Coverage Report

Created: 2024-07-27 06:27

/src/libwebp/src/enc/histogram_enc.c
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// 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
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// 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.
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// -----------------------------------------------------------------------------
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"
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#include "src/enc/histogram_enc.h"
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#include "src/enc/vp8i_enc.h"
23
#include "src/utils/utils.h"
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25
// Number of partitions for the three dominant (literal, red and blue) symbol
26
// costs.
27
0
#define NUM_PARTITIONS 4
28
// The size of the bin-hash corresponding to the three dominant costs.
29
0
#define BIN_SIZE (NUM_PARTITIONS * NUM_PARTITIONS * NUM_PARTITIONS)
30
// Maximum number of histograms allowed in greedy combining algorithm.
31
0
#define MAX_HISTO_GREEDY 100
32
33
// Return the size of the histogram for a given cache_bits.
34
0
static int GetHistogramSize(int cache_bits) {
35
0
  const int literal_size = VP8LHistogramNumCodes(cache_bits);
36
0
  const size_t total_size = sizeof(VP8LHistogram) + sizeof(int) * literal_size;
37
0
  assert(total_size <= (size_t)0x7fffffff);
38
0
  return (int)total_size;
39
0
}
40
41
0
static void HistogramClear(VP8LHistogram* const p) {
42
0
  uint32_t* const literal = p->literal_;
43
0
  const int cache_bits = p->palette_code_bits_;
44
0
  const int histo_size = GetHistogramSize(cache_bits);
45
0
  memset(p, 0, histo_size);
46
0
  p->palette_code_bits_ = cache_bits;
47
0
  p->literal_ = literal;
48
0
}
49
50
// Swap two histogram pointers.
51
0
static void HistogramSwap(VP8LHistogram** const A, VP8LHistogram** const B) {
52
0
  VP8LHistogram* const tmp = *A;
53
0
  *A = *B;
54
0
  *B = tmp;
55
0
}
56
57
static void HistogramCopy(const VP8LHistogram* const src,
58
0
                          VP8LHistogram* const dst) {
59
0
  uint32_t* const dst_literal = dst->literal_;
60
0
  const int dst_cache_bits = dst->palette_code_bits_;
61
0
  const int literal_size = VP8LHistogramNumCodes(dst_cache_bits);
62
0
  const int histo_size = GetHistogramSize(dst_cache_bits);
63
0
  assert(src->palette_code_bits_ == dst_cache_bits);
64
0
  memcpy(dst, src, histo_size);
65
0
  dst->literal_ = dst_literal;
66
0
  memcpy(dst->literal_, src->literal_, literal_size * sizeof(*dst->literal_));
67
0
}
68
69
0
void VP8LFreeHistogram(VP8LHistogram* const histo) {
70
0
  WebPSafeFree(histo);
71
0
}
72
73
0
void VP8LFreeHistogramSet(VP8LHistogramSet* const histo) {
74
0
  WebPSafeFree(histo);
75
0
}
76
77
void VP8LHistogramStoreRefs(const VP8LBackwardRefs* const refs,
78
0
                            VP8LHistogram* const histo) {
79
0
  VP8LRefsCursor c = VP8LRefsCursorInit(refs);
80
0
  while (VP8LRefsCursorOk(&c)) {
81
0
    VP8LHistogramAddSinglePixOrCopy(histo, c.cur_pos, NULL, 0);
82
0
    VP8LRefsCursorNext(&c);
83
0
  }
84
0
}
85
86
void VP8LHistogramCreate(VP8LHistogram* const p,
87
                         const VP8LBackwardRefs* const refs,
88
0
                         int palette_code_bits) {
89
0
  if (palette_code_bits >= 0) {
90
0
    p->palette_code_bits_ = palette_code_bits;
91
0
  }
92
0
  HistogramClear(p);
93
0
  VP8LHistogramStoreRefs(refs, p);
94
0
}
95
96
void VP8LHistogramInit(VP8LHistogram* const p, int palette_code_bits,
97
0
                       int init_arrays) {
98
0
  p->palette_code_bits_ = palette_code_bits;
99
0
  if (init_arrays) {
100
0
    HistogramClear(p);
101
0
  } else {
102
0
    p->trivial_symbol_ = 0;
103
0
    p->bit_cost_ = 0;
104
0
    p->literal_cost_ = 0;
105
0
    p->red_cost_ = 0;
106
0
    p->blue_cost_ = 0;
107
0
    memset(p->is_used_, 0, sizeof(p->is_used_));
108
0
  }
109
0
}
110
111
0
VP8LHistogram* VP8LAllocateHistogram(int cache_bits) {
112
0
  VP8LHistogram* histo = NULL;
113
0
  const int total_size = GetHistogramSize(cache_bits);
114
0
  uint8_t* const memory = (uint8_t*)WebPSafeMalloc(total_size, sizeof(*memory));
115
0
  if (memory == NULL) return NULL;
116
0
  histo = (VP8LHistogram*)memory;
117
  // literal_ won't necessary be aligned.
118
0
  histo->literal_ = (uint32_t*)(memory + sizeof(VP8LHistogram));
119
0
  VP8LHistogramInit(histo, cache_bits, /*init_arrays=*/ 0);
120
0
  return histo;
121
0
}
122
123
// Resets the pointers of the histograms to point to the bit buffer in the set.
124
static void HistogramSetResetPointers(VP8LHistogramSet* const set,
125
0
                                      int cache_bits) {
126
0
  int i;
127
0
  const int histo_size = GetHistogramSize(cache_bits);
128
0
  uint8_t* memory = (uint8_t*) (set->histograms);
129
0
  memory += set->max_size * sizeof(*set->histograms);
130
0
  for (i = 0; i < set->max_size; ++i) {
131
0
    memory = (uint8_t*) WEBP_ALIGN(memory);
132
0
    set->histograms[i] = (VP8LHistogram*) memory;
133
    // literal_ won't necessary be aligned.
134
0
    set->histograms[i]->literal_ = (uint32_t*)(memory + sizeof(VP8LHistogram));
135
0
    memory += histo_size;
136
0
  }
137
0
}
138
139
// Returns the total size of the VP8LHistogramSet.
