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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)
11 //
12 #ifdef HAVE_CONFIG_H
13 #include "src/webp/config.h"
14 #endif
15 
16 #include <string.h>
17 
18 #include "src/dsp/lossless.h"
19 #include "src/dsp/lossless_common.h"
20 #include "src/enc/backward_references_enc.h"
21 #include "src/enc/histogram_enc.h"
22 #include "src/enc/vp8i_enc.h"
23 #include "src/utils/utils.h"
24 
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)
30 // Maximum number of histograms allowed in greedy combining algorithm.
31 #define MAX_HISTO_GREEDY 100
32 
33 // Return the size of the histogram for a given cache_bits.
GetHistogramSize(int cache_bits)34 static int GetHistogramSize(int cache_bits) {
35   const int literal_size = VP8LHistogramNumCodes(cache_bits);
36   const size_t total_size = sizeof(VP8LHistogram) + sizeof(int) * literal_size;
37   assert(total_size <= (size_t)0x7fffffff);
38   return (int)total_size;
39 }
40 
HistogramClear(VP8LHistogram * const p)41 static void HistogramClear(VP8LHistogram* const p) {
42   uint32_t* const literal = p->literal_;
43   const int cache_bits = p->palette_code_bits_;
44   const int histo_size = GetHistogramSize(cache_bits);
45   memset(p, 0, histo_size);
46   p->palette_code_bits_ = cache_bits;
47   p->literal_ = literal;
48 }
49 
50 // Swap two histogram pointers.
HistogramSwap(VP8LHistogram ** const A,VP8LHistogram ** const B)51 static void HistogramSwap(VP8LHistogram** const A, VP8LHistogram** const B) {
52   VP8LHistogram* const tmp = *A;
53   *A = *B;
54   *B = tmp;
55 }
56 
HistogramCopy(const VP8LHistogram * const src,VP8LHistogram * const dst)57 static void HistogramCopy(const VP8LHistogram* const src,
58                           VP8LHistogram* const dst) {
59   uint32_t* const dst_literal = dst->literal_;
60   const int dst_cache_bits = dst->palette_code_bits_;
61   const int literal_size = VP8LHistogramNumCodes(dst_cache_bits);
62   const int histo_size = GetHistogramSize(dst_cache_bits);
63   assert(src->palette_code_bits_ == dst_cache_bits);
64   memcpy(dst, src, histo_size);
65   dst->literal_ = dst_literal;
66   memcpy(dst->literal_, src->literal_, literal_size * sizeof(*dst->literal_));
67 }
68 
VP8LFreeHistogram(VP8LHistogram * const histo)69 void VP8LFreeHistogram(VP8LHistogram* const histo) {
70   WebPSafeFree(histo);
71 }
72 
VP8LFreeHistogramSet(VP8LHistogramSet * const histo)73 void VP8LFreeHistogramSet(VP8LHistogramSet* const histo) {
74   WebPSafeFree(histo);
75 }
76 
VP8LHistogramStoreRefs(const VP8LBackwardRefs * const refs,VP8LHistogram * const histo)77 void 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 
VP8LHistogramCreate(VP8LHistogram * const p,const VP8LBackwardRefs * const refs,int palette_code_bits)86 void 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 
VP8LHistogramInit(VP8LHistogram * const p,int palette_code_bits,int init_arrays)96 void 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 
VP8LAllocateHistogram(int cache_bits)111 VP8LHistogram* VP8LAllocateHistogram(int cache_bits) {
112   VP8LHistogram* histo = NULL;
113   const int total_size = GetHistogramSize(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.
HistogramSetResetPointers(VP8LHistogramSet * const set,int cache_bits)124 static void HistogramSetResetPointers(VP8LHistogramSet* const set,
125                                       int cache_bits) {
126   int i;
127   const int histo_size = GetHistogramSize(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.
HistogramSetTotalSize(int size,int cache_bits)140 static size_t HistogramSetTotalSize(int size, int cache_bits) {
141   const int histo_size = GetHistogramSize(cache_bits);
142   return (sizeof(VP8LHistogramSet) + size * (sizeof(VP8LHistogram*) +
143           histo_size + WEBP_ALIGN_CST));
144 }
145 
VP8LAllocateHistogramSet(int size,int cache_bits)146 VP8LHistogramSet* 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 
VP8LHistogramSetClear(VP8LHistogramSet * const set)165 void 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.
HistogramSetRemoveHistogram(VP8LHistogramSet * const set,int i,int * const num_used)184 static 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 
VP8LHistogramAddSinglePixOrCopy(VP8LHistogram * const histo,const PixOrCopy * const v,int (* const distance_modifier)(int,int),int distance_modifier_arg0)199 void 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     assert(histo->palette_code_bits_ != 0);
212     ++histo->literal_[literal_ix];
213   } else {
214     int code, extra_bits;
215     VP8LPrefixEncodeBits(PixOrCopyLength(v), &code, &extra_bits);
216     ++histo->literal_[NUM_LITERAL_CODES + code];
217     if (distance_modifier == NULL) {
218       VP8LPrefixEncodeBits(PixOrCopyDistance(v), &code, &extra_bits);
219     } else {
220       VP8LPrefixEncodeBits(
221           distance_modifier(distance_modifier_arg0, PixOrCopyDistance(v)),
222           &code, &extra_bits);
223     }
224     ++histo->distance_[code];
225   }
226 }
227 
228 // -----------------------------------------------------------------------------
229 // Entropy-related functions.
230 
BitsEntropyRefine(const VP8LBitEntropy * entropy)231 static WEBP_INLINE uint64_t BitsEntropyRefine(const VP8LBitEntropy* entropy) {
232   uint64_t mix;
233   if (entropy->nonzeros < 5) {
234     if (entropy->nonzeros <= 1) {
235       return 0;
236     }
237     // Two symbols, they will be 0 and 1 in a Huffman code.
238     // Let's mix in a bit of entropy to favor good clustering when
239     // distributions of these are combined.
240     if (entropy->nonzeros == 2) {
241       return DivRound(99 * ((uint64_t)entropy->sum << LOG_2_PRECISION_BITS) +
242                           entropy->entropy,
243                       100);
244     }
245     // No matter what the entropy says, we cannot be better than min_limit
246     // with Huffman coding. I am mixing a bit of entropy into the
247     // min_limit since it produces much better (~0.5 %) compression results
248     // perhaps because of better entropy clustering.
249     if (entropy->nonzeros == 3) {
250       mix = 950;
251     } else {
252       mix = 700;  // nonzeros == 4.
253     }
254   } else {
255     mix = 627;
256   }
257 
258   {
259     uint64_t min_limit = (uint64_t)(2 * entropy->sum - entropy->max_val)
260                          << LOG_2_PRECISION_BITS;
261     min_limit =
262         DivRound(mix * min_limit + (1000 - mix) * entropy->entropy, 1000);
263     return (entropy->entropy < min_limit) ? min_limit : entropy->entropy;
264   }
265 }
266 
VP8LBitsEntropy(const uint32_t * const array,int n)267 uint64_t VP8LBitsEntropy(const uint32_t* const array, int n) {
268   VP8LBitEntropy entropy;
269   VP8LBitsEntropyUnrefined(array, n, &entropy);
270 
271   return BitsEntropyRefine(&entropy);
272 }
273 
InitialHuffmanCost(void)274 static uint64_t InitialHuffmanCost(void) {
275   // Small bias because Huffman code length is typically not stored in
276   // full length.
