixOrCopyLiteral(v, 1)];
207 ++histo->blue_[PixOrCopyLiteral(v, 0)];
208 } else if (PixOrCopyIsCacheIdx(v)) {
209 const int literal_ix =
210 NUM_LITERAL_CODES + NUM_LENGTH_CODES + PixOrCopyCacheIdx(v);
211 ++histo->literal_[literal_ix];
212 } else {
213 int code, extra_bits;
214 VP8LPrefixEncodeBits(PixOrCopyLength(v), &code, &extra_bits);
215 ++histo->literal_[NUM_LITERAL_CODES + code];
216 if (distance_modifier == NULL) {
217 VP8LPrefixEncodeBits(PixOrCopyDistance(v), &code, &extra_bits);
218 } else {
219 VP8LPrefixEncodeBits(
220 distance_modifier(distance_modifier_arg0, PixOrCopyDistance(v)),
221 &code, &extra_bits);
222 }
223 ++histo->distance_[code];
224 }
225}
226
227// -----------------------------------------------------------------------------
228// Entropy-related functions.
229
230static WEBP_INLINE double BitsEntropyRefine(const VP8LBitEntropy* entropy) {
231 double mix;
232 if (entropy->nonzeros < 5) {
233 if (entropy->nonzeros <= 1) {
234 return 0;
235 }
236 // Two symbols, they will be 0 and 1 in a Huffman code.
237 // Let's mix in a bit of entropy to favor good clustering when
238 // distributions of these are combined.
239 if (entropy->nonzeros == 2) {
240 return 0.99 * entropy->sum + 0.01 * entropy->entropy;
241 }
242 // No matter what the entropy says, we cannot be better than min_limit
243 // with Huffman coding. I am mixing a bit of entropy into the
244 // min_limit since it produces much better (~0.5 %) compression results
245 // perhaps because of better entropy clustering.
246 if (entropy->nonzeros == 3) {
247 mix = 0.95;
248 } else {
249 mix = 0.7; // nonzeros == 4.
250 }
251 } else {
252 mix = 0.627;
253 }
254
255 {
256 double min_limit = 2 * entropy->sum - entropy->max_val;
257 min_limit = mix * min_limit + (1.0 - mix) * entropy->entropy;
258 return (entropy->entropy < min_limit) ? min_limit : entropy->entropy;
259 }
260}
261
262double VP8LBitsEntropy(const uint32_t* const array, int n) {
263 VP8LBitEntropy entropy;
264 VP8LBitsEntropyUnrefined(array, n, &entropy);
265
266 return BitsEntropyRefine(&entropy);
267}
268
269static double InitialHuffmanCost(void) {
270 // Small bias because Huffman code length is typically not stored in
271 // full length.
272 static const int kHuffmanCodeOfHuffmanCodeSize = CODE_LENGTH_CODES * 3;
273 static const double kSmallBias = 9.1;
274 return kHuffmanCodeOfHuffmanCodeSize - kSmallBias;
275}
276
277// Finalize the Huffman cost based on streak numbers and length type (<3 or >=3)
278static double FinalHuffmanCost(const VP8LStreaks* const stats) {
279 // The constants in this function are experimental and got rounded from
280 // their original values in 1/8 when switched to 1/1024.
281 double retval = InitialHuffmanCost();
282 // Second coefficient: Many zeros in the histogram are covered efficiently
283 // by a run-length encode. Originally 2/8.
284 retval += stats->counts[0] * 1.5625 + 0.234375 * stats->streaks[0][1];
285 // Second coefficient: Constant values are encoded less efficiently, but still
286 // RLE'ed. Originally 6/8.
287 retval += stats->counts[1] * 2.578125 + 0.703125 * stats->streaks[1][1];
288 // 0s are usually encoded more efficiently than non-0s.
289 // Originally 15/8.
290 retval += 1.796875 * stats->streaks[0][0];
291 // Originally 26/8.
292 retval += 3.28125 * stats->streaks[1][0];
293 return retval;
294}
295
296// Get the symbol entropy for the distribution 'population'.
297// Set 'trivial_sym', if there's only one symbol present in the distribution.
298static double PopulationCost(const uint32_t* const population, int length,
299 uint32_t* const trivial_sym,
300 uint8_t* const is_used) {
301 VP8LBitEntropy bit_entropy;
302 VP8LStreaks stats;
303 VP8LGetEntropyUnrefined(population, length, &bit_entropy, &stats);
304 if (trivial_sym != NULL) {
305 *trivial_sym = (bit_entropy.nonzeros == 1) ? bit_entropy.nonzero_code
306 : VP8L_NON_TRIVIAL_SYM;
307 }
308 // The histogram is used if there is at least one non-zero streak.
309 *is_used = (stats.streaks[1][0] != 0 || stats.streaks[1][1] != 0);
310
311 return BitsEntropyRefine(&bit_entropy) + FinalHuffmanCost(&stats);
312}
313
314// trivial_at_end is 1 if the two histograms only have one element that is
315// non-zero: both the zero-th one, or both the last one.
316static WEBP_INLINE double GetCombinedEntropy(const uint32_t* const X,
317 const uint32_t* const Y,
318 int length, int is_X_used,
319 int is_Y_used,
320 int trivial_at_end) {
321 VP8LStreaks stats;
322 if (trivial_at_end) {
323 // This configuration is due to palettization that transforms an indexed
324 // pixel into 0xff000000 | (pixel << 8) in VP8LBundleColorMap.
325 // BitsEntropyRefine is 0 for histograms with only one non-zero value.
326 // Only FinalHuffmanCost needs to be evaluated.
327 memset(&stats, 0, sizeof(stats));
328 // Deal with the non-zero value at index 0 or length-1.
329 stats.streaks[1][0] = 1;
330 // Deal with the following/previous zero streak.