140
0
static size_t HistogramSetTotalSize(int size, int cache_bits) {
141
0
  const int histo_size = GetHistogramSize(cache_bits);
142
0
  return (sizeof(VP8LHistogramSet) + size * (sizeof(VP8LHistogram*) +
143
0
          histo_size + WEBP_ALIGN_CST));
144
0
}
145
146
0
VP8LHistogramSet* VP8LAllocateHistogramSet(int size, int cache_bits) {
147
0
  int i;
148
0
  VP8LHistogramSet* set;
149
0
  const size_t total_size = HistogramSetTotalSize(size, cache_bits);
150
0
  uint8_t* memory = (uint8_t*)WebPSafeMalloc(total_size, sizeof(*memory));
151
0
  if (memory == NULL) return NULL;
152
153
0
  set = (VP8LHistogramSet*)memory;
154
0
  memory += sizeof(*set);
155
0
  set->histograms = (VP8LHistogram**)memory;
156
0
  set->max_size = size;
157
0
  set->size = size;
158
0
  HistogramSetResetPointers(set, cache_bits);
159
0
  for (i = 0; i < size; ++i) {
160
0
    VP8LHistogramInit(set->histograms[i], cache_bits, /*init_arrays=*/ 0);
161
0
  }
162
0
  return set;
163
0
}
164
165
0
void VP8LHistogramSetClear(VP8LHistogramSet* const set) {
166
0
  int i;
167
0
  const int cache_bits = set->histograms[0]->palette_code_bits_;
168
0
  const int size = set->max_size;
169
0
  const size_t total_size = HistogramSetTotalSize(size, cache_bits);
170
0
  uint8_t* memory = (uint8_t*)set;
171
172
0
  memset(memory, 0, total_size);
173
0
  memory += sizeof(*set);
174
0
  set->histograms = (VP8LHistogram**)memory;
175
0
  set->max_size = size;
176
0
  set->size = size;
177
0
  HistogramSetResetPointers(set, cache_bits);
178
0
  for (i = 0; i < size; ++i) {
179
0
    set->histograms[i]->palette_code_bits_ = cache_bits;
180
0
  }
181
0
}
182
183
// Removes the histogram 'i' from 'set' by setting it to NULL.
184
static void HistogramSetRemoveHistogram(VP8LHistogramSet* const set, int i,
185
0
                                        int* const num_used) {
186
0
  assert(set->histograms[i] != NULL);
187
0
  set->histograms[i] = NULL;
188
0
  --*num_used;
189
  // If we remove the last valid one, shrink until the next valid one.
190
0
  if (i == set->size - 1) {
191
0
    while (set->size >= 1 && set->histograms[set->size - 1] == NULL) {
192
0
      --set->size;
193
0
    }
194
0
  }
195
0
}
196
197
// -----------------------------------------------------------------------------
198
199
void VP8LHistogramAddSinglePixOrCopy(VP8LHistogram* const histo,
200
                                     const PixOrCopy* const v,
201
                                     int (*const distance_modifier)(int, int),
202
0
                                     int distance_modifier_arg0) {
203
0
  if (PixOrCopyIsLiteral(v)) {
204
0
    ++histo->alpha_[PixOrCopyLiteral(v, 3)];
205
0
    ++histo->red_[PixOrCopyLiteral(v, 2)];
206
0
    ++histo->literal_[PixOrCopyLiteral(v, 1)];
207
0
    ++histo->blue_[PixOrCopyLiteral(v, 0)];
208
0
  } else if (PixOrCopyIsCacheIdx(v)) {
209
0
    const int literal_ix =
210
0
        NUM_LITERAL_CODES + NUM_LENGTH_CODES + PixOrCopyCacheIdx(v);
211
0
    assert(histo->palette_code_bits_ != 0);
212
0
    ++histo->literal_[literal_ix];
213
0
  } else {
214
0
    int code, extra_bits;
215
0
    VP8LPrefixEncodeBits(PixOrCopyLength(v), &code, &extra_bits);
216
0
    ++histo->literal_[NUM_LITERAL_CODES + code];
217
0
    if (distance_modifier == NULL) {
218
0
      VP8LPrefixEncodeBits(PixOrCopyDistance(v), &code, &extra_bits);
219
0
    } else {
220
0
      VP8LPrefixEncodeBits(
221
0
          distance_modifier(distance_modifier_arg0, PixOrCopyDistance(v)),
222
0
          &code, &extra_bits);
223
0
    }
224
0
    ++histo->distance_[code];
225
0
  }
226
0
}
227
228
// -----------------------------------------------------------------------------
229
// Entropy-related functions.
230
231
0
static WEBP_INLINE uint64_t BitsEntropyRefine(const VP8LBitEntropy* entropy) {
232
0
  uint64_t mix;
233
0
  if (entropy->nonzeros < 5) {
234
0
    if (entropy->nonzeros <= 1) {
235
0
      return 0;
236
0
    }
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
0
    if (entropy->nonzeros == 2) {
241
0
      return DivRound(99 * ((uint64_t)entropy->sum << LOG_2_PRECISION_BITS) +
242
0
                          entropy->entropy,
243
0
                      100);
244
0
    }
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
0
    if (entropy->nonzeros == 3) {
250
0
      mix = 950;
251
0
    } else {
252
0
      mix = 700;  // nonzeros == 4.
253
0
    }
254
0
  } else {
255
0
    mix = 627;
256
0
  }
257
258
0
  {
259
0
    uint64_t min_limit = (uint64_t)(2 * entropy->sum - entropy->max_val)
260
0
                         << LOG_2_PRECISION_BITS;
261
0
    min_limit =
262
0
        DivRound(mix * min_limit + (1000 - mix) * entropy->entropy, 1000);
263
0
    return (entropy->entropy < min_limit) ? min_limit : entropy->entropy;
264
0
  }
265
0
}
266
267
0
uint64_t VP8LBitsEntropy(const uint32_t* const array, int n) {
268
0
  VP8LBitEntropy entropy;
269
0
  VP8LBitsEntropyUnrefined(array, n, &entropy);
270
271
0
  return BitsEntropyRefine(&entropy);
272
0
}
273
274
0
static uint64_t InitialHuffmanCost(void) {
275
  // Small bias because Huffman code length is typically not stored in
276
  // full length.
277
0
  static const uint64_t kHuffmanCodeOfHuffmanCodeSize = CODE_LENGTH_CODES * 3;
278
  // Subtract a bias of 9.1.
279
0
  return (kHuffmanCodeOfHuffmanCodeSize << LOG_2_PRECISION_BITS) -
280
0
         DivRound(91ll << LOG_2_PRECISION_BITS, 10);
281
0
}
282
283
// Finalize the Huffman cost based on streak numbers and length type (<3 or >=3)
284
0
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
0
  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
0
  uint64_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
0
  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
0
  retval_extra += 1840 * stats->streaks[0][0];
297
  // Originally 26/8.
298
0
  retval_extra += 3360 * stats->streaks[1][0];
299
0
  return retval + (retval_extra << (LOG_2_PRECISION_BITS - 10));
300
0
}
301
302
// Get the symbol entropy for the distribution 'population'.
303
// Set 'trivial_sym', if there's only one symbol present in the distribution.
304
static uint64_t PopulationCost(const uint32_t* const population, int length,
305
                               uint32_t* const trivial_sym,
306
0
                               uint8_t* const is_used) {
307
0
  VP8LBitEntropy bit_entropy;
308
0
  VP8LStreaks stats;
309
0
  VP8LGetEntropyUnrefined(population, length, &bit_entropy, &stats);
310
0
  if (trivial_sym != NULL) {
311
0
    *trivial_sym = (bit_entropy.nonzeros == 1) ? bit_entropy.nonzero_code
312
0
                                               : VP8L_NON_TRIVIAL_SYM;
313
0
  }
314
  // The histogram is used if there is at least one non-zero streak.
315
0
  *is_used = (stats.streaks[1][0] != 0 || stats.streaks[1][1] != 0);
316
317
0
  return BitsEntropyRefine(&bit_entropy) + FinalHuffmanCost(&stats);
318
0
}
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.