277   static const uint64_t kHuffmanCodeOfHuffmanCodeSize = CODE_LENGTH_CODES * 3;
278   // Subtract a bias of 9.1.
279   return (kHuffmanCodeOfHuffmanCodeSize << LOG_2_PRECISION_BITS) -
280          DivRound(91ll << LOG_2_PRECISION_BITS, 10);
281 }
282 
283 // Finalize the Huffman cost based on streak numbers and length type (<3 or >=3)
FinalHuffmanCost(const VP8LStreaks * const stats)284 static uint64_t FinalHuffmanCost(const VP8LStreaks* const stats) {
285   // The constants in this function are empirical and got rounded from
286   // their original values in 1/8 when switched to 1/1024.
287   uint64_t retval = InitialHuffmanCost();
288   // Second coefficient: Many zeros in the histogram are covered efficiently
289   // by a run-length encode. Originally 2/8.
290   uint32_t retval_extra = stats->counts[0] * 1600 + 240 * stats->streaks[0][1];
291   // Second coefficient: Constant values are encoded less efficiently, but still
292   // RLE'ed. Originally 6/8.
293   retval_extra += stats->counts[1] * 2640 + 720 * stats->streaks[1][1];
294   // 0s are usually encoded more efficiently than non-0s.
295   // Originally 15/8.
296   retval_extra += 1840 * stats->streaks[0][0];
297   // Originally 26/8.
298   retval_extra += 3360 * stats->streaks[1][0];
299   return retval + ((uint64_t)retval_extra << (LOG_2_PRECISION_BITS - 10));
300 }
301 
302 // Get the symbol entropy for the distribution 'population'.
303 // Set 'trivial_sym', if there's only one symbol present in the distribution.
PopulationCost(const uint32_t * const population,int length,uint32_t * const trivial_sym,uint8_t * const is_used)304 static uint64_t PopulationCost(const uint32_t* const population, int length,
305                                uint32_t* const trivial_sym,
306                                uint8_t* const is_used) {
307   VP8LBitEntropy bit_entropy;
308   VP8LStreaks stats;
309   VP8LGetEntropyUnrefined(population, length, &bit_entropy, &stats);
310   if (trivial_sym != NULL) {
311     *trivial_sym = (bit_entropy.nonzeros == 1) ? bit_entropy.nonzero_code
312                                                : VP8L_NON_TRIVIAL_SYM;
313   }
314   // The histogram is used if there is at least one non-zero streak.
315   *is_used = (stats.streaks[1][0] != 0 || stats.streaks[1][1] != 0);
316 
317   return BitsEntropyRefine(&bit_entropy) + FinalHuffmanCost(&stats);
318 }
319 
320 // trivial_at_end is 1 if the two histograms only have one element that is
321 // non-zero: both the zero-th one, or both the last one.
GetCombinedEntropy(const uint32_t * const X,const uint32_t * const Y,int length,int is_X_used,int is_Y_used,int trivial_at_end)322 static WEBP_INLINE uint64_t GetCombinedEntropy(const uint32_t* const X,
323                                                const uint32_t* const Y,
324                                                int length, int is_X_used,
325                                                int is_Y_used,
326                                                int trivial_at_end) {
327   VP8LStreaks stats;
328   if (trivial_at_end) {
329     // This configuration is due to palettization that transforms an indexed
330     // pixel into 0xff000000 | (pixel << 8) in VP8LBundleColorMap.
331     // BitsEntropyRefine is 0 for histograms with only one non-zero value.
332     // Only FinalHuffmanCost needs to be evaluated.
333     memset(&stats, 0, sizeof(stats));
334     // Deal with the non-zero value at index 0 or length-1.
335     stats.streaks[1][0] = 1;
336     // Deal with the following/previous zero streak.
337     stats.counts[0] = 1;
338     stats.streaks[0][1] = length - 1;
339     return FinalHuffmanCost(&stats);
340   } else {
341     VP8LBitEntropy bit_entropy;
342     if (is_X_used) {
343       if (is_Y_used) {
344         VP8LGetCombinedEntropyUnrefined(X, Y, length, &bit_entropy, &stats);
345       } else {
346         VP8LGetEntropyUnrefined(X, length, &bit_entropy, &stats);
347       }
348     } else {
349       if (is_Y_used) {
350         VP8LGetEntropyUnrefined(Y, length, &bit_entropy, &stats);
351       } else {
352         memset(&stats, 0, sizeof(stats));
353         stats.counts[0] = 1;
354         stats.streaks[0][length > 3] = length;
355         VP8LBitEntropyInit(&bit_entropy);
356       }
357     }
358 
359     return BitsEntropyRefine(&bit_entropy) + FinalHuffmanCost(&stats);
360   }
361 }
362 
363 // Estimates the Entropy + Huffman + other block overhead size cost.
VP8LHistogramEstimateBits(VP8LHistogram * const p)364 uint64_t VP8LHistogramEstimateBits(VP8LHistogram* const p) {
365   return PopulationCost(p->literal_,
366                         VP8LHistogramNumCodes(p->palette_code_bits_), NULL,
367                         &p->is_used_[0]) +
368          PopulationCost(p->red_, NUM_LITERAL_CODES, NULL, &p->is_used_[1]) +
369          PopulationCost(p->blue_, NUM_LITERAL_CODES, NULL, &p->is_used_[2]) +
370          PopulationCost(p->alpha_, NUM_LITERAL_CODES, NULL, &p->is_used_[3]) +
371          PopulationCost(p->distance_, NUM_DISTANCE_CODES, NULL,
372                         &p->is_used_[4]) +
373          ((uint64_t)(VP8LExtraCost(p->literal_ + NUM_LITERAL_CODES,
374                                    NUM_LENGTH_CODES) +
375                      VP8LExtraCost(p->distance_, NUM_DISTANCE_CODES))
376           << LOG_2_PRECISION_BITS);
377 }
378 
379 // -----------------------------------------------------------------------------
380 // Various histogram combine/cost-eval functions
381 
382 // Set a + b in b, saturating at WEBP_INT64_MAX.
SaturateAdd(uint64_t a,int64_t * b)383 static WEBP_INLINE void SaturateAdd(uint64_t a, int64_t* b) {
384   if (*b < 0 || (int64_t)a <= WEBP_INT64_MAX - *b) {
385     *b += (int64_t)a;
386   } else {
387     *b = WEBP_INT64_MAX;
388   }
389 }
390 
391 // Returns 1 if the cost of the combined histogram is less than the threshold.
392 // Otherwise returns 0 and the cost is invalid due to early bail-out.
GetCombinedHistogramEntropy(const VP8LHistogram * const a,const VP8LHistogram * const b,int64_t cost_threshold_in,uint64_t * cost)393 WEBP_NODISCARD static int GetCombinedHistogramEntropy(
394     const VP8LHistogram* const a, const VP8LHistogram* const b,
395     int64_t cost_threshold_in, uint64_t* cost) {
396   const int palette_code_bits = a->palette_code_bits_;
397   int trivial_at_end = 0;
398   const uint64_t cost_threshold = (uint64_t)cost_threshold_in;
399   assert(a->palette_code_bits_ == b->palette_code_bits_);
400   if (cost_threshold_in <= 0) return 0;
401   *cost = GetCombinedEntropy(a->literal_, b->literal_,
402                              VP8LHistogramNumCodes(palette_code_bits),
403                              a->is_used_[0], b->is_used_[0], 0);
404   *cost += (uint64_t)VP8LExtraCostCombined(a->literal_ + NUM_LITERAL_CODES,
405                                            b->literal_ + NUM_LITERAL_CODES,
406                                            NUM_LENGTH_CODES)
407            << LOG_2_PRECISION_BITS;
408   if (*cost >= cost_threshold) return 0;
409 
410   if (a->trivial_symbol_ != VP8L_NON_TRIVIAL_SYM &&
411       a->trivial_symbol_ == b->trivial_symbol_) {
412     // A, R and B are all 0 or 0xff.