331 stats.counts[0] = 1;
332 stats.streaks[0][1] = length - 1;
333 return FinalHuffmanCost(&stats);
334 } else {
335 VP8LBitEntropy bit_entropy;
336 if (is_X_used) {
337 if (is_Y_used) {
338 VP8LGetCombinedEntropyUnrefined(X, Y, length, &bit_entropy, &stats);
339 } else {
340 VP8LGetEntropyUnrefined(X, length, &bit_entropy, &stats);
341 }
342 } else {
343 if (is_Y_used) {
344 VP8LGetEntropyUnrefined(Y, length, &bit_entropy, &stats);
345 } else {
346 memset(&stats, 0, sizeof(stats));
347 stats.counts[0] = 1;
348 stats.streaks[0][length > 3] = length;
349 VP8LBitEntropyInit(&bit_entropy);
350 }
351 }
352
353 return BitsEntropyRefine(&bit_entropy) + FinalHuffmanCost(&stats);
354 }
355}
356
357// Estimates the Entropy + Huffman + other block overhead size cost.
358double VP8LHistogramEstimateBits(VP8LHistogram* const p) {
359 return
360 PopulationCost(p->literal_, VP8LHistogramNumCodes(p->palette_code_bits_),
361 NULL, &p->is_used_[0])
362 + PopulationCost(p->red_, NUM_LITERAL_CODES, NULL, &p->is_used_[1])
363 + PopulationCost(p->blue_, NUM_LITERAL_CODES, NULL, &p->is_used_[2])
364 + PopulationCost(p->alpha_, NUM_LITERAL_CODES, NULL, &p->is_used_[3])
365 + PopulationCost(p->distance_, NUM_DISTANCE_CODES, NULL, &p->is_used_[4])
366 + VP8LExtraCost(p->literal_ + NUM_LITERAL_CODES, NUM_LENGTH_CODES)
367 + VP8LExtraCost(p->distance_, NUM_DISTANCE_CODES);
368}
369
370// -----------------------------------------------------------------------------
371// Various histogram combine/cost-eval functions
372
373static int GetCombinedHistogramEntropy(const VP8LHistogram* const a,
374 const VP8LHistogram* const b,
375 double cost_threshold,
376 double* cost) {
377 const int palette_code_bits = a->palette_code_bits_;
378 int trivial_at_end = 0;
379 assert(a->palette_code_bits_ == b->palette_code_bits_);
380 *cost += GetCombinedEntropy(a->literal_, b->literal_,
381 VP8LHistogramNumCodes(palette_code_bits),
382 a->is_used_[0], b->is_used_[0], 0);
383 *cost += VP8LExtraCostCombined(a->literal_ + NUM_LITERAL_CODES,
384 b->literal_ + NUM_LITERAL_CODES,
385 NUM_LENGTH_CODES);
386 if (*cost > cost_threshold) return 0;
387
388 if (a->trivial_symbol_ != VP8L_NON_TRIVIAL_SYM &&
389 a->trivial_symbol_ == b->trivial_symbol_) {
390 // A, R and B are all 0 or 0xff.
391 const uint32_t color_a = (a->trivial_symbol_ >> 24) & 0xff;
392 const uint32_t color_r = (a->trivial_symbol_ >> 16) & 0xff;
393 const uint32_t color_b = (a->trivial_symbol_ >> 0) & 0xff;
394 if ((color_a == 0 || color_a == 0xff) &&
395 (color_r == 0 || color_r == 0xff) &&
396 (color_b == 0 || color_b == 0xff)) {
397 trivial_at_end = 1;
398 }
399 }
400
401 *cost +=
402 GetCombinedEntropy(a->red_, b->red_, NUM_LITERAL_CODES, a->is_used_[1],
403 b->is_used_[1], trivial_at_end);
404 if (*cost > cost_threshold) return 0;
405
406 *cost +=
407 GetCombinedEntropy(a->blue_, b->blue_, NUM_LITERAL_CODES, a->is_used_[2],
408 b->is_used_[2], trivial_at_end);
409 if (*cost > cost_threshold) return 0;
410
411 *cost +=
412 GetCombinedEntropy(a->alpha_, b->alpha_, NUM_LITERAL_CODES,
413 a->is_used_[3], b->is_used_[3], trivial_at_end);
414 if (*cost > cost_threshold) return 0;
415
416 *cost +=
417 GetCombinedEntropy(a->distance_, b->distance_, NUM_DISTANCE_CODES,
418 a->is_used_[4], b->is_used_[4], 0);
419 *cost +=
420 VP8LExtraCostCombined(a->distance_, b->distance_, NUM_DISTANCE_CODES);
421 if (*cost > cost_threshold) return 0;
422
423 return 1;
424}
425
426static WEBP_INLINE void HistogramAdd(const VP8LHistogram* const a,
427 const VP8LHistogram* const b,
428 VP8LHistogram* const out) {
429 VP8LHistogramAdd(a, b, out);
430 out->trivial_symbol_ = (a->trivial_symbol_ == b->trivial_symbol_)
431 ? a->trivial_symbol_
432 : VP8L_NON_TRIVIAL_SYM;
433}
434
435// Performs out = a + b, computing the cost C(a+b) - C(a) - C(b) while comparing
436// to the threshold value 'cost_threshold'. The score returned is
437// Score = C(a+b) - C(a) - C(b), where C(a) + C(b) is known and fixed.
438// Since the previous score passed is 'cost_threshold', we only need to compare
439// the partial cost against 'cost_threshold + C(a) + C(b)' to possibly bail-out
440// early.
441static double HistogramAddEval(const VP8LHistogram* const a,
442 const VP8LHistogram* const b,
443 VP8LHistogram* const out,
444 double cost_threshold) {
445 double cost = 0;
446 const double sum_cost = a->bit_cost_ + b->bit_cost_;
447 cost_threshold += sum_cost;
448
449 if (GetCombinedHistogramEntropy(a, b, cost_threshold, &cost)) {
450 HistogramAdd(a, b, out);
451 out->bit_cost_ = cost;
452 out->palette_code_bits_ = a->palette_code_bits_;
453 }
454
455 return cost - sum_cost;
456}
457
458// Same as HistogramAddEval(), except that the resulting histogram
459// is not stored. Only the cost C(a+b) - C(a) is evaluated. We omit
460// the term C(b) which is constant over all the evaluations.