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
0
                                               int trivial_at_end) {
327
0
  VP8LStreaks stats;
328
0
  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
0
    memset(&stats, 0, sizeof(stats));
334
    // Deal with the non-zero value at index 0 or length-1.
335
0
    stats.streaks[1][0] = 1;
336
    // Deal with the following/previous zero streak.
337
0
    stats.counts[0] = 1;
338
0
    stats.streaks[0][1] = length - 1;
339
0
    return FinalHuffmanCost(&stats);
340
0
  } else {
341
0
    VP8LBitEntropy bit_entropy;
342
0
    if (is_X_used) {
343
0
      if (is_Y_used) {
344
0
        VP8LGetCombinedEntropyUnrefined(X, Y, length, &bit_entropy, &stats);
345
0
      } else {
346
0
        VP8LGetEntropyUnrefined(X, length, &bit_entropy, &stats);
347
0
      }
348
0
    } else {
349
0
      if (is_Y_used) {
350
0
        VP8LGetEntropyUnrefined(Y, length, &bit_entropy, &stats);
351
0
      } else {
352
0
        memset(&stats, 0, sizeof(stats));
353
0
        stats.counts[0] = 1;
354
0
        stats.streaks[0][length > 3] = length;
355
0
        VP8LBitEntropyInit(&bit_entropy);
356
0
      }
357
0
    }
358
359
0
    return BitsEntropyRefine(&bit_entropy) + FinalHuffmanCost(&stats);
360
0
  }
361
0
}
362
363
// Estimates the Entropy + Huffman + other block overhead size cost.
364
0
uint64_t VP8LHistogramEstimateBits(VP8LHistogram* const p) {
365
0
  return PopulationCost(p->literal_,
366
0
                        VP8LHistogramNumCodes(p->palette_code_bits_), NULL,
367
0
                        &p->is_used_[0]) +
368
0
         PopulationCost(p->red_, NUM_LITERAL_CODES, NULL, &p->is_used_[1]) +
369
0
         PopulationCost(p->blue_, NUM_LITERAL_CODES, NULL, &p->is_used_[2]) +
370
0
         PopulationCost(p->alpha_, NUM_LITERAL_CODES, NULL, &p->is_used_[3]) +
371
0
         PopulationCost(p->distance_, NUM_DISTANCE_CODES, NULL,
372
0
                        &p->is_used_[4]) +
373
0
         ((uint64_t)(VP8LExtraCost(p->literal_ + NUM_LITERAL_CODES,
374
0
                                   NUM_LENGTH_CODES) +
375
0
                     VP8LExtraCost(p->distance_, NUM_DISTANCE_CODES))
376
0
          << LOG_2_PRECISION_BITS);
377
0
}
378
379
// -----------------------------------------------------------------------------
380
// Various histogram combine/cost-eval functions
381
382
// Set a + b in b, saturating at WEBP_INT64_MAX.
383
0
static WEBP_INLINE void SaturateAdd(uint64_t a, int64_t* b) {
384
0
  if (*b < 0 || (int64_t)a <= WEBP_INT64_MAX - *b) {
385
0
    *b += (int64_t)a;
386
0
  } else {
387
0
    *b = WEBP_INT64_MAX;
388
0
  }
389
0
}
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.
393
WEBP_NODISCARD static int GetCombinedHistogramEntropy(
394
    const VP8LHistogram* const a, const VP8LHistogram* const b,
395
0
    int64_t cost_threshold_in, uint64_t* cost) {
396
0
  const int palette_code_bits = a->palette_code_bits_;
397
0
  int trivial_at_end = 0;
398
0
  const uint64_t cost_threshold = (uint64_t)cost_threshold_in;
399
0
  assert(a->palette_code_bits_ == b->palette_code_bits_);
400
0
  if (cost_threshold_in <= 0) return 0;
401
0
  *cost = GetCombinedEntropy(a->literal_, b->literal_,
402
0
                             VP8LHistogramNumCodes(palette_code_bits),
403
0
                             a->is_used_[0], b->is_used_[0], 0);
404
0
  *cost += (uint64_t)VP8LExtraCostCombined(a->literal_ + NUM_LITERAL_CODES,
405
0
                                           b->literal_ + NUM_LITERAL_CODES,
406
0
                                           NUM_LENGTH_CODES)
407
0
           << LOG_2_PRECISION_BITS;
408
0
  if (*cost >= cost_threshold) return 0;
409
410
0
  if (a->trivial_symbol_ != VP8L_NON_TRIVIAL_SYM &&
411
0
      a->trivial_symbol_ == b->trivial_symbol_) {
412
    // A, R and B are all 0 or 0xff.
413
0
    const uint32_t color_a = (a->trivial_symbol_ >> 24) & 0xff;
414
0
    const uint32_t color_r = (a->trivial_symbol_ >> 16) & 0xff;
415
0
    const uint32_t color_b = (a->trivial_symbol_ >> 0) & 0xff;
416
0
    if ((color_a == 0 || color_a == 0xff) &&
417
0
        (color_r == 0 || color_r == 0xff) &&
418
0
        (color_b == 0 || color_b == 0xff)) {
419
0
      trivial_at_end = 1;
420
0
    }
421
0
  }
422
423
0
  *cost += GetCombinedEntropy(a->red_, b->red_, NUM_LITERAL_CODES,
424
0
                              a->is_used_[1], b->is_used_[1], trivial_at_end);
425
0
  if (*cost >= cost_threshold) return 0;
426
427
0
  *cost += GetCombinedEntropy(a->blue_, b->blue_, NUM_LITERAL_CODES,
428
0
                              a->is_used_[2], b->is_used_[2], trivial_at_end);
429
0
  if (*cost >= cost_threshold) return 0;
430
431
0
  *cost += GetCombinedEntropy(a->alpha_, b->alpha_, NUM_LITERAL_CODES,
432
0
                              a->is_used_[3], b->is_used_[3], trivial_at_end);
433
0
  if (*cost >= cost_threshold) return 0;
434
435
0
  *cost += GetCombinedEntropy(a->distance_, b->distance_, NUM_DISTANCE_CODES,
436
0
                              a->is_used_[4], b->is_used_[4], 0);
437
0
  *cost += (uint64_t)VP8LExtraCostCombined(a->distance_, b->distance_,
438
0
                                           NUM_DISTANCE_CODES)
439
0
           << LOG_2_PRECISION_BITS;
440
0
  if (*cost >= cost_threshold) return 0;
441
442
0
  return 1;
443
0
}
444
445
static WEBP_INLINE void HistogramAdd(const VP8LHistogram* const a,
446
                                     const VP8LHistogram* const b,
447
0
                                     VP8LHistogram* const out) {
448
0
  VP8LHistogramAdd(a, b, out);
449
0
  out->trivial_symbol_ = (a->trivial_symbol_ == b->trivial_symbol_)
450
0
                       ? a->trivial_symbol_
451
0
                       : VP8L_NON_TRIVIAL_SYM;
452
0
}
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.