413     const uint32_t color_a = (a->trivial_symbol_ >> 24) & 0xff;
414     const uint32_t color_r = (a->trivial_symbol_ >> 16) & 0xff;
415     const uint32_t color_b = (a->trivial_symbol_ >> 0) & 0xff;
416     if ((color_a == 0 || color_a == 0xff) &&
417         (color_r == 0 || color_r == 0xff) &&
418         (color_b == 0 || color_b == 0xff)) {
419       trivial_at_end = 1;
420     }
421   }
422 
423   *cost += GetCombinedEntropy(a->red_, b->red_, NUM_LITERAL_CODES,
424                               a->is_used_[1], b->is_used_[1], trivial_at_end);
425   if (*cost >= cost_threshold) return 0;
426 
427   *cost += GetCombinedEntropy(a->blue_, b->blue_, NUM_LITERAL_CODES,
428                               a->is_used_[2], b->is_used_[2], trivial_at_end);
429   if (*cost >= cost_threshold) return 0;
430 
431   *cost += GetCombinedEntropy(a->alpha_, b->alpha_, NUM_LITERAL_CODES,
432                               a->is_used_[3], b->is_used_[3], trivial_at_end);
433   if (*cost >= cost_threshold) return 0;
434 
435   *cost += GetCombinedEntropy(a->distance_, b->distance_, NUM_DISTANCE_CODES,
436                               a->is_used_[4], b->is_used_[4], 0);
437   *cost += (uint64_t)VP8LExtraCostCombined(a->distance_, b->distance_,
438                                            NUM_DISTANCE_CODES)
439            << LOG_2_PRECISION_BITS;
440   if (*cost >= cost_threshold) return 0;
441 
442   return 1;
443 }
444 
HistogramAdd(const VP8LHistogram * const a,const VP8LHistogram * const b,VP8LHistogram * const out)445 static WEBP_INLINE void HistogramAdd(const VP8LHistogram* const a,
446                                      const VP8LHistogram* const b,
447                                      VP8LHistogram* const out) {
448   VP8LHistogramAdd(a, b, out);
449   out->trivial_symbol_ = (a->trivial_symbol_ == b->trivial_symbol_)
450                        ? a->trivial_symbol_
451                        : VP8L_NON_TRIVIAL_SYM;
452 }
453 
454 // Performs out = a + b, computing the cost C(a+b) - C(a) - C(b) while comparing
455 // to the threshold value 'cost_threshold'. The score returned is
456 //  Score = C(a+b) - C(a) - C(b), where C(a) + C(b) is known and fixed.
457 // Since the previous score passed is 'cost_threshold', we only need to compare
458 // the partial cost against 'cost_threshold + C(a) + C(b)' to possibly bail-out
459 // early.
460 // Returns 1 if the cost is less than the threshold.
461 // Otherwise returns 0 and the cost is invalid due to early bail-out.
HistogramAddEval(const VP8LHistogram * const a,const VP8LHistogram * const b,VP8LHistogram * const out,int64_t cost_threshold)462 WEBP_NODISCARD static int HistogramAddEval(const VP8LHistogram* const a,
463                                            const VP8LHistogram* const b,
464                                            VP8LHistogram* const out,
465                                            int64_t cost_threshold) {
466   uint64_t cost;
467   const uint64_t sum_cost = a->bit_cost_ + b->bit_cost_;
468   SaturateAdd(sum_cost, &cost_threshold);
469   if (!GetCombinedHistogramEntropy(a, b, cost_threshold, &cost)) return 0;
470 
471   HistogramAdd(a, b, out);
472   out->bit_cost_ = cost;
473   out->palette_code_bits_ = a->palette_code_bits_;
474   return 1;
475 }
476 
477 // Same as HistogramAddEval(), except that the resulting histogram
478 // is not stored. Only the cost C(a+b) - C(a) is evaluated. We omit
479 // the term C(b) which is constant over all the evaluations.
480 // Returns 1 if the cost is less than the threshold.
481 // Otherwise returns 0 and the cost is invalid due to early bail-out.
HistogramAddThresh(const VP8LHistogram * const a,const VP8LHistogram * const b,int64_t cost_threshold,int64_t * cost_out)482 WEBP_NODISCARD static int HistogramAddThresh(const VP8LHistogram* const a,
483                                              const VP8LHistogram* const b,
484                                              int64_t cost_threshold,
485                                              int64_t* cost_out) {
486   uint64_t cost;
487   assert(a != NULL && b != NULL);
488   SaturateAdd(a->bit_cost_, &cost_threshold);
489   if (!GetCombinedHistogramEntropy(a, b, cost_threshold, &cost)) return 0;
490 
491   *cost_out = (int64_t)cost - (int64_t)a->bit_cost_;
492   return 1;
493 }
494 
495 // -----------------------------------------------------------------------------
496 
497 // The structure to keep track of cost range for the three dominant entropy
498 // symbols.