461static double HistogramAddThresh(const VP8LHistogram* const a,
462 const VP8LHistogram* const b,
463 double cost_threshold) {
464 double cost;
465 assert(a != NULL && b != NULL);
466 cost = -a->bit_cost_;
467 GetCombinedHistogramEntropy(a, b, cost_threshold, &cost);
468 return cost;
469}
470
471// -----------------------------------------------------------------------------
472
473// The structure to keep track of cost range for the three dominant entropy
474// symbols.
475// TODO(skal): Evaluate if float can be used here instead of double for
476// representing the entropy costs.
477typedef struct {
478 double literal_max_;
479 double literal_min_;
480 double red_max_;
481 double red_min_;
482 double blue_max_;
483 double blue_min_;
484} DominantCostRange;
485
486static void DominantCostRangeInit(DominantCostRange* const c) {
487 c->literal_max_ = 0.;
488 c->literal_min_ = MAX_COST;
489 c->red_max_ = 0.;
490 c->red_min_ = MAX_COST;
491 c->blue_max_ = 0.;
492 c->blue_min_ = MAX_COST;
493}
494
495static void UpdateDominantCostRange(
496 const VP8LHistogram* const h, DominantCostRange* const c) {
497 if (c->literal_max_ < h->literal_cost_) c->literal_max_ = h->literal_cost_;
498 if (c->literal_min_ > h->literal_cost_) c->literal_min_ = h->literal_cost_;
499 if (c->red_max_ < h->red_cost_) c->red_max_ = h->red_cost_;
500 if (c->red_min_ > h->red_cost_) c->red_min_ = h->red_cost_;
501 if (c->blue_max_ < h->blue_cost_) c->blue_max_ = h->blue_cost_;
502 if (c->blue_min_ > h->blue_cost_) c->blue_min_ = h->blue_cost_;
503}
504
505static void UpdateHistogramCost(VP8LHistogram* const h) {
506 uint32_t alpha_sym, red_sym, blue_sym;
507 const double alpha_cost =
508 PopulationCost(h->alpha_, NUM_LITERAL_CODES, &alpha_sym,
509 &h->is_used_[3]);
510 const double distance_cost =
511 PopulationCost(h->distance_, NUM_DISTANCE_CODES, NULL, &h->is_used_[4]) +
512 VP8LExtraCost(h->distance_, NUM_DISTANCE_CODES);
513 const int num_codes = VP8LHistogramNumCodes(h->palette_code_bits_);
514 h->literal_cost_ =
515 PopulationCost(h->literal_, num_codes, NULL, &h->is_used_[0]) +
516 VP8LExtraCost(h->literal_ + NUM_LITERAL_CODES, NUM_LENGTH_CODES);
517 h->red_cost_ =
518 PopulationCost(h->red_, NUM_LITERAL_CODES, &red_sym, &h->is_used_[1]);
519 h->blue_cost_ =
520 PopulationCost(h->blue_, NUM_LITERAL_CODES, &blue_sym, &h->is_used_[2]);
521 h->bit_cost_ = h->literal_cost_ + h->red_cost_ + h->blue_cost_ +
522 alpha_cost + distance_cost;
523 if ((alpha_sym | red_sym | blue_sym) == VP8L_NON_TRIVIAL_SYM) {
524 h->trivial_symbol_ = VP8L_NON_TRIVIAL_SYM;
525 } else {
526 h->trivial_symbol_ =
527 ((uint32_t)alpha_sym << 24) | (red_sym << 16) | (blue_sym << 0);
528 }
529}
530
531static int GetBinIdForEntropy(double min, double max, double val) {
532 const double range = max - min;
533 if (range > 0.) {
534 const double delta = val - min;
535 return (int)((NUM_PARTITIONS - 1e-6) * delta / range);
536 } else {
537 return 0;
538 }
539}
540
541static int GetHistoBinIndex(const VP8LHistogram* const h,
542 const DominantCostRange* const c, int low_effort) {
543 int bin_id = GetBinIdForEntropy(c->literal_min_, c->literal_max_,
544 h->literal_cost_);
545 assert(bin_id < NUM_PARTITIONS);
546 if (!low_effort) {
547 bin_id = bin_id * NUM_PARTITIONS
548 + GetBinIdForEntropy(c->red_min_, c->red_max_, h->red_cost_);
549 bin_id = bin_id * NUM_PARTITIONS
550 + GetBinIdForEntropy(c->blue_min_, c->blue_max_, h->blue_cost_);
551 assert(bin_id < BIN_SIZE);
552 }
553 return bin_id;
554}
555
556// Construct the histograms from backward references.
557static void HistogramBuild(
558 int xsize, int histo_bits, const VP8LBackwardRefs* const backward_refs,
559 VP8LHistogramSet* const image_histo) {
560 int x = 0, y = 0;
561 const int histo_xsize = VP8LSubSampleSize(xsize, histo_bits);
562 VP8LHistogram** const histograms = image_histo->histograms;
563 VP8LRefsCursor c = VP8LRefsCursorInit(backward_refs);
564 assert(histo_bits > 0);
565 VP8LHistogramSetClear(image_histo);
566 while (VP8LRefsCursorOk(&c)) {
567 const PixOrCopy* const v = c.cur_pos;
568 const int ix = (y >> histo_bits) * histo_xsize + (x >> histo_bits);
569 VP8LHistogramAddSinglePixOrCopy(histograms[ix], v, NULL, 0);
570 x += PixOrCopyLength(v);
571 while (x >= xsize) {
572 x -= xsize;
573 ++y;
574 }
575 VP8LRefsCursorNext(&c);
576 }
577}
578
579// Copies the histograms and computes its bit_cost.