462
WEBP_NODISCARD static int HistogramAddEval(const VP8LHistogram* const a,
463
                                           const VP8LHistogram* const b,
464
                                           VP8LHistogram* const out,
465
0
                                           int64_t cost_threshold) {
466
0
  uint64_t cost;
467
0
  const uint64_t sum_cost = a->bit_cost_ + b->bit_cost_;
468
0
  SaturateAdd(sum_cost, &cost_threshold);
469
0
  if (!GetCombinedHistogramEntropy(a, b, cost_threshold, &cost)) return 0;
470
471
0
  HistogramAdd(a, b, out);
472
0
  out->bit_cost_ = cost;
473
0
  out->palette_code_bits_ = a->palette_code_bits_;
474
0
  return 1;
475
0
}
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.
482
WEBP_NODISCARD static int HistogramAddThresh(const VP8LHistogram* const a,
483
                                             const VP8LHistogram* const b,
484
                                             int64_t cost_threshold,
485
0
                                             int64_t* cost_out) {
486
0
  uint64_t cost;
487
0
  assert(a != NULL && b != NULL);
488
0
  SaturateAdd(a->bit_cost_, &cost_threshold);
489
0
  if (!GetCombinedHistogramEntropy(a, b, cost_threshold, &cost)) return 0;
490
491
0
  *cost_out = (int64_t)cost - (int64_t)a->bit_cost_;
492
0
  return 1;
493
0
}
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
508
0
static void DominantCostRangeInit(DominantCostRange* const c) {
509
0
  c->literal_max_ = 0;
510
0
  c->literal_min_ = WEBP_UINT64_MAX;
511
0
  c->red_max_ = 0;
512
0
  c->red_min_ = WEBP_UINT64_MAX;
513
0
  c->blue_max_ = 0;
514
0
  c->blue_min_ = WEBP_UINT64_MAX;
515
0
}
516
517
static void UpdateDominantCostRange(
518
0
    const VP8LHistogram* const h, DominantCostRange* const c) {
519
0
  if (c->literal_max_ < h->literal_cost_) c->literal_max_ = h->literal_cost_;
520
0
  if (c->literal_min_ > h->literal_cost_) c->literal_min_ = h->literal_cost_;
521
0
  if (c->red_max_ < h->red_cost_) c->red_max_ = h->red_cost_;
522
0
  if (c->red_min_ > h->red_cost_) c->red_min_ = h->red_cost_;
523
0
  if (c->blue_max_ < h->blue_cost_) c->blue_max_ = h->blue_cost_;
524
0
  if (c->blue_min_ > h->blue_cost_) c->blue_min_ = h->blue_cost_;
525
0
}
526
527
0
static void UpdateHistogramCost(VP8LHistogram* const h) {
528
0
  uint32_t alpha_sym, red_sym, blue_sym;
529
0
  const uint64_t alpha_cost =
530
0
      PopulationCost(h->alpha_, NUM_LITERAL_CODES, &alpha_sym, &h->is_used_[3]);
531
0
  const uint64_t distance_cost =
532
0
      PopulationCost(h->distance_, NUM_DISTANCE_CODES, NULL, &h->is_used_[4]) +
533
0
      ((uint64_t)VP8LExtraCost(h->distance_, NUM_DISTANCE_CODES)
534
0
       << LOG_2_PRECISION_BITS);
535
0
  const int num_codes = VP8LHistogramNumCodes(h->palette_code_bits_);
536
0
  h->literal_cost_ =
537
0
      PopulationCost(h->literal_, num_codes, NULL, &h->is_used_[0]) +
538
0
      ((uint64_t)VP8LExtraCost(h->literal_ + NUM_LITERAL_CODES,
539
0
                               NUM_LENGTH_CODES)
540
0
       << LOG_2_PRECISION_BITS);
541
0
  h->red_cost_ =
542
0
      PopulationCost(h->red_, NUM_LITERAL_CODES, &red_sym, &h->is_used_[1]);
543
0
  h->blue_cost_ =
544
0
      PopulationCost(h->blue_, NUM_LITERAL_CODES, &blue_sym, &h->is_used_[2]);
545
0
  h->bit_cost_ = h->literal_cost_ + h->red_cost_ + h->blue_cost_ +
546
0
                 alpha_cost + distance_cost;
547
0
  if ((alpha_sym | red_sym | blue_sym) == VP8L_NON_TRIVIAL_SYM) {
548
0
    h->trivial_symbol_ = VP8L_NON_TRIVIAL_SYM;
549
0
  } else {
550
0
    h->trivial_symbol_ =
551
0
        ((uint32_t)alpha_sym << 24) | (red_sym << 16) | (blue_sym << 0);
552
0
  }
553
0
}
554
555
0
static int GetBinIdForEntropy(uint64_t min, uint64_t max, uint64_t val) {
556
0
  const uint64_t range = max - min;
557
0
  if (range > 0) {
558
0
    const uint64_t delta = val - min;
559
0
    return (int)((NUM_PARTITIONS - 1e-6) * delta / range);
560
0
  } else {
561
0
    return 0;
562
0
  }
563
0
}
564
565
static int GetHistoBinIndex(const VP8LHistogram* const h,
566
0
                            const DominantCostRange* const c, int low_effort) {
567
0
  int bin_id = GetBinIdForEntropy(c->literal_min_, c->literal_max_,
568
0
                                  h->literal_cost_);
569
0
  assert(bin_id < NUM_PARTITIONS);
570
0
  if (!low_effort) {
571
0
    bin_id = bin_id * NUM_PARTITIONS
572
0
           + GetBinIdForEntropy(c->red_min_, c->red_max_, h->red_cost_);
573
0
    bin_id = bin_id * NUM_PARTITIONS
574
0
           + GetBinIdForEntropy(c->blue_min_, c->blue_max_, h->blue_cost_);
575
0
    assert(bin_id < BIN_SIZE);
576
0
  }
577
0
  return bin_id;
578
0
}
579
580
// Construct the histograms from backward references.
581
static void HistogramBuild(
582
    int xsize, int histo_bits, const VP8LBackwardRefs* const backward_refs,
583
0
    VP8LHistogramSet* const image_histo) {
584
0
  int x = 0, y = 0;
585
0
  const int histo_xsize = VP8LSubSampleSize(xsize, histo_bits);
586
0
  VP8LHistogram** const histograms = image_histo->histograms;
587
0
  VP8LRefsCursor c = VP8LRefsCursorInit(backward_refs);
588
0
  assert(histo_bits > 0);
589
0
  VP8LHistogramSetClear(image_histo);
590
0
  while (VP8LRefsCursorOk(&c)) {
591
0
    const PixOrCopy* const v = c.cur_pos;
592
0
    const int ix = (y >> histo_bits) * histo_xsize + (x >> histo_bits);
593
0
    VP8LHistogramAddSinglePixOrCopy(histograms[ix], v, NULL, 0);
594
0
    x += PixOrCopyLength(v);
595
0
    while (x >= xsize) {
596
0
      x -= xsize;
597
0
      ++y;
598
0
    }
599
0
    VP8LRefsCursorNext(&c);
600
0
  }
601
0
}
602
603
// Copies the histograms and computes its bit_cost.