499 typedef struct {
500   uint64_t literal_max_;
501   uint64_t literal_min_;
502   uint64_t red_max_;
503   uint64_t red_min_;
504   uint64_t blue_max_;
505   uint64_t blue_min_;
506 } DominantCostRange;
507 
DominantCostRangeInit(DominantCostRange * const c)508 static void DominantCostRangeInit(DominantCostRange* const c) {
509   c->literal_max_ = 0;
510   c->literal_min_ = WEBP_UINT64_MAX;
511   c->red_max_ = 0;
512   c->red_min_ = WEBP_UINT64_MAX;
513   c->blue_max_ = 0;
514   c->blue_min_ = WEBP_UINT64_MAX;
515 }
516 
UpdateDominantCostRange(const VP8LHistogram * const h,DominantCostRange * const c)517 static void UpdateDominantCostRange(
518     const VP8LHistogram* const h, DominantCostRange* const c) {
519   if (c->literal_max_ < h->literal_cost_) c->literal_max_ = h->literal_cost_;
520   if (c->literal_min_ > h->literal_cost_) c->literal_min_ = h->literal_cost_;
521   if (c->red_max_ < h->red_cost_) c->red_max_ = h->red_cost_;
522   if (c->red_min_ > h->red_cost_) c->red_min_ = h->red_cost_;
523   if (c->blue_max_ < h->blue_cost_) c->blue_max_ = h->blue_cost_;
524   if (c->blue_min_ > h->blue_cost_) c->blue_min_ = h->blue_cost_;
525 }
526 
UpdateHistogramCost(VP8LHistogram * const h)527 static void UpdateHistogramCost(VP8LHistogram* const h) {
528   uint32_t alpha_sym, red_sym, blue_sym;
529   const uint64_t alpha_cost =
530       PopulationCost(h->alpha_, NUM_LITERAL_CODES, &alpha_sym, &h->is_used_[3]);
531   const uint64_t distance_cost =
532       PopulationCost(h->distance_, NUM_DISTANCE_CODES, NULL, &h->is_used_[4]) +
533       ((uint64_t)VP8LExtraCost(h->distance_, NUM_DISTANCE_CODES)
534        << LOG_2_PRECISION_BITS);
535   const int num_codes = VP8LHistogramNumCodes(h->palette_code_bits_);
536   h->literal_cost_ =
537       PopulationCost(h->literal_, num_codes, NULL, &h->is_used_[0]) +
538       ((uint64_t)VP8LExtraCost(h->literal_ + NUM_LITERAL_CODES,
539                                NUM_LENGTH_CODES)
540        << LOG_2_PRECISION_BITS);
541   h->red_cost_ =
542       PopulationCost(h->red_, NUM_LITERAL_CODES, &red_sym, &h->is_used_[1]);
543   h->blue_cost_ =
544       PopulationCost(h->blue_, NUM_LITERAL_CODES, &blue_sym, &h->is_used_[2]);
545   h->bit_cost_ = h->literal_cost_ + h->red_cost_ + h->blue_cost_ +
546                  alpha_cost + distance_cost;
547   if ((alpha_sym | red_sym | blue_sym) == VP8L_NON_TRIVIAL_SYM) {
548     h->trivial_symbol_ = VP8L_NON_TRIVIAL_SYM;
549   } else {
550     h->trivial_symbol_ =
551         ((uint32_t)alpha_sym << 24) | (red_sym << 16) | (blue_sym << 0);
552   }
553 }
554 
GetBinIdForEntropy(uint64_t min,uint64_t max,uint64_t val)555 static int GetBinIdForEntropy(uint64_t min, uint64_t max, uint64_t val) {
556   const uint64_t range = max - min;
557   if (range > 0) {
558     const uint64_t delta = val - min;
559     return (int)((NUM_PARTITIONS - 1e-6) * delta / range);
560   } else {
561     return 0;
562   }
563 }
564 
GetHistoBinIndex(const VP8LHistogram * const h,const DominantCostRange * const c,int low_effort)565 static int GetHistoBinIndex(const VP8LHistogram* const h,
566                             const DominantCostRange* const c, int low_effort) {
567   int bin_id = GetBinIdForEntropy(c->literal_min_, c->literal_max_,
568                                   h->literal_cost_);
569   assert(bin_id < NUM_PARTITIONS);
570   if (!low_effort) {
571     bin_id = bin_id * NUM_PARTITIONS
572            + GetBinIdForEntropy(c->red_min_, c->red_max_, h->red_cost_);
573     bin_id = bin_id * NUM_PARTITIONS
574            + GetBinIdForEntropy(c->blue_min_, c->blue_max_, h->blue_cost_);
575     assert(bin_id < BIN_SIZE);
576   }
577   return bin_id;
578 }
579 
580 // Construct the histograms from backward references.
HistogramBuild(int xsize,int histo_bits,const VP8LBackwardRefs * const backward_refs,VP8LHistogramSet * const image_histo)581 static void HistogramBuild(
582     int xsize, int histo_bits, const VP8LBackwardRefs* const backward_refs,
583     VP8LHistogramSet* const image_histo) {
584   int x = 0, y = 0;
585   const int histo_xsize = VP8LSubSampleSize(xsize, histo_bits);
586   VP8LHistogram** const histograms = image_histo->histograms;
587   VP8LRefsCursor c = VP8LRefsCursorInit(backward_refs);
588   assert(histo_bits > 0);
589   VP8LHistogramSetClear(image_histo);
590   while (VP8LRefsCursorOk(&c)) {
591     const PixOrCopy* const v = c.cur_pos;
592     const int ix = (y >> histo_bits) * histo_xsize + (x >> histo_bits);
593     VP8LHistogramAddSinglePixOrCopy(histograms[ix], v, NULL, 0);
594     x += PixOrCopyLength(v);
595     while (x >= xsize) {
596       x -= xsize;
597       ++y;
598     }
599     VP8LRefsCursorNext(&c);
600   }
601 }
602 
603 // Copies the histograms and computes its bit_cost.
604 static const uint32_t kInvalidHistogramSymbol = (uint32_t)(-1);
HistogramCopyAndAnalyze(VP8LHistogramSet * const orig_histo,VP8LHistogramSet * const image_histo,int * const num_used,uint32_t * const histogram_symbols)605 static void HistogramCopyAndAnalyze(VP8LHistogramSet* const orig_histo,
606                                     VP8LHistogramSet* const image_histo,
607                                     int* const num_used,
608                                     uint32_t* const histogram_symbols) {
609   int i, cluster_id;
610   int num_used_orig = *num_used;
611   VP8LHistogram** const orig_histograms = orig_histo->histograms;
612   VP8LHistogram** const histograms = image_histo->histograms;
613   assert(image_histo->max_size == orig_histo->max_size);
614   for (cluster_id = 0, i = 0; i < orig_histo->max_size; ++i) {
615     VP8LHistogram* const histo = orig_histograms[i];
616     UpdateHistogramCost(histo);
617 
618     // Skip the histogram if it is completely empty, which can happen for tiles
619     // with no information (when they are skipped because of LZ77).
620     if (!histo->is_used_[0] && !histo->is_used_[1] && !histo->is_used_[2]
621         && !histo->is_used_[3] && !histo->is_used_[4]) {
622       // The first histogram is always used. If an histogram is empty, we set
623       // its id to be the same as the previous one: this will improve
624       // compressibility for later LZ77.
625       assert(i > 0);
626       HistogramSetRemoveHistogram(image_histo, i, num_used);
627       HistogramSetRemoveHistogram(orig_histo, i, &num_used_orig);
628       histogram_symbols[i] = kInvalidHistogramSymbol;
629     } else {
630       // Copy histograms from orig_histo[] to image_histo[].
631       HistogramCopy(histo, histograms[i]);
632       histogram_symbols[i] = cluster_id++;
633       assert(cluster_id <= image_histo->max_size);
634     }
635   }
636 }
637 
638 // Partition histograms to different entropy bins for three dominant (literal,
639 // red and blue) symbol costs and compute the histogram aggregate bit_cost.
HistogramAnalyzeEntropyBin(VP8LHistogramSet * const image_histo,uint16_t * const bin_map,int low_effort)640 static void HistogramAnalyzeEntropyBin(VP8LHistogramSet* const image_histo,
641                                        uint16_t* const bin_map,
642                                        int low_effort) {
643   int i;
644   VP8LHistogram** const histograms = image_histo->histograms;
645   const int histo_size = image_histo->size;
646   DominantCostRange cost_range;
647   DominantCostRangeInit(&cost_range);
648 
649   // Analyze the dominant (literal, red and blue) entropy costs.
650   for (i = 0; i < histo_size; ++i) {
651     if (histograms[i] == NULL) continue;
652     UpdateDominantCostRange(histograms[i], &cost_range);
653   }
654 
655   // bin-hash histograms on three of the dominant (literal, red and blue)
656   // symbol costs and store the resulting bin_id for each histogram.
657   for (i = 0; i < histo_size; ++i) {
658     // bin_map[i] is not set to a special value as its use will later be guarded
659     // by another (histograms[i] == NULL).
660     if (histograms[i] == NULL) continue;
661     bin_map[i] = GetHistoBinIndex(histograms[i], &cost_range, low_effort);
662   }
663 }
664 
665 // Merges some histograms with same bin_id together if it's advantageous.