580static const uint16_t kInvalidHistogramSymbol = (uint16_t)(-1);
581static void HistogramCopyAndAnalyze(VP8LHistogramSet* const orig_histo,
582 VP8LHistogramSet* const image_histo,
583 int* const num_used,
584 uint16_t* const histogram_symbols) {
585 int i, cluster_id;
586 int num_used_orig = *num_used;
587 VP8LHistogram** const orig_histograms = orig_histo->histograms;
588 VP8LHistogram** const histograms = image_histo->histograms;
589 assert(image_histo->max_size == orig_histo->max_size);
590 for (cluster_id = 0, i = 0; i < orig_histo->max_size; ++i) {
591 VP8LHistogram* const histo = orig_histograms[i];
592 UpdateHistogramCost(histo);
593
594 // Skip the histogram if it is completely empty, which can happen for tiles
595 // with no information (when they are skipped because of LZ77).
596 if (!histo->is_used_[0] && !histo->is_used_[1] && !histo->is_used_[2]
597 && !histo->is_used_[3] && !histo->is_used_[4]) {
598 // The first histogram is always used. If an histogram is empty, we set
599 // its id to be the same as the previous one: this will improve
600 // compressibility for later LZ77.
601 assert(i > 0);
602 HistogramSetRemoveHistogram(image_histo, i, num_used);
603 HistogramSetRemoveHistogram(orig_histo, i, &num_used_orig);
604 histogram_symbols[i] = kInvalidHistogramSymbol;
605 } else {
606 // Copy histograms from orig_histo[] to image_histo[].
607 HistogramCopy(histo, histograms[i]);
608 histogram_symbols[i] = cluster_id++;
609 assert(cluster_id <= image_histo->max_size);
610 }
611 }
612}
613
614// Partition histograms to different entropy bins for three dominant (literal,
615// red and blue) symbol costs and compute the histogram aggregate bit_cost.
616static void HistogramAnalyzeEntropyBin(VP8LHistogramSet* const image_histo,
617 uint16_t* const bin_map,
618 int low_effort) {
619 int i;
620 VP8LHistogram** const histograms = image_histo->histograms;
621 const int histo_size = image_histo->size;
622 DominantCostRange cost_range;
623 DominantCostRangeInit(&cost_range);
624
625 // Analyze the dominant (literal, red and blue) entropy costs.
626 for (i = 0; i < histo_size; ++i) {
627 if (histograms[i] == NULL) continue;
628 UpdateDominantCostRange(histograms[i], &cost_range);
629 }
630
631 // bin-hash histograms on three of the dominant (literal, red and blue)
632 // symbol costs and store the resulting bin_id for each histogram.
633 for (i = 0; i < histo_size; ++i) {
634 // bin_map[i] is not set to a special value as its use will later be guarded
635 // by another (histograms[i] == NULL).
636 if (histograms[i] == NULL) continue;
637 bin_map[i] = GetHistoBinIndex(histograms[i], &cost_range, low_effort);
638 }
639}
640
641// Merges some histograms with same bin_id together if it's advantageous.
642// Sets the remaining histograms to NULL.
643static void HistogramCombineEntropyBin(VP8LHistogramSet* const image_histo,
644 int* num_used,
645 const uint16_t* const clusters,
646 uint16_t* const cluster_mappings,
647 VP8LHistogram* cur_combo,
648 const uint16_t* const bin_map,
649 int num_bins,
650 double combine_cost_factor,
651 int low_effort) {
652 VP8LHistogram** const histograms = image_histo->histograms;
653 int idx;
654 struct {
655 int16_t first; // position of the histogram that accumulates all
656 // histograms with the same bin_id
657 uint16_t num_combine_failures; // number of combine failures per bin_id
658 } bin_info[BIN_SIZE];
659
660 assert(num_bins <= BIN_SIZE);
661 for (idx = 0; idx < num_bins; ++idx) {
662 bin_info[idx].first = -1;
663 bin_info[idx].num_combine_failures = 0;
664 }
665
666 // By default, a cluster matches itself.
667 for (idx = 0; idx < *num_used; ++idx) cluster_mappings[idx] = idx;
668 for (idx = 0; idx < image_histo->size; ++idx) {
669 int bin_id, first;
670 if (histograms[idx] == NULL) continue;
671 bin_id = bin_map[idx];
672 first = bin_info[bin_id].first;
673 if (first == -1) {
674 bin_info[bin_id].first = idx;
675 } else if (low_effort) {
676 HistogramAdd(histograms[idx], histograms[first], histograms[first]);
677 HistogramSetRemoveHistogram(image_histo, idx, num_used);
678 cluster_mappings[clusters[idx]] = clusters[first];
679 } else {
680 // try to merge #idx into #first (both share the same bin_id)
681 const double bit_cost = histograms[idx]->bit_cost_;
682 const double bit_cost_thresh = -bit_cost * combine_cost_factor;
683 const double curr_cost_diff =
684 HistogramAddEval(histograms[first], histograms[idx],
685 cur_combo, bit_cost_thresh);
686 if (curr_cost_diff < bit_cost_thresh) {
687 // Try to merge two histograms only if the combo is a trivial one or
688 // the two candidate histograms are already non-trivial.
689 // For some images, 'try_combine' turns out to be false for a lot of
690 // histogram pairs. In that case, we fallback to combining
691 // histograms as usual to avoid increasing the header size.