604
static const uint16_t kInvalidHistogramSymbol = (uint16_t)(-1);
605
static void HistogramCopyAndAnalyze(VP8LHistogramSet* const orig_histo,
606
                                    VP8LHistogramSet* const image_histo,
607
                                    int* const num_used,
608
0
                                    uint16_t* const histogram_symbols) {
609
0
  int i, cluster_id;
610
0
  int num_used_orig = *num_used;
611
0
  VP8LHistogram** const orig_histograms = orig_histo->histograms;
612
0
  VP8LHistogram** const histograms = image_histo->histograms;
613
0
  assert(image_histo->max_size == orig_histo->max_size);
614
0
  for (cluster_id = 0, i = 0; i < orig_histo->max_size; ++i) {
615
0
    VP8LHistogram* const histo = orig_histograms[i];
616
0
    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
0
    if (!histo->is_used_[0] && !histo->is_used_[1] && !histo->is_used_[2]
621
0
        && !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
0
      assert(i > 0);
626
0
      HistogramSetRemoveHistogram(image_histo, i, num_used);
627
0
      HistogramSetRemoveHistogram(orig_histo, i, &num_used_orig);
628
0
      histogram_symbols[i] = kInvalidHistogramSymbol;
629
0
    } else {
630
      // Copy histograms from orig_histo[] to image_histo[].
631
0
      HistogramCopy(histo, histograms[i]);
632
0
      histogram_symbols[i] = cluster_id++;
633
0
      assert(cluster_id <= image_histo->max_size);
634
0
    }
635
0
  }
636
0
}
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.
640
static void HistogramAnalyzeEntropyBin(VP8LHistogramSet* const image_histo,
641
                                       uint16_t* const bin_map,
642
0
                                       int low_effort) {
643
0
  int i;
644
0
  VP8LHistogram** const histograms = image_histo->histograms;
645
0
  const int histo_size = image_histo->size;
646
0
  DominantCostRange cost_range;
647
0
  DominantCostRangeInit(&cost_range);
648
649
  // Analyze the dominant (literal, red and blue) entropy costs.
650
0
  for (i = 0; i < histo_size; ++i) {
651
0
    if (histograms[i] == NULL) continue;
652
0
    UpdateDominantCostRange(histograms[i], &cost_range);
653
0
  }
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
0
  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
0
    if (histograms[i] == NULL) continue;
661
0
    bin_map[i] = GetHistoBinIndex(histograms[i], &cost_range, low_effort);
662
0
  }
663
0
}
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.
668
static void HistogramCombineEntropyBin(
669
    VP8LHistogramSet* const image_histo, int* num_used,
670
    const uint16_t* const clusters, uint16_t* const cluster_mappings,
671
    VP8LHistogram* cur_combo, const uint16_t* const bin_map, int num_bins,
672
0
    int32_t combine_cost_factor, int low_effort) {
673
0
  VP8LHistogram** const histograms = image_histo->histograms;
674
0
  int idx;
675
0
  struct {
676
0
    int16_t first;    // position of the histogram that accumulates all
677
                      // histograms with the same bin_id
678
0
    uint16_t num_combine_failures;   // number of combine failures per bin_id
679
0
  } bin_info[BIN_SIZE];
680
681
0
  assert(num_bins <= BIN_SIZE);
682
0
  for (idx = 0; idx < num_bins; ++idx) {
683
0
    bin_info[idx].first = -1;
684
0
    bin_info[idx].num_combine_failures = 0;
685
0
  }
686
687
  // By default, a cluster matches itself.
688
0
  for (idx = 0; idx < *num_used; ++idx) cluster_mappings[idx] = idx;
689
0
  for (idx = 0; idx < image_histo->size; ++idx) {
690
0
    int bin_id, first;
691
0
    if (histograms[idx] == NULL) continue;
692
0
    bin_id = bin_map[idx];
693
0
    first = bin_info[bin_id].first;
694
0
    if (first == -1) {
695
0
      bin_info[bin_id].first = idx;
696
0
    } else if (low_effort) {
697
0
      HistogramAdd(histograms[idx], histograms[first], histograms[first]);
698
0
      HistogramSetRemoveHistogram(image_histo, idx, num_used);
699
0
      cluster_mappings[clusters[idx]] = clusters[first];
700
0
    } else {
701
      // try to merge #idx into #first (both share the same bin_id)
702
0
      const uint64_t bit_cost = histograms[idx]->bit_cost_;
703
0
      const int64_t bit_cost_thresh =
704
0
          -DivRound((int64_t)bit_cost * combine_cost_factor, 100);
705
0
      if (HistogramAddEval(histograms[first], histograms[idx], cur_combo,
706
0
                           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
0
        const int try_combine =
713
0
            (cur_combo->trivial_symbol_ != VP8L_NON_TRIVIAL_SYM) ||
714
0
            ((histograms[idx]->trivial_symbol_ == VP8L_NON_TRIVIAL_SYM) &&
715
0
             (histograms[first]->trivial_symbol_ == VP8L_NON_TRIVIAL_SYM));
716
0
        const int max_combine_failures = 32;
717
0
        if (try_combine ||
718
0
            bin_info[bin_id].num_combine_failures >= max_combine_failures) {
719
          // move the (better) merged histogram to its final slot
720
0
          HistogramSwap(&cur_combo, &histograms[first]);
721
0
          HistogramSetRemoveHistogram(image_histo, idx, num_used);
722
0
          cluster_mappings[clusters[idx]] = clusters[first];
723
0
        } else {
724
0
          ++bin_info[bin_id].num_combine_failures;
725
0
        }
726
0
      }
727
0
    }
728
0
  }
729
0
  if (low_effort) {
730
    // for low_effort case, update the final cost when everything is merged
731
0
    for (idx = 0; idx < image_histo->size; ++idx) {
732
0
      if (histograms[idx] == NULL) continue;
733
0
      UpdateHistogramCost(histograms[idx]);
734
0
    }
735
0
  }
736
0
}
737
738
// Implement a Lehmer random number generator with a multiplicative constant of
739
// 48271 and a modulo constant of 2^31 - 1.
740
0
static uint32_t MyRand(uint32_t* const seed) {
741
0
  *seed = (uint32_t)(((uint64_t)(*seed) * 48271u) % 2147483647u);
742
0
  assert(*seed > 0);
743
0
  return *seed;
744
0
}
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
763
0
static int HistoQueueInit(HistoQueue* const histo_queue, const int max_size) {
764
0
  histo_queue->size = 0;
765
0
  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
0
  histo_queue->queue = (HistogramPair*)WebPSafeMalloc(
769
0
      histo_queue->max_size + 1, sizeof(*histo_queue->queue));
770
0
  return histo_queue->queue != NULL;
771
0
}
772
773
0
static void HistoQueueClear(HistoQueue* const histo_queue) {
774
0
  assert(histo_queue != NULL);
775
0
  WebPSafeFree(histo_queue->queue);
776
0
  histo_queue->size = 0;
777
0
  histo_queue->max_size = 0;
778
0
}
779
780
// Pop a specific pair in the queue by replacing it with the last one
781
// and shrinking the queue.