666 // Sets the remaining histograms to NULL.
667 // 'combine_cost_factor' has to be divided by 100.
HistogramCombineEntropyBin(VP8LHistogramSet * const image_histo,int * num_used,const uint32_t * const clusters,uint16_t * const cluster_mappings,VP8LHistogram * cur_combo,const uint16_t * const bin_map,int num_bins,int32_t combine_cost_factor,int low_effort)668 static void HistogramCombineEntropyBin(
669     VP8LHistogramSet* const image_histo, int* num_used,
670     const uint32_t* const clusters, uint16_t* const cluster_mappings,
671     VP8LHistogram* cur_combo, const uint16_t* const bin_map, int num_bins,
672     int32_t combine_cost_factor, int low_effort) {
673   VP8LHistogram** const histograms = image_histo->histograms;
674   int idx;
675   struct {
676     int16_t first;    // position of the histogram that accumulates all
677                       // histograms with the same bin_id
678     uint16_t num_combine_failures;   // number of combine failures per bin_id
679   } bin_info[BIN_SIZE];
680 
681   assert(num_bins <= BIN_SIZE);
682   for (idx = 0; idx < num_bins; ++idx) {
683     bin_info[idx].first = -1;
684     bin_info[idx].num_combine_failures = 0;
685   }
686 
687   // By default, a cluster matches itself.
688   for (idx = 0; idx < *num_used; ++idx) cluster_mappings[idx] = idx;
689   for (idx = 0; idx < image_histo->size; ++idx) {
690     int bin_id, first;
691     if (histograms[idx] == NULL) continue;
692     bin_id = bin_map[idx];
693     first = bin_info[bin_id].first;
694     if (first == -1) {
695       bin_info[bin_id].first = idx;
696     } else if (low_effort) {
697       HistogramAdd(histograms[idx], histograms[first], histograms[first]);
698       HistogramSetRemoveHistogram(image_histo, idx, num_used);
699       cluster_mappings[clusters[idx]] = clusters[first];
700     } else {
701       // try to merge #idx into #first (both share the same bin_id)
702       const uint64_t bit_cost = histograms[idx]->bit_cost_;
703       const int64_t bit_cost_thresh =
704           -DivRound((int64_t)bit_cost * combine_cost_factor, 100);
705       if (HistogramAddEval(histograms[first], histograms[idx], cur_combo,
706                            bit_cost_thresh)) {
707         // Try to merge two histograms only if the combo is a trivial one or
708         // the two candidate histograms are already non-trivial.
709         // For some images, 'try_combine' turns out to be false for a lot of
710         // histogram pairs. In that case, we fallback to combining
711         // histograms as usual to avoid increasing the header size.
712         const int try_combine =
713             (cur_combo->trivial_symbol_ != VP8L_NON_TRIVIAL_SYM) ||
714             ((histograms[idx]->trivial_symbol_ == VP8L_NON_TRIVIAL_SYM) &&
715              (histograms[first]->trivial_symbol_ == VP8L_NON_TRIVIAL_SYM));
716         const int max_combine_failures = 32;
717         if (try_combine ||
718             bin_info[bin_id].num_combine_failures >= max_combine_failures) {
719           // move the (better) merged histogram to its final slot
720           HistogramSwap(&cur_combo, &histograms[first]);
721           HistogramSetRemoveHistogram(image_histo, idx, num_used);
722           cluster_mappings[clusters[idx]] = clusters[first];
723         } else {
724           ++bin_info[bin_id].num_combine_failures;
725         }
726       }
727     }
728   }
729   if (low_effort) {
730     // for low_effort case, update the final cost when everything is merged
731     for (idx = 0; idx < image_histo->size; ++idx) {
732       if (histograms[idx] == NULL) continue;
733       UpdateHistogramCost(histograms[idx]);
734     }
735   }
736 }
737 
738 // Implement a Lehmer random number generator with a multiplicative constant of
739 // 48271 and a modulo constant of 2^31 - 1.
MyRand(uint32_t * const seed)740 static uint32_t MyRand(uint32_t* const seed) {
741   *seed = (uint32_t)(((uint64_t)(*seed) * 48271u) % 2147483647u);
742   assert(*seed > 0);
743   return *seed;
744 }
745 
746 // -----------------------------------------------------------------------------
747 // Histogram pairs priority queue
748 
749 // Pair of histograms. Negative idx1 value means that pair is out-of-date.
750 typedef struct {
751   int idx1;
752   int idx2;
753   int64_t cost_diff;
754   uint64_t cost_combo;
755 } HistogramPair;
756 
757 typedef struct {
758   HistogramPair* queue;
759   int size;
760   int max_size;
761 } HistoQueue;
762 
HistoQueueInit(HistoQueue * const histo_queue,const int max_size)763 static int HistoQueueInit(HistoQueue* const histo_queue, const int max_size) {
764   histo_queue->size = 0;
765   histo_queue->max_size = max_size;
766   // We allocate max_size + 1 because the last element at index "size" is
767   // used as temporary data (and it could be up to max_size).
768   histo_queue->queue = (HistogramPair*)WebPSafeMalloc(
769       histo_queue->max_size + 1, sizeof(*histo_queue->queue));
770   return histo_queue->queue != NULL;
771 }
772 
HistoQueueClear(HistoQueue * const histo_queue)773 static void HistoQueueClear(HistoQueue* const histo_queue) {
774   assert(histo_queue != NULL);
775   WebPSafeFree(histo_queue->queue);
776   histo_queue->size = 0;
777   histo_queue->max_size = 0;
778 }
779 
780 // Pop a specific pair in the queue by replacing it with the last one
781 // and shrinking the queue.
HistoQueuePopPair(HistoQueue * const histo_queue,HistogramPair * const pair)782 static void HistoQueuePopPair(HistoQueue* const histo_queue,
783                               HistogramPair* const pair) {
784   assert(pair >= histo_queue->queue &&
785          pair < (histo_queue->queue + histo_queue->size));
786   assert(histo_queue->size > 0);
787   *pair = histo_queue->queue[histo_queue->size - 1];
788   --histo_queue->size;
789 }
790 
791 // Check whether a pair in the queue should be updated as head or not.
HistoQueueUpdateHead(HistoQueue * const histo_queue,HistogramPair * const pair)792 static void HistoQueueUpdateHead(HistoQueue* const histo_queue,
793                                  HistogramPair* const pair) {
794   assert(pair->cost_diff < 0);
795   assert(pair >= histo_queue->queue &&
796          pair < (histo_queue->queue + histo_queue->size));
797   assert(histo_queue->size > 0);
798   if (pair->cost_diff < histo_queue->queue[0].cost_diff) {
799     // Replace the best pair.
800     const HistogramPair tmp = histo_queue->queue[0];
801     histo_queue->queue[0] = *pair;
802     *pair = tmp;
803   }
804 }
805 
806 // Update the cost diff and combo of a pair of histograms. This needs to be
807 // called when the histograms have been merged with a third one.
808 // Returns 1 if the cost diff is less than the threshold.
809 // Otherwise returns 0 and the cost is invalid due to early bail-out.