692 const int try_combine =
693 (cur_combo->trivial_symbol_ != VP8L_NON_TRIVIAL_SYM) ||
694 ((histograms[idx]->trivial_symbol_ == VP8L_NON_TRIVIAL_SYM) &&
695 (histograms[first]->trivial_symbol_ == VP8L_NON_TRIVIAL_SYM));
696 const int max_combine_failures = 32;
697 if (try_combine ||
698 bin_info[bin_id].num_combine_failures >= max_combine_failures) {
699 // move the (better) merged histogram to its final slot
700 HistogramSwap(&cur_combo, &histograms[first]);
701 HistogramSetRemoveHistogram(image_histo, idx, num_used);
702 cluster_mappings[clusters[idx]] = clusters[first];
703 } else {
704 ++bin_info[bin_id].num_combine_failures;
705 }
706 }
707 }
708 }
709 if (low_effort) {
710 // for low_effort case, update the final cost when everything is merged
711 for (idx = 0; idx < image_histo->size; ++idx) {
712 if (histograms[idx] == NULL) continue;
713 UpdateHistogramCost(histograms[idx]);
714 }
715 }
716}
717
718// Implement a Lehmer random number generator with a multiplicative constant of
719// 48271 and a modulo constant of 2^31 - 1.
720static uint32_t MyRand(uint32_t* const seed) {
721 *seed = (uint32_t)(((uint64_t)(*seed) * 48271u) % 2147483647u);
722 assert(*seed > 0);
723 return *seed;
724}
725
726// -----------------------------------------------------------------------------
727// Histogram pairs priority queue
728
729// Pair of histograms. Negative idx1 value means that pair is out-of-date.
730typedef struct {
731 int idx1;
732 int idx2;
733 double cost_diff;
734 double cost_combo;
735} HistogramPair;
736
737typedef struct {
738 HistogramPair* queue;
739 int size;
740 int max_size;
741} HistoQueue;
742
743static int HistoQueueInit(HistoQueue* const histo_queue, const int max_size) {
744 histo_queue->size = 0;
745 histo_queue->max_size = max_size;
746 // We allocate max_size + 1 because the last element at index "size" is
747 // used as temporary data (and it could be up to max_size).
748 histo_queue->queue = (HistogramPair*)WebPSafeMalloc(
749 histo_queue->max_size + 1, sizeof(*histo_queue->queue));
750 return histo_queue->queue != NULL;
751}
752
753static void HistoQueueClear(HistoQueue* const histo_queue) {
754 assert(histo_queue != NULL);
755 WebPSafeFree(histo_queue->queue);
756 histo_queue->size = 0;
757 histo_queue->max_size = 0;
758}
759
760// Pop a specific pair in the queue by replacing it with the last one
761// and shrinking the queue.
762static void HistoQueuePopPair(HistoQueue* const histo_queue,
763 HistogramPair* const pair) {
764 assert(pair >= histo_queue->queue &&
765 pair < (histo_queue->queue + histo_queue->size));
766 assert(histo_queue->size > 0);
767 *pair = histo_queue->queue[histo_queue->size - 1];
768 --histo_queue->size;
769}
770
771// Check whether a pair in the queue should be updated as head or not.
772static void HistoQueueUpdateHead(HistoQueue* const histo_queue,
773 HistogramPair* const pair) {
774 assert(pair->cost_diff < 0.);
775 assert(pair >= histo_queue->queue &&
776 pair < (histo_queue->queue + histo_queue->size));
777 assert(histo_queue->size > 0);
778 if (pair->cost_diff < histo_queue->queue[0].cost_diff) {
779 // Replace the best pair.
780 const HistogramPair tmp = histo_queue->queue[0];
781 histo_queue->queue[0] = *pair;
782 *pair = tmp;
783 }
784}
785
786// Update the cost diff and combo of a pair of histograms. This needs to be
787// called when the the histograms have been merged with a third one.
788static void HistoQueueUpdatePair(const VP8LHistogram* const h1,
789 const VP8LHistogram* const h2,
790 double threshold,
791 HistogramPair* const pair) {
792 const double sum_cost = h1->bit_cost_ + h2->bit_cost_;
793 pair->cost_combo = 0.;
794 GetCombinedHistogramEntropy(h1, h2, sum_cost + threshold, &pair->cost_combo);
795 pair->cost_diff = pair->cost_combo - sum_cost;
796}
797
798// Create a pair from indices "idx1" and "idx2" provided its cost
799// is inferior to "threshold", a negative entropy.
800// It returns the cost of the pair, or 0. if it superior to threshold.
801static double HistoQueuePush(HistoQueue* const histo_queue,
802 VP8LHistogram** const histograms, int idx1,
803 int idx2, double threshold) {
804 const VP8LHistogram* h1;
805 const VP8LHistogram* h2;
806 HistogramPair pair;
807
808 // Stop here if the queue is full.
809 if (histo_queue->size == histo_queue->max_size) return 0.;
810 assert(threshold <= 0.);
811 if (idx1 > idx2) {
812 const int tmp = idx2;
813 idx2 = idx1;
814 idx1 = tmp;
815 }
816 pair.idx1 = idx1;
817 pair.idx2 = idx2;
818 h1 = histograms[idx1];
819 h2 = histograms[idx2];
820
821 HistoQueueUpdatePair(h1, h2, threshold, &pair);
822
823 // Do not even consider the pair if it does not improve the entropy.
824 if (pair.cost_diff >= threshold) return 0.;
825
826 histo_queue->queue[histo_queue->size++] = pair;
827 HistoQueueUpdateHead(histo_queue, &histo_queue->queue[histo_queue->size - 1]);
828
829 return pair.cost_diff;
830}
831
832// -----------------------------------------------------------------------------
833
834// Combines histograms by continuously choosing the one with the highest cost
835// reduction.
836static int HistogramCombineGreedy(VP8LHistogramSet* const image_histo,
837 int* const num_used) {
838 int ok = 0;
839 const int image_histo_size = image_histo->size;
840 int i, j;
841 VP8LHistogram** const histograms = image_histo->histograms;
842 // Priority queue of histogram pairs.
843 HistoQueue histo_queue;
844
845 // image_histo_size^2 for the queue size is safe. If you look at
846 // HistogramCombineGreedy, and imagine that UpdateQueueFront always pushes
847 // data to the queue, you insert at most:
848 // - image_histo_size*(image_histo_size-1)/2 (the first two for loops)
849 // - image_histo_size - 1 in the last for loop at the first iteration of
850 // the while loop, image_histo_size - 2 at the second iteration ...