782
static void HistoQueuePopPair(HistoQueue* const histo_queue,
783
0
                              HistogramPair* const pair) {
784
0
  assert(pair >= histo_queue->queue &&
785
0
         pair < (histo_queue->queue + histo_queue->size));
786
0
  assert(histo_queue->size > 0);
787
0
  *pair = histo_queue->queue[histo_queue->size - 1];
788
0
  --histo_queue->size;
789
0
}
790
791
// Check whether a pair in the queue should be updated as head or not.
792
static void HistoQueueUpdateHead(HistoQueue* const histo_queue,
793
0
                                 HistogramPair* const pair) {
794
0
  assert(pair->cost_diff < 0);
795
0
  assert(pair >= histo_queue->queue &&
796
0
         pair < (histo_queue->queue + histo_queue->size));
797
0
  assert(histo_queue->size > 0);
798
0
  if (pair->cost_diff < histo_queue->queue[0].cost_diff) {
799
    // Replace the best pair.
800
0
    const HistogramPair tmp = histo_queue->queue[0];
801
0
    histo_queue->queue[0] = *pair;
802
0
    *pair = tmp;
803
0
  }
804
0
}
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.
810
WEBP_NODISCARD static int HistoQueueUpdatePair(const VP8LHistogram* const h1,
811
                                               const VP8LHistogram* const h2,
812
                                               int64_t cost_threshold,
813
0
                                               HistogramPair* const pair) {
814
0
  const int64_t sum_cost = h1->bit_cost_ + h2->bit_cost_;
815
0
  SaturateAdd(sum_cost, &cost_threshold);
816
0
  if (!GetCombinedHistogramEntropy(h1, h2, cost_threshold, &pair->cost_combo)) {
817
0
    return 0;
818
0
  }
819
0
  pair->cost_diff = (int64_t)pair->cost_combo - sum_cost;
820
0
  return 1;
821
0
}
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.
826
static int64_t HistoQueuePush(HistoQueue* const histo_queue,
827
                              VP8LHistogram** const histograms, int idx1,
828
0
                              int idx2, int64_t threshold) {
829
0
  const VP8LHistogram* h1;
830
0
  const VP8LHistogram* h2;
831
0
  HistogramPair pair;
832
833
  // Stop here if the queue is full.
834
0
  if (histo_queue->size == histo_queue->max_size) return 0;
835
0
  assert(threshold <= 0);
836
0
  if (idx1 > idx2) {
837
0
    const int tmp = idx2;
838
0
    idx2 = idx1;
839
0
    idx1 = tmp;
840
0
  }
841
0
  pair.idx1 = idx1;
842
0
  pair.idx2 = idx2;
843
0
  h1 = histograms[idx1];
844
0
  h2 = histograms[idx2];
845
846
  // Do not even consider the pair if it does not improve the entropy.
847
0
  if (!HistoQueueUpdatePair(h1, h2, threshold, &pair)) return 0;
848
849
0
  histo_queue->queue[histo_queue->size++] = pair;
850
0
  HistoQueueUpdateHead(histo_queue, &histo_queue->queue[histo_queue->size - 1]);
851
852
0
  return pair.cost_diff;
853
0
}
854
855
// -----------------------------------------------------------------------------
856
857
// Combines histograms by continuously choosing the one with the highest cost
858
// reduction.
859
static int HistogramCombineGreedy(VP8LHistogramSet* const image_histo,
860
0
                                  int* const num_used) {
861
0
  int ok = 0;
862
0
  const int image_histo_size = image_histo->size;
863
0
  int i, j;
864
0
  VP8LHistogram** const histograms = image_histo->histograms;
865
  // Priority queue of histogram pairs.
866
0
  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
0
  if (!HistoQueueInit(&histo_queue, image_histo_size * image_histo_size)) {
876
0
    goto End;
877
0
  }
878
879
0
  for (i = 0; i < image_histo_size; ++i) {
880
0
    if (image_histo->histograms[i] == NULL) continue;
881
0
    for (j = i + 1; j < image_histo_size; ++j) {
882
      // Initialize queue.
883
0
      if (image_histo->histograms[j] == NULL) continue;
884
0
      HistoQueuePush(&histo_queue, histograms, i, j, 0);
885
0
    }
886
0
  }
887
888
0
  while (histo_queue.size > 0) {
889
0
    const int idx1 = histo_queue.queue[0].idx1;
890
0
    const int idx2 = histo_queue.queue[0].idx2;
891
0
    HistogramAdd(histograms[idx2], histograms[idx1], histograms[idx1]);
892
0
    histograms[idx1]->bit_cost_ = histo_queue.queue[0].cost_combo;
893
894
    // Remove merged histogram.
895
0
    HistogramSetRemoveHistogram(image_histo, idx2, num_used);
896
897
    // Remove pairs intersecting the just combined best pair.
898
0
    for (i = 0; i < histo_queue.size;) {
899
0
      HistogramPair* const p = histo_queue.queue + i;
900
0
      if (p->idx1 == idx1 || p->idx2 == idx1 ||
901
0
          p->idx1 == idx2 || p->idx2 == idx2) {
902
0
        HistoQueuePopPair(&histo_queue, p);
903
0
      } else {
904
0
        HistoQueueUpdateHead(&histo_queue, p);
905
0
        ++i;
906
0
      }
907
0
    }
908
909
    // Push new pairs formed with combined histogram to the queue.
910
0
    for (i = 0; i < image_histo->size; ++i) {
911
0
      if (i == idx1 || image_histo->histograms[i] == NULL) continue;
912
0
      HistoQueuePush(&histo_queue, image_histo->histograms, idx1, i, 0);
913
0
    }
914
0
  }
915
916
0
  ok = 1;
917
918
0
 End:
919
0
  HistoQueueClear(&histo_queue);
920
0
  return ok;
921
0
}
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.
926
0
static int PairComparison(const void* idx1, const void* idx2) {
927
  // To be used with bsearch: <0 when *idx1<*idx2, >0 if >, 0 when ==.
928
0
  return (*(int*) idx1 - *(int*) idx2);
929
0
}
930
static int HistogramCombineStochastic(VP8LHistogramSet* const image_histo,
931
                                      int* const num_used, int min_cluster_size,
932
0
                                      int* const do_greedy) {
933
0
  int j, iter;
934
0
  uint32_t seed = 1;
935
0
  int tries_with_no_success = 0;
936
0
  const int outer_iters = *num_used;
937
0
  const int num_tries_no_success = outer_iters / 2;
938
0
  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
0
  HistoQueue histo_queue;
943
0
  const int kHistoQueueSize = 9;
944
0
  int ok = 0;
945
  // mapping from an index in image_histo with no NULL histogram to the full
946
  // blown image_histo.
947
0
  int* mappings;
948
949
0
  if (*num_used < min_cluster_size) {
950
0
    *do_greedy = 1;
951
0
    return 1;
952
0
  }
953
954
0
  mappings = (int*) WebPSafeMalloc(*num_used, sizeof(*mappings));
955
0
  if (mappings == NULL) return 0;
956
0
  if (!HistoQueueInit(&histo_queue, kHistoQueueSize)) goto End;
957
  // Fill the initial mapping.