HistoQueueUpdatePair(const VP8LHistogram * const h1,const VP8LHistogram * const h2,int64_t cost_threshold,HistogramPair * const pair)810 WEBP_NODISCARD static int HistoQueueUpdatePair(const VP8LHistogram* const h1,
811                                                const VP8LHistogram* const h2,
812                                                int64_t cost_threshold,
813                                                HistogramPair* const pair) {
814   const int64_t sum_cost = h1->bit_cost_ + h2->bit_cost_;
815   SaturateAdd(sum_cost, &cost_threshold);
816   if (!GetCombinedHistogramEntropy(h1, h2, cost_threshold, &pair->cost_combo)) {
817     return 0;
818   }
819   pair->cost_diff = (int64_t)pair->cost_combo - sum_cost;
820   return 1;
821 }
822 
823 // Create a pair from indices "idx1" and "idx2" provided its cost
824 // is inferior to "threshold", a negative entropy.
825 // It returns the cost of the pair, or 0 if it superior to threshold.
HistoQueuePush(HistoQueue * const histo_queue,VP8LHistogram ** const histograms,int idx1,int idx2,int64_t threshold)826 static int64_t HistoQueuePush(HistoQueue* const histo_queue,
827                               VP8LHistogram** const histograms, int idx1,
828                               int idx2, int64_t threshold) {
829   const VP8LHistogram* h1;
830   const VP8LHistogram* h2;
831   HistogramPair pair;
832 
833   // Stop here if the queue is full.
834   if (histo_queue->size == histo_queue->max_size) return 0;
835   assert(threshold <= 0);
836   if (idx1 > idx2) {
837     const int tmp = idx2;
838     idx2 = idx1;
839     idx1 = tmp;
840   }
841   pair.idx1 = idx1;
842   pair.idx2 = idx2;
843   h1 = histograms[idx1];
844   h2 = histograms[idx2];
845 
846   // Do not even consider the pair if it does not improve the entropy.
847   if (!HistoQueueUpdatePair(h1, h2, threshold, &pair)) return 0;
848 
849   histo_queue->queue[histo_queue->size++] = pair;
850   HistoQueueUpdateHead(histo_queue, &histo_queue->queue[histo_queue->size - 1]);
851 
852   return pair.cost_diff;
853 }
854 
855 // -----------------------------------------------------------------------------
856 
857 // Combines histograms by continuously choosing the one with the highest cost
858 // reduction.
HistogramCombineGreedy(VP8LHistogramSet * const image_histo,int * const num_used)859 static int HistogramCombineGreedy(VP8LHistogramSet* const image_histo,
860                                   int* const num_used) {
861   int ok = 0;
862   const int image_histo_size = image_histo->size;
863   int i, j;
864   VP8LHistogram** const histograms = image_histo->histograms;
865   // Priority queue of histogram pairs.
866   HistoQueue histo_queue;
867 
868   // image_histo_size^2 for the queue size is safe. If you look at
869   // HistogramCombineGreedy, and imagine that UpdateQueueFront always pushes
870   // data to the queue, you insert at most:
871   // - image_histo_size*(image_histo_size-1)/2 (the first two for loops)
872   // - image_histo_size - 1 in the last for loop at the first iteration of
873   //   the while loop, image_histo_size - 2 at the second iteration ...
874   //   therefore image_histo_size*(image_histo_size-1)/2 overall too
875   if (!HistoQueueInit(&histo_queue, image_histo_size * image_histo_size)) {
876     goto End;
877   }
878 
879   for (i = 0; i < image_histo_size; ++i) {
880     if (image_histo->histograms[i] == NULL) continue;
881     for (j = i + 1; j < image_histo_size; ++j) {
882       // Initialize queue.
883       if (image_histo->histograms[j] == NULL) continue;
884       HistoQueuePush(&histo_queue, histograms, i, j, 0);
885     }
886   }
887 
888   while (histo_queue.size > 0) {
889     const int idx1 = histo_queue.queue[0].idx1;
890     const int idx2 = histo_queue.queue[0].idx2;
891     HistogramAdd(histograms[idx2], histograms[idx1], histograms[idx1]);
892     histograms[idx1]->bit_cost_ = histo_queue.queue[0].cost_combo;
893 
894     // Remove merged histogram.
895     HistogramSetRemoveHistogram(image_histo, idx2, num_used);
896 
897     // Remove pairs intersecting the just combined best pair.
898     for (i = 0; i < histo_queue.size;) {
899       HistogramPair* const p = histo_queue.queue + i;
900       if (p->idx1 == idx1 || p->idx2 == idx1 ||
901           p->idx1 == idx2 || p->idx2 == idx2) {
902         HistoQueuePopPair(&histo_queue, p);
903       } else {
904         HistoQueueUpdateHead(&histo_queue, p);
905         ++i;
906       }
907     }
908 
909     // Push new pairs formed with combined histogram to the queue.
910     for (i = 0; i < image_histo->size; ++i) {
911       if (i == idx1 || image_histo->histograms[i] == NULL) continue;
912       HistoQueuePush(&histo_queue, image_histo->histograms, idx1, i, 0);
913     }
914   }
915 
916   ok = 1;
917 
918  End:
919   HistoQueueClear(&histo_queue);
920   return ok;
921 }
922 
923 // Perform histogram aggregation using a stochastic approach.
924 // 'do_greedy' is set to 1 if a greedy approach needs to be performed
925 // afterwards, 0 otherwise.
PairComparison(const void * idx1,const void * idx2)926 static int PairComparison(const void* idx1, const void* idx2) {
927   // To be used with bsearch: <0 when *idx1<*idx2, >0 if >, 0 when ==.
928   return (*(int*) idx1 - *(int*) idx2);
929 }
HistogramCombineStochastic(VP8LHistogramSet * const image_histo,int * const num_used,int min_cluster_size,int * const do_greedy)930 static int HistogramCombineStochastic(VP8LHistogramSet* const image_histo,
931                                       int* const num_used, int min_cluster_size,
932                                       int* const do_greedy) {
933   int j, iter;
934   uint32_t seed = 1;
935   int tries_with_no_success = 0;
936   const int outer_iters = *num_used;
937   const int num_tries_no_success = outer_iters / 2;
938   VP8LHistogram** const histograms = image_histo->histograms;
939   // Priority queue of histogram pairs. Its size of 'kHistoQueueSize'
940   // impacts the quality of the compression and the speed: the smaller the
941   // faster but the worse for the compression.
942   HistoQueue histo_queue;
943   const int kHistoQueueSize = 9;
944   int ok = 0;
945   // mapping from an index in image_histo with no NULL histogram to the full
946   // blown image_histo.
947   int* mappings;
948 
949   if (*num_used < min_cluster_size) {
950     *do_greedy = 1;
951     return 1;
952   }
953 
954   mappings = (int*) WebPSafeMalloc(*num_used, sizeof(*mappings));
955   if (mappings == NULL) return 0;
956   if (!HistoQueueInit(&histo_queue, kHistoQueueSize)) goto End;
957   // Fill the initial mapping.
958   for (j = 0, iter = 0; iter < image_histo->size; ++iter) {
959     if (histograms[iter] == NULL) continue;
960     mappings[j++] = iter;
961   }
962   assert(j == *num_used);
963 
964   // Collapse similar histograms in 'image_histo'.
965   for (iter = 0;
966        iter < outer_iters && *num_used >= min_cluster_size &&
967            ++tries_with_no_success < num_tries_no_success;
968        ++iter) {
969     int* mapping_index;
970     int64_t best_cost =
971         (histo_queue.size == 0) ? 0 : histo_queue.queue[0].cost_diff;
972     int best_idx1 = -1, best_idx2 = 1;
973     const uint32_t rand_range = (*num_used - 1) * (*num_used);
974     // (*num_used) / 2 was chosen empirically. Less means faster but worse
975     // compression.