851 // therefore image_histo_size*(image_histo_size-1)/2 overall too
852 if (!HistoQueueInit(&histo_queue, image_histo_size * image_histo_size)) {
853 goto End;
854 }
855
856 for (i = 0; i < image_histo_size; ++i) {
857 if (image_histo->histograms[i] == NULL) continue;
858 for (j = i + 1; j < image_histo_size; ++j) {
859 // Initialize queue.
860 if (image_histo->histograms[j] == NULL) continue;
861 HistoQueuePush(&histo_queue, histograms, i, j, 0.);
862 }
863 }
864
865 while (histo_queue.size > 0) {
866 const int idx1 = histo_queue.queue[0].idx1;
867 const int idx2 = histo_queue.queue[0].idx2;
868 HistogramAdd(histograms[idx2], histograms[idx1], histograms[idx1]);
869 histograms[idx1]->bit_cost_ = histo_queue.queue[0].cost_combo;
870
871 // Remove merged histogram.
872 HistogramSetRemoveHistogram(image_histo, idx2, num_used);
873
874 // Remove pairs intersecting the just combined best pair.
875 for (i = 0; i < histo_queue.size;) {
876 HistogramPair* const p = histo_queue.queue + i;
877 if (p->idx1 == idx1 || p->idx2 == idx1 ||
878 p->idx1 == idx2 || p->idx2 == idx2) {
879 HistoQueuePopPair(&histo_queue, p);
880 } else {
881 HistoQueueUpdateHead(&histo_queue, p);
882 ++i;
883 }
884 }
885
886 // Push new pairs formed with combined histogram to the queue.
887 for (i = 0; i < image_histo->size; ++i) {
888 if (i == idx1 || image_histo->histograms[i] == NULL) continue;
889 HistoQueuePush(&histo_queue, image_histo->histograms, idx1, i, 0.);
890 }
891 }
892
893 ok = 1;
894
895 End:
896 HistoQueueClear(&histo_queue);
897 return ok;
898}
899
900// Perform histogram aggregation using a stochastic approach.
901// 'do_greedy' is set to 1 if a greedy approach needs to be performed
902// afterwards, 0 otherwise.
903static int PairComparison(const void* idx1, const void* idx2) {
904 // To be used with bsearch: <0 when *idx1<*idx2, >0 if >, 0 when ==.
905 return (*(int*) idx1 - *(int*) idx2);
906}
907static int HistogramCombineStochastic(VP8LHistogramSet* const image_histo,
908 int* const num_used, int min_cluster_size,
909 int* const do_greedy) {
910 int j, iter;
911 uint32_t seed = 1;
912 int tries_with_no_success = 0;
913 const int outer_iters = *num_used;
914 const int num_tries_no_success = outer_iters / 2;
915 VP8LHistogram** const histograms = image_histo->histograms;
916 // Priority queue of histogram pairs. Its size of 'kHistoQueueSize'
917 // impacts the quality of the compression and the speed: the smaller the
918 // faster but the worse for the compression.
919 HistoQueue histo_queue;
920 const int kHistoQueueSize = 9;
921 int ok = 0;
922 // mapping from an index in image_histo with no NULL histogram to the full
923 // blown image_histo.
924 int* mappings;
925
926 if (*num_used < min_cluster_size) {
927 *do_greedy = 1;
928 return 1;
929 }
930
931 mappings = (int*) WebPSafeMalloc(*num_used, sizeof(*mappings));
932 if (mappings == NULL) return 0;
933 if (!HistoQueueInit(&histo_queue, kHistoQueueSize)) goto End;
934 // Fill the initial mapping.
935 for (j = 0, iter = 0; iter < image_histo->size; ++iter) {
936 if (histograms[iter] == NULL) continue;
937 mappings[j++] = iter;
938 }
939 assert(j == *num_used);
940
941 // Collapse similar histograms in 'image_histo'.
942 for (iter = 0;
943 iter < outer_iters && *num_used >= min_cluster_size &&
944 ++tries_with_no_success < num_tries_no_success;
945 ++iter) {
946 int* mapping_index;
947 double best_cost =
948 (histo_queue.size == 0) ? 0. : histo_queue.queue[0].cost_diff;
949 int best_idx1 = -1, best_idx2 = 1;
950 const uint32_t rand_range = (*num_used - 1) * (*num_used);
951 // (*num_used) / 2 was chosen empirically. Less means faster but worse
952 // compression.
953 const int num_tries = (*num_used) / 2;
954
955 // Pick random samples.
956 for (j = 0; *num_used >= 2 && j < num_tries; ++j) {
957 double curr_cost;
958 // Choose two different histograms at random and try to combine them.
959 const uint32_t tmp = MyRand(&seed) % rand_range;
960 uint32_t idx1 = tmp / (*num_used - 1);
961 uint32_t idx2 = tmp % (*num_used - 1);
962 if (idx2 >= idx1) ++idx2;
963 idx1 = mappings[idx1];
964 idx2 = mappings[idx2];
965
966 // Calculate cost reduction on combination.
967 curr_cost =
968 HistoQueuePush(&histo_queue, histograms, idx1, idx2, best_cost);
969 if (curr_cost < 0) { // found a better pair?
970 best_cost = curr_cost;
971 // Empty the queue if we reached full capacity.
972 if (histo_queue.size == histo_queue.max_size) break;
973 }
974 }
975 if (histo_queue.size == 0) continue;
976
977 // Get the best histograms.
978 best_idx1 = histo_queue.queue[0].idx1;
979 best_idx2 = histo_queue.queue[0].idx2;
980 assert(best_idx1 < best_idx2);
981 // Pop best_idx2 from mappings.