958
0
  for (j = 0, iter = 0; iter < image_histo->size; ++iter) {
959
0
    if (histograms[iter] == NULL) continue;
960
0
    mappings[j++] = iter;
961
0
  }
962
0
  assert(j == *num_used);
963
964
  // Collapse similar histograms in 'image_histo'.
965
0
  for (iter = 0;
966
0
       iter < outer_iters && *num_used >= min_cluster_size &&
967
0
           ++tries_with_no_success < num_tries_no_success;
968
0
       ++iter) {
969
0
    int* mapping_index;
970
0
    int64_t best_cost =
971
0
        (histo_queue.size == 0) ? 0 : histo_queue.queue[0].cost_diff;
972
0
    int best_idx1 = -1, best_idx2 = 1;
973
0
    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
0
    const int num_tries = (*num_used) / 2;
977
978
    // Pick random samples.
979
0
    for (j = 0; *num_used >= 2 && j < num_tries; ++j) {
980
0
      int64_t curr_cost;
981
      // Choose two different histograms at random and try to combine them.
982
0
      const uint32_t tmp = MyRand(&seed) % rand_range;
983
0
      uint32_t idx1 = tmp / (*num_used - 1);
984
0
      uint32_t idx2 = tmp % (*num_used - 1);
985
0
      if (idx2 >= idx1) ++idx2;
986
0
      idx1 = mappings[idx1];
987
0
      idx2 = mappings[idx2];
988
989
      // Calculate cost reduction on combination.
990
0
      curr_cost =
991
0
          HistoQueuePush(&histo_queue, histograms, idx1, idx2, best_cost);
992
0
      if (curr_cost < 0) {  // found a better pair?
993
0
        best_cost = curr_cost;
994
        // Empty the queue if we reached full capacity.
995
0
        if (histo_queue.size == histo_queue.max_size) break;
996
0
      }
997
0
    }
998
0
    if (histo_queue.size == 0) continue;
999
1000
    // Get the best histograms.
1001
0
    best_idx1 = histo_queue.queue[0].idx1;
1002
0
    best_idx2 = histo_queue.queue[0].idx2;
1003
0
    assert(best_idx1 < best_idx2);
1004
    // Pop best_idx2 from mappings.
1005
0
    mapping_index = (int*) bsearch(&best_idx2, mappings, *num_used,
1006
0
                                   sizeof(best_idx2), &PairComparison);
1007
0
    assert(mapping_index != NULL);
1008
0
    memmove(mapping_index, mapping_index + 1, sizeof(*mapping_index) *
1009
0
        ((*num_used) - (mapping_index - mappings) - 1));
1010
    // Merge the histograms and remove best_idx2 from the queue.
1011
0
    HistogramAdd(histograms[best_idx2], histograms[best_idx1],
1012
0
                 histograms[best_idx1]);
1013
0
    histograms[best_idx1]->bit_cost_ = histo_queue.queue[0].cost_combo;
1014
0
    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
0
    for (j = 0; j < histo_queue.size;) {
1018
0
      HistogramPair* const p = histo_queue.queue + j;
1019
0
      const int is_idx1_best = p->idx1 == best_idx1 || p->idx1 == best_idx2;
1020
0
      const int is_idx2_best = p->idx2 == best_idx1 || p->idx2 == best_idx2;
1021
0
      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
0
      if (is_idx1_best && is_idx2_best) {
1025
0
        HistoQueuePopPair(&histo_queue, p);
1026
0
        continue;
1027
0
      }
1028
      // Any pair containing one of the two best indices should only refer to
1029
      // best_idx1. Its cost should also be updated.
1030
0
      if (is_idx1_best) {
1031
0
        p->idx1 = best_idx1;
1032
0
        do_eval = 1;
1033
0
      } else if (is_idx2_best) {
1034
0
        p->idx2 = best_idx1;
1035
0
        do_eval = 1;
1036
0
      }
1037
      // Make sure the index order is respected.
1038
0
      if (p->idx1 > p->idx2) {
1039
0
        const int tmp = p->idx2;
1040
0
        p->idx2 = p->idx1;
1041
0
        p->idx1 = tmp;
1042
0
      }
1043
0
      if (do_eval) {
1044
        // Re-evaluate the cost of an updated pair.
1045
0
        if (!HistoQueueUpdatePair(histograms[p->idx1], histograms[p->idx2], 0,
1046
0
                                  p)) {
1047
0
          HistoQueuePopPair(&histo_queue, p);
1048
0
          continue;
1049
0
        }
1050
0
      }
1051
0
      HistoQueueUpdateHead(&histo_queue, p);
1052
0
      ++j;
1053
0
    }
1054
0
    tries_with_no_success = 0;
1055
0
  }
1056
0
  *do_greedy = (*num_used <= min_cluster_size);
1057
0
  ok = 1;
1058
1059
0
 End:
1060
0
  HistoQueueClear(&histo_queue);
1061
0
  WebPSafeFree(mappings);
1062
0
  return ok;
1063
0
}
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.
1071
static void HistogramRemap(const VP8LHistogramSet* const in,
1072
                           VP8LHistogramSet* const out,
1073
0
                           uint16_t* const symbols) {
1074
0
  int i;
1075
0
  VP8LHistogram** const in_histo = in->histograms;
1076
0
  VP8LHistogram** const out_histo = out->histograms;
1077
0
  const int in_size = out->max_size;
1078
0
  const int out_size = out->size;
1079
0
  if (out_size > 1) {
1080
0
    for (i = 0; i < in_size; ++i) {
1081
0
      int best_out = 0;
1082
0
      int64_t best_bits = WEBP_INT64_MAX;
1083
0
      int k;
1084
0
      if (in_histo[i] == NULL) {
1085
        // Arbitrarily set to the previous value if unused to help future LZ77.
1086
0
        symbols[i] = symbols[i - 1];
1087
0
        continue;
1088
0
      }
1089
0
      for (k = 0; k < out_size; ++k) {
1090
0
        int64_t cur_bits;
1091
0
        if (HistogramAddThresh(out_histo[k], in_histo[i], best_bits,
1092
0
                               &cur_bits)) {
1093
0
          best_bits = cur_bits;
1094
0
          best_out = k;
1095
0
        }
1096
0
      }
1097
0
      symbols[i] = best_out;
1098
0
    }
1099
0
  } else {
1100
0
    assert(out_size == 1);
1101
0
    for (i = 0; i < in_size; ++i) {
1102
0
      symbols[i] = 0;
1103
0
    }
1104
0
  }
1105
1106
  // Recompute each out based on raw and symbols.