976     const int num_tries = (*num_used) / 2;
977 
978     // Pick random samples.
979     for (j = 0; *num_used >= 2 && j < num_tries; ++j) {
980       int64_t curr_cost;
981       // Choose two different histograms at random and try to combine them.
982       const uint32_t tmp = MyRand(&seed) % rand_range;
983       uint32_t idx1 = tmp / (*num_used - 1);
984       uint32_t idx2 = tmp % (*num_used - 1);
985       if (idx2 >= idx1) ++idx2;
986       idx1 = mappings[idx1];
987       idx2 = mappings[idx2];
988 
989       // Calculate cost reduction on combination.
990       curr_cost =
991           HistoQueuePush(&histo_queue, histograms, idx1, idx2, best_cost);
992       if (curr_cost < 0) {  // found a better pair?
993         best_cost = curr_cost;
994         // Empty the queue if we reached full capacity.
995         if (histo_queue.size == histo_queue.max_size) break;
996       }
997     }
998     if (histo_queue.size == 0) continue;
999 
1000     // Get the best histograms.
1001     best_idx1 = histo_queue.queue[0].idx1;
1002     best_idx2 = histo_queue.queue[0].idx2;
1003     assert(best_idx1 < best_idx2);
1004     // Pop best_idx2 from mappings.
1005     mapping_index = (int*) bsearch(&best_idx2, mappings, *num_used,
1006                                    sizeof(best_idx2), &PairComparison);
1007     assert(mapping_index != NULL);
1008     memmove(mapping_index, mapping_index + 1, sizeof(*mapping_index) *
1009         ((*num_used) - (mapping_index - mappings) - 1));
1010     // Merge the histograms and remove best_idx2 from the queue.
1011     HistogramAdd(histograms[best_idx2], histograms[best_idx1],
1012                  histograms[best_idx1]);
1013     histograms[best_idx1]->bit_cost_ = histo_queue.queue[0].cost_combo;
1014     HistogramSetRemoveHistogram(image_histo, best_idx2, num_used);
1015     // Parse the queue and update each pair that deals with best_idx1,
1016     // best_idx2 or image_histo_size.
1017     for (j = 0; j < histo_queue.size;) {
1018       HistogramPair* const p = histo_queue.queue + j;
1019       const int is_idx1_best = p->idx1 == best_idx1 || p->idx1 == best_idx2;
1020       const int is_idx2_best = p->idx2 == best_idx1 || p->idx2 == best_idx2;
1021       int do_eval = 0;
1022       // The front pair could have been duplicated by a random pick so
1023       // check for it all the time nevertheless.
1024       if (is_idx1_best && is_idx2_best) {
1025         HistoQueuePopPair(&histo_queue, p);
1026         continue;
1027       }
1028       // Any pair containing one of the two best indices should only refer to
1029       // best_idx1. Its cost should also be updated.
1030       if (is_idx1_best) {
1031         p->idx1 = best_idx1;
1032         do_eval = 1;
1033       } else if (is_idx2_best) {
1034         p->idx2 = best_idx1;
1035         do_eval = 1;
1036       }
1037       // Make sure the index order is respected.
1038       if (p->idx1 > p->idx2) {
1039         const int tmp = p->idx2;
1040         p->idx2 = p->idx1;
1041         p->idx1 = tmp;
1042       }
1043       if (do_eval) {
1044         // Re-evaluate the cost of an updated pair.
1045         if (!HistoQueueUpdatePair(histograms[p->idx1], histograms[p->idx2], 0,
1046                                   p)) {
1047           HistoQueuePopPair(&histo_queue, p);
1048           continue;
1049         }
1050       }
1051       HistoQueueUpdateHead(&histo_queue, p);
1052       ++j;
1053     }
1054     tries_with_no_success = 0;
1055   }
1056   *do_greedy = (*num_used <= min_cluster_size);
1057   ok = 1;
1058 
1059  End:
1060   HistoQueueClear(&histo_queue);
1061   WebPSafeFree(mappings);
1062   return ok;
1063 }
1064 
1065 // -----------------------------------------------------------------------------
1066 // Histogram refinement
1067 
1068 // Find the best 'out' histogram for each of the 'in' histograms.
1069 // At call-time, 'out' contains the histograms of the clusters.
1070 // Note: we assume that out[]->bit_cost_ is already up-to-date.
HistogramRemap(const VP8LHistogramSet * const in,VP8LHistogramSet * const out,uint32_t * const symbols)1071 static void HistogramRemap(const VP8LHistogramSet* const in,
1072                            VP8LHistogramSet* const out,
1073                            uint32_t* const symbols) {
1074   int i;
1075   VP8LHistogram** const in_histo = in->histograms;
1076   VP8LHistogram** const out_histo = out->histograms;
1077   const int in_size = out->max_size;
1078   const int out_size = out->size;
1079   if (out_size > 1) {
1080     for (i = 0; i < in_size; ++i) {
1081       int best_out = 0;
1082       int64_t best_bits = WEBP_INT64_MAX;
1083       int k;
1084       if (in_histo[i] == NULL) {
1085         // Arbitrarily set to the previous value if unused to help future LZ77.
1086         symbols[i] = symbols[i - 1];
1087         continue;
1088       }
1089       for (k = 0; k < out_size; ++k) {
1090         int64_t cur_bits;
1091         if (HistogramAddThresh(out_histo[k], in_histo[i], best_bits,
1092                                &cur_bits)) {
1093           best_bits = cur_bits;
1094           best_out = k;
1095         }
1096       }
1097       symbols[i] = best_out;
1098     }
1099   } else {
1100     assert(out_size == 1);
1101     for (i = 0; i < in_size; ++i) {
1102       symbols[i] = 0;
1103     }
1104   }
1105 
1106   // Recompute each out based on raw and symbols.
1107   VP8LHistogramSetClear(out);
1108   out->size = out_size;
1109 
1110   for (i = 0; i < in_size; ++i) {
1111     int idx;
1112     if (in_histo[i] == NULL) continue;
1113     idx = symbols[i];
1114     HistogramAdd(in_histo[i], out_histo[idx], out_histo[idx]);
1115   }
1116 }
1117 
GetCombineCostFactor(int histo_size,int quality)1118 static int32_t GetCombineCostFactor(int histo_size, int quality) {
1119   int32_t combine_cost_factor = 16;
1120   if (quality < 90) {
1121     if (histo_size > 256) combine_cost_factor /= 2;
1122     if (histo_size > 512) combine_cost_factor /= 2;
1123     if (histo_size > 1024) combine_cost_factor /= 2;
1124     if (quality <= 50) combine_cost_factor /= 2;
1125   }
1126   return combine_cost_factor;
1127 }
1128 
1129 // Given a HistogramSet 'set', the mapping of clusters 'cluster_mapping' and the
1130 // current assignment of the cells in 'symbols', merge the clusters and
1131 // assign the smallest possible clusters values.
OptimizeHistogramSymbols(const VP8LHistogramSet * const set,uint16_t * const cluster_mappings,uint32_t num_clusters,uint16_t * const cluster_mappings_tmp,uint32_t * const symbols)1132 static void OptimizeHistogramSymbols(const VP8LHistogramSet* const set,
1133                                      uint16_t* const cluster_mappings,
1134                                      uint32_t num_clusters,
1135                                      uint16_t* const cluster_mappings_tmp,
1136                                      uint32_t* const symbols) {
1137   uint32_t i, cluster_max;
1138   int do_continue = 1;
1139   // First, assign the lowest cluster to each pixel.