982 mapping_index = (int*) bsearch(&best_idx2, mappings, *num_used,
983 sizeof(best_idx2), &PairComparison);
984 assert(mapping_index != NULL);
985 memmove(mapping_index, mapping_index + 1, sizeof(*mapping_index) *
986 ((*num_used) - (mapping_index - mappings) - 1));
987 // Merge the histograms and remove best_idx2 from the queue.
988 HistogramAdd(histograms[best_idx2], histograms[best_idx1],
989 histograms[best_idx1]);
990 histograms[best_idx1]->bit_cost_ = histo_queue.queue[0].cost_combo;
991 HistogramSetRemoveHistogram(image_histo, best_idx2, num_used);
992 // Parse the queue and update each pair that deals with best_idx1,
993 // best_idx2 or image_histo_size.
994 for (j = 0; j < histo_queue.size;) {
995 HistogramPair* const p = histo_queue.queue + j;
996 const int is_idx1_best = p->idx1 == best_idx1 || p->idx1 == best_idx2;
997 const int is_idx2_best = p->idx2 == best_idx1 || p->idx2 == best_idx2;
998 int do_eval = 0;
999 // The front pair could have been duplicated by a random pick so
1000 // check for it all the time nevertheless.
1001 if (is_idx1_best && is_idx2_best) {
1002 HistoQueuePopPair(&histo_queue, p);
1003 continue;
1004 }
1005 // Any pair containing one of the two best indices should only refer to
1006 // best_idx1. Its cost should also be updated.
1007 if (is_idx1_best) {
1008 p->idx1 = best_idx1;
1009 do_eval = 1;
1010 } else if (is_idx2_best) {
1011 p->idx2 = best_idx1;
1012 do_eval = 1;
1013 }
1014 // Make sure the index order is respected.
1015 if (p->idx1 > p->idx2) {
1016 const int tmp = p->idx2;
1017 p->idx2 = p->idx1;
1018 p->idx1 = tmp;
1019 }
1020 if (do_eval) {
1021 // Re-evaluate the cost of an updated pair.
1022 HistoQueueUpdatePair(histograms[p->idx1], histograms[p->idx2], 0., p);
1023 if (p->cost_diff >= 0.) {
1024 HistoQueuePopPair(&histo_queue, p);
1025 continue;
1026 }
1027 }
1028 HistoQueueUpdateHead(&histo_queue, p);
1029 ++j;
1030 }
1031 tries_with_no_success = 0;
1032 }
1033 *do_greedy = (*num_used <= min_cluster_size);
1034 ok = 1;
1035
1036End:
1037 HistoQueueClear(&histo_queue);
1038 WebPSafeFree(mappings);
1039 return ok;
1040}
1041
1042// -----------------------------------------------------------------------------
1043// Histogram refinement
1044
1045// Find the best 'out' histogram for each of the 'in' histograms.
1046// At call-time, 'out' contains the histograms of the clusters.
1047// Note: we assume that out[]->bit_cost_ is already up-to-date.
1048static void HistogramRemap(const VP8LHistogramSet* const in,
1049 VP8LHistogramSet* const out,
1050 uint16_t* const symbols) {
1051 int i;
1052 VP8LHistogram** const in_histo = in->histograms;
1053 VP8LHistogram** const out_histo = out->histograms;
1054 const int in_size = out->max_size;
1055 const int out_size = out->size;
1056 if (out_size > 1) {
1057 for (i = 0; i < in_size; ++i) {
1058 int best_out = 0;
1059 double best_bits = MAX_COST;
1060 int k;
1061 if (in_histo[i] == NULL) {
1062 // Arbitrarily set to the previous value if unused to help future LZ77.
1063 symbols[i] = symbols[i - 1];
1064 continue;
1065 }
1066 for (k = 0; k < out_size; ++k) {
1067 double cur_bits;
1068 cur_bits = HistogramAddThresh(out_histo[k], in_histo[i], best_bits);
1069 if (k == 0 || cur_bits < best_bits) {
1070 best_bits = cur_bits;
1071 best_out = k;
1072 }
1073 }
1074 symbols[i] = best_out;
1075 }
1076 } else {
1077 assert(out_size == 1);
1078 for (i = 0; i < in_size; ++i) {
1079 symbols[i] = 0;
1080 }
1081 }
1082
1083 // Recompute each out based on raw and symbols.
1084 VP8LHistogramSetClear(out);
1085 out->size = out_size;
1086
1087 for (i = 0; i < in_size; ++i) {
1088 int idx;
1089 if (in_histo[i] == NULL) continue;
1090 idx = symbols[i];
1091 HistogramAdd(in_histo[i], out_histo[idx], out_histo[idx]);
1092 }
1093}
1094
1095static double GetCombineCostFactor(int histo_size, int quality) {
1096 double combine_cost_factor = 0.16;
1097 if (quality < 90) {
1098 if (histo_size > 256) combine_cost_factor /= 2.;
1099 if (histo_size > 512) combine_cost_factor /= 2.;
1100 if (histo_size > 1024) combine_cost_factor /= 2.;
1101 if (quality <= 50) combine_cost_factor /= 2.;
1102 }
1103 return combine_cost_factor;
1104}
1105
1106// Given a HistogramSet 'set', the mapping of clusters 'cluster_mapping' and the
1107// current assignment of the cells in 'symbols', merge the clusters and
1108// assign the smallest possible clusters values.
1109static void OptimizeHistogramSymbols(const VP8LHistogramSet* const set,
1110 uint16_t* const cluster_mappings,
1111 int num_clusters,
1112 uint16_t* const cluster_mappings_tmp,
1113 uint16_t* const symbols) {
1114 int i, cluster_max;
1115 int do_continue = 1;
1116 // First, assign the lowest cluster to each pixel.