1140   while (do_continue) {
1141     do_continue = 0;
1142     for (i = 0; i < num_clusters; ++i) {
1143       int k;
1144       k = cluster_mappings[i];
1145       while (k != cluster_mappings[k]) {
1146         cluster_mappings[k] = cluster_mappings[cluster_mappings[k]];
1147         k = cluster_mappings[k];
1148       }
1149       if (k != cluster_mappings[i]) {
1150         do_continue = 1;
1151         cluster_mappings[i] = k;
1152       }
1153     }
1154   }
1155   // Create a mapping from a cluster id to its minimal version.
1156   cluster_max = 0;
1157   memset(cluster_mappings_tmp, 0,
1158          set->max_size * sizeof(*cluster_mappings_tmp));
1159   assert(cluster_mappings[0] == 0);
1160   // Re-map the ids.
1161   for (i = 0; i < (uint32_t)set->max_size; ++i) {
1162     int cluster;
1163     if (symbols[i] == kInvalidHistogramSymbol) continue;
1164     cluster = cluster_mappings[symbols[i]];
1165     assert(symbols[i] < num_clusters);
1166     if (cluster > 0 && cluster_mappings_tmp[cluster] == 0) {
1167       ++cluster_max;
1168       cluster_mappings_tmp[cluster] = cluster_max;
1169     }
1170     symbols[i] = cluster_mappings_tmp[cluster];
1171   }
1172 
1173   // Make sure all cluster values are used.
1174   cluster_max = 0;
1175   for (i = 0; i < (uint32_t)set->max_size; ++i) {
1176     if (symbols[i] == kInvalidHistogramSymbol) continue;
1177     if (symbols[i] <= cluster_max) continue;
1178     ++cluster_max;
1179     assert(symbols[i] == cluster_max);
1180   }
1181 }
1182 
RemoveEmptyHistograms(VP8LHistogramSet * const image_histo)1183 static void RemoveEmptyHistograms(VP8LHistogramSet* const image_histo) {
1184   uint32_t size;
1185   int i;
1186   for (i = 0, size = 0; i < image_histo->size; ++i) {
1187     if (image_histo->histograms[i] == NULL) continue;
1188     image_histo->histograms[size++] = image_histo->histograms[i];
1189   }
1190   image_histo->size = size;
1191 }
1192 
VP8LGetHistoImageSymbols(int xsize,int ysize,const VP8LBackwardRefs * const refs,int quality,int low_effort,int histogram_bits,int cache_bits,VP8LHistogramSet * const image_histo,VP8LHistogram * const tmp_histo,uint32_t * const histogram_symbols,const WebPPicture * const pic,int percent_range,int * const percent)1193 int VP8LGetHistoImageSymbols(int xsize, int ysize,
1194                              const VP8LBackwardRefs* const refs, int quality,
1195                              int low_effort, int histogram_bits, int cache_bits,
1196                              VP8LHistogramSet* const image_histo,
1197                              VP8LHistogram* const tmp_histo,
1198                              uint32_t* const histogram_symbols,
1199                              const WebPPicture* const pic, int percent_range,
1200                              int* const percent) {
1201   const int histo_xsize =
1202       histogram_bits ? VP8LSubSampleSize(xsize, histogram_bits) : 1;
1203   const int histo_ysize =
1204       histogram_bits ? VP8LSubSampleSize(ysize, histogram_bits) : 1;
1205   const int image_histo_raw_size = histo_xsize * histo_ysize;
1206   VP8LHistogramSet* const orig_histo =
1207       VP8LAllocateHistogramSet(image_histo_raw_size, cache_bits);
1208   // Don't attempt linear bin-partition heuristic for
1209   // histograms of small sizes (as bin_map will be very sparse) and
1210   // maximum quality q==100 (to preserve the compression gains at that level).
1211   const int entropy_combine_num_bins = low_effort ? NUM_PARTITIONS : BIN_SIZE;
1212   int entropy_combine;
1213   uint16_t* const map_tmp =
1214       (uint16_t*)WebPSafeMalloc(2 * image_histo_raw_size, sizeof(*map_tmp));
1215   uint16_t* const cluster_mappings = map_tmp + image_histo_raw_size;
1216   int num_used = image_histo_raw_size;
1217   if (orig_histo == NULL || map_tmp == NULL) {
1218     WebPEncodingSetError(pic, VP8_ENC_ERROR_OUT_OF_MEMORY);
1219     goto Error;
1220   }
1221 
1222   // Construct the histograms from backward references.
1223   HistogramBuild(xsize, histogram_bits, refs, orig_histo);
1224   // Copies the histograms and computes its bit_cost.
1225   // histogram_symbols is optimized
1226   HistogramCopyAndAnalyze(orig_histo, image_histo, &num_used,
1227                           histogram_symbols);
1228 
1229   entropy_combine =
1230       (num_used > entropy_combine_num_bins * 2) && (quality < 100);
1231 
1232   if (entropy_combine) {
1233     uint16_t* const bin_map = map_tmp;
1234     const int32_t combine_cost_factor =
1235         GetCombineCostFactor(image_histo_raw_size, quality);
1236     const uint32_t num_clusters = num_used;
1237 
1238     HistogramAnalyzeEntropyBin(image_histo, bin_map, low_effort);
1239     // Collapse histograms with similar entropy.
1240     HistogramCombineEntropyBin(
1241         image_histo, &num_used, histogram_symbols, cluster_mappings, tmp_histo,
1242         bin_map, entropy_combine_num_bins, combine_cost_factor, low_effort);
1243     OptimizeHistogramSymbols(image_histo, cluster_mappings, num_clusters,
1244                              map_tmp, histogram_symbols);
1245   }
1246 
1247   // Don't combine the histograms using stochastic and greedy heuristics for
1248   // low-effort compression mode.
1249   if (!low_effort || !entropy_combine) {
1250     // cubic ramp between 1 and MAX_HISTO_GREEDY:
1251     const int threshold_size =
1252         (int)(1 + DivRound(quality * quality * quality * (MAX_HISTO_GREEDY - 1),
1253                            100 * 100 * 100));
1254     int do_greedy;
1255     if (!HistogramCombineStochastic(image_histo, &num_used, threshold_size,
1256                                     &do_greedy)) {
1257       WebPEncodingSetError(pic, VP8_ENC_ERROR_OUT_OF_MEMORY);
1258       goto Error;
1259     }
1260     if (do_greedy) {
1261       RemoveEmptyHistograms(image_histo);
1262       if (!HistogramCombineGreedy(image_histo, &num_used)) {
1263         WebPEncodingSetError(pic, VP8_ENC_ERROR_OUT_OF_MEMORY);
1264         goto Error;
1265       }
1266     }
1267   }
1268 
1269   // Find the optimal map from original histograms to the final ones.
1270   RemoveEmptyHistograms(image_histo);
1271   HistogramRemap(orig_histo, image_histo, histogram_symbols);
1272 
1273   if (!WebPReportProgress(pic, *percent + percent_range, percent)) {
1274     goto Error;
1275   }
1276 
1277  Error:
1278   VP8LFreeHistogramSet(orig_histo);
1279   WebPSafeFree(map_tmp);
1280   return (pic->error_code == VP8_ENC_OK);
1281 }
1282