1117 while (do_continue) {
1118 do_continue = 0;
1119 for (i = 0; i < num_clusters; ++i) {
1120 int k;
1121 k = cluster_mappings[i];
1122 while (k != cluster_mappings[k]) {
1123 cluster_mappings[k] = cluster_mappings[cluster_mappings[k]];
1124 k = cluster_mappings[k];
1125 }
1126 if (k != cluster_mappings[i]) {
1127 do_continue = 1;
1128 cluster_mappings[i] = k;
1129 }
1130 }
1131 }
1132 // Create a mapping from a cluster id to its minimal version.
1133 cluster_max = 0;
1134 memset(cluster_mappings_tmp, 0,
1135 set->max_size * sizeof(*cluster_mappings_tmp));
1136 assert(cluster_mappings[0] == 0);
1137 // Re-map the ids.
1138 for (i = 0; i < set->max_size; ++i) {
1139 int cluster;
1140 if (symbols[i] == kInvalidHistogramSymbol) continue;
1141 cluster = cluster_mappings[symbols[i]];
1142 assert(symbols[i] < num_clusters);
1143 if (cluster > 0 && cluster_mappings_tmp[cluster] == 0) {
1144 ++cluster_max;
1145 cluster_mappings_tmp[cluster] = cluster_max;
1146 }
1147 symbols[i] = cluster_mappings_tmp[cluster];
1148 }
1149
1150 // Make sure all cluster values are used.
1151 cluster_max = 0;
1152 for (i = 0; i < set->max_size; ++i) {
1153 if (symbols[i] == kInvalidHistogramSymbol) continue;
1154 if (symbols[i] <= cluster_max) continue;
1155 ++cluster_max;
1156 assert(symbols[i] == cluster_max);
1157 }
1158}
1159
1160static void RemoveEmptyHistograms(VP8LHistogramSet* const image_histo) {
1161 uint32_t size;
1162 int i;
1163 for (i = 0, size = 0; i < image_histo->size; ++i) {
1164 if (image_histo->histograms[i] == NULL) continue;
1165 image_histo->histograms[size++] = image_histo->histograms[i];
1166 }
1167 image_histo->size = size;
1168}
1169
1170int VP8LGetHistoImageSymbols(int xsize, int ysize,
1171 const VP8LBackwardRefs* const refs,
1172 int quality, int low_effort,
1173 int histo_bits, int cache_bits,
1174 VP8LHistogramSet* const image_histo,
1175 VP8LHistogram* const tmp_histo,
1176 uint16_t* const histogram_symbols) {
1177 int ok = 0;
1178 const int histo_xsize = histo_bits ? VP8LSubSampleSize(xsize, histo_bits) : 1;
1179 const int histo_ysize = histo_bits ? VP8LSubSampleSize(ysize, histo_bits) : 1;
1180 const int image_histo_raw_size = histo_xsize * histo_ysize;
1181 VP8LHistogramSet* const orig_histo =
1182 VP8LAllocateHistogramSet(image_histo_raw_size, cache_bits);
1183 // Don't attempt linear bin-partition heuristic for
1184 // histograms of small sizes (as bin_map will be very sparse) and
1185 // maximum quality q==100 (to preserve the compression gains at that level).
1186 const int entropy_combine_num_bins = low_effort ? NUM_PARTITIONS : BIN_SIZE;
1187 int entropy_combine;
1188 uint16_t* const map_tmp =
1189 WebPSafeMalloc(2 * image_histo_raw_size, sizeof(map_tmp));
1190 uint16_t* const cluster_mappings = map_tmp + image_histo_raw_size;
1191 int num_used = image_histo_raw_size;
1192 if (orig_histo == NULL || map_tmp == NULL) goto Error;
1193
1194 // Construct the histograms from backward references.
1195 HistogramBuild(xsize, histo_bits, refs, orig_histo);
1196 // Copies the histograms and computes its bit_cost.
1197 // histogram_symbols is optimized
1198 HistogramCopyAndAnalyze(orig_histo, image_histo, &num_used,
1199 histogram_symbols);
1200
1201 entropy_combine =
1202 (num_used > entropy_combine_num_bins * 2) && (quality < 100);
1203
1204 if (entropy_combine) {
1205 uint16_t* const bin_map = map_tmp;
1206 const double combine_cost_factor =
1207 GetCombineCostFactor(image_histo_raw_size, quality);
1208 const uint32_t num_clusters = num_used;
1209
1210 HistogramAnalyzeEntropyBin(image_histo, bin_map, low_effort);
1211 // Collapse histograms with similar entropy.
1212 HistogramCombineEntropyBin(image_histo, &num_used, histogram_symbols,
1213 cluster_mappings, tmp_histo, bin_map,
1214 entropy_combine_num_bins, combine_cost_factor,
1215 low_effort);
1216 OptimizeHistogramSymbols(image_histo, cluster_mappings, num_clusters,
1217 map_tmp, histogram_symbols);
1218 }
1219
1220 // Don't combine the histograms using stochastic and greedy heuristics for
1221 // low-effort compression mode.
1222 if (!low_effort || !entropy_combine) {
1223 const float x = quality / 100.f;
1224 // cubic ramp between 1 and MAX_HISTO_GREEDY:
1225 const int threshold_size = (int)(1 + (x * x * x) * (MAX_HISTO_GREEDY - 1));
1226 int do_greedy;
1227 if (!HistogramCombineStochastic(image_histo, &num_used, threshold_size,
1228 &do_greedy)) {
1229 goto Error;
1230 }
1231 if (do_greedy) {
1232 RemoveEmptyHistograms(image_histo);
1233 if (!HistogramCombineGreedy(image_histo, &num_used)) {
1234 goto Error;
1235 }
1236 }
1237 }
1238
1239 // Find the optimal map from original histograms to the final ones.
1240 RemoveEmptyHistograms(image_histo);
1241 HistogramRemap(orig_histo, image_histo, histogram_symbols);
1242
1243 ok = 1;
1244
1245 Error:
1246 VP8LFreeHistogramSet(orig_histo);
1247 WebPSafeFree(map_tmp);
1248 return ok;
1249}
1250