1107
0
  VP8LHistogramSetClear(out);
1108
0
  out->size = out_size;
1109
1110
0
  for (i = 0; i < in_size; ++i) {
1111
0
    int idx;
1112
0
    if (in_histo[i] == NULL) continue;
1113
0
    idx = symbols[i];
1114
0
    HistogramAdd(in_histo[i], out_histo[idx], out_histo[idx]);
1115
0
  }
1116
0
}
1117
1118
0
static int32_t GetCombineCostFactor(int histo_size, int quality) {
1119
0
  int32_t combine_cost_factor = 16;
1120
0
  if (quality < 90) {
1121
0
    if (histo_size > 256) combine_cost_factor /= 2;
1122
0
    if (histo_size > 512) combine_cost_factor /= 2;
1123
0
    if (histo_size > 1024) combine_cost_factor /= 2;
1124
0
    if (quality <= 50) combine_cost_factor /= 2;
1125
0
  }
1126
0
  return combine_cost_factor;
1127
0
}
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.
1132
static void OptimizeHistogramSymbols(const VP8LHistogramSet* const set,
1133
                                     uint16_t* const cluster_mappings,
1134
                                     int num_clusters,
1135
                                     uint16_t* const cluster_mappings_tmp,
1136
0
                                     uint16_t* const symbols) {
1137
0
  int i, cluster_max;
1138
0
  int do_continue = 1;
1139
  // First, assign the lowest cluster to each pixel.
1140
0
  while (do_continue) {
1141
0
    do_continue = 0;
1142
0
    for (i = 0; i < num_clusters; ++i) {
1143
0
      int k;
1144
0
      k = cluster_mappings[i];
1145
0
      while (k != cluster_mappings[k]) {
1146
0
        cluster_mappings[k] = cluster_mappings[cluster_mappings[k]];
1147
0
        k = cluster_mappings[k];
1148
0
      }
1149
0
      if (k != cluster_mappings[i]) {
1150
0
        do_continue = 1;
1151
0
        cluster_mappings[i] = k;
1152
0
      }
1153
0
    }
1154
0
  }
1155
  // Create a mapping from a cluster id to its minimal version.
1156
0
  cluster_max = 0;
1157
0
  memset(cluster_mappings_tmp, 0,
1158
0
         set->max_size * sizeof(*cluster_mappings_tmp));
1159
0
  assert(cluster_mappings[0] == 0);
1160
  // Re-map the ids.
1161
0
  for (i = 0; i < set->max_size; ++i) {
1162
0
    int cluster;
1163
0
    if (symbols[i] == kInvalidHistogramSymbol) continue;
1164
0
    cluster = cluster_mappings[symbols[i]];
1165
0
    assert(symbols[i] < num_clusters);
1166
0
    if (cluster > 0 && cluster_mappings_tmp[cluster] == 0) {
1167
0
      ++cluster_max;
1168
0
      cluster_mappings_tmp[cluster] = cluster_max;
1169
0
    }
1170
0
    symbols[i] = cluster_mappings_tmp[cluster];
1171
0
  }
1172
1173
  // Make sure all cluster values are used.
1174
0
  cluster_max = 0;
1175
0
  for (i = 0; i < set->max_size; ++i) {
1176
0
    if (symbols[i] == kInvalidHistogramSymbol) continue;
1177
0
    if (symbols[i] <= cluster_max) continue;
1178
0
    ++cluster_max;
1179
0
    assert(symbols[i] == cluster_max);
1180
0
  }
1181
0
}
1182
1183
0
static void RemoveEmptyHistograms(VP8LHistogramSet* const image_histo) {
1184
0
  uint32_t size;
1185
0
  int i;
1186
0
  for (i = 0, size = 0; i < image_histo->size; ++i) {
1187
0
    if (image_histo->histograms[i] == NULL) continue;
1188
0
    image_histo->histograms[size++] = image_histo->histograms[i];
1189
0
  }
1190
0
  image_histo->size = size;
1191
0
}
1192
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
                             uint16_t* const histogram_symbols,
1199
                             const WebPPicture* const pic, int percent_range,
1200
0
                             int* const percent) {
1201
0
  const int histo_xsize =
1202
0
      histogram_bits ? VP8LSubSampleSize(xsize, histogram_bits) : 1;
1203
0
  const int histo_ysize =
1204
0
      histogram_bits ? VP8LSubSampleSize(ysize, histogram_bits) : 1;
1205
0
  const int image_histo_raw_size = histo_xsize * histo_ysize;
1206
0
  VP8LHistogramSet* const orig_histo =
1207
0
      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
0
  const int entropy_combine_num_bins = low_effort ? NUM_PARTITIONS : BIN_SIZE;
1212
0
  int entropy_combine;
1213
0
  uint16_t* const map_tmp =
1214
0
      (uint16_t*)WebPSafeMalloc(2 * image_histo_raw_size, sizeof(*map_tmp));
1215
0
  uint16_t* const cluster_mappings = map_tmp + image_histo_raw_size;
1216
0
  int num_used = image_histo_raw_size;
1217
0
  if (orig_histo == NULL || map_tmp == NULL) {
1218
0
    WebPEncodingSetError(pic, VP8_ENC_ERROR_OUT_OF_MEMORY);
1219
0
    goto Error;
1220
0
  }
1221
1222
  // Construct the histograms from backward references.
1223
0
  HistogramBuild(xsize, histogram_bits, refs, orig_histo);
1224
  // Copies the histograms and computes its bit_cost.
1225
  // histogram_symbols is optimized
1226
0
  HistogramCopyAndAnalyze(orig_histo, image_histo, &num_used,
1227
0
                          histogram_symbols);
1228
1229
0
  entropy_combine =
1230
0
      (num_used > entropy_combine_num_bins * 2) && (quality < 100);
1231
1232
0
  if (entropy_combine) {
1233
0
    uint16_t* const bin_map = map_tmp;
1234
0
    const int32_t combine_cost_factor =
1235
0
        GetCombineCostFactor(image_histo_raw_size, quality);
1236
0
    const uint32_t num_clusters = num_used;
1237
1238
0
    HistogramAnalyzeEntropyBin(image_histo, bin_map, low_effort);
1239
    // Collapse histograms with similar entropy.
1240
0
    HistogramCombineEntropyBin(
1241
0
        image_histo, &num_used, histogram_symbols, cluster_mappings, tmp_histo,
1242
0
        bin_map, entropy_combine_num_bins, combine_cost_factor, low_effort);
1243
0
    OptimizeHistogramSymbols(image_histo, cluster_mappings, num_clusters,
1244
0
                             map_tmp, histogram_symbols);
1245
0
  }
1246
1247
  // Don't combine the histograms using stochastic and greedy heuristics for
1248
  // low-effort compression mode.
1249
0
  if (!low_effort || !entropy_combine) {
1250
0
    const float x = quality / 100.f;
1251
    // cubic ramp between 1 and MAX_HISTO_GREEDY:
1252
0
    const int threshold_size = (int)(1 + (x * x * x) * (MAX_HISTO_GREEDY - 1));
1253
0
    int do_greedy;
1254
0
    if (!HistogramCombineStochastic(image_histo, &num_used, threshold_size,
1255
0
                                    &do_greedy)) {
1256
0
      WebPEncodingSetError(pic, VP8_ENC_ERROR_OUT_OF_MEMORY);
1257
0
      goto Error;
1258
0
    }
1259
0
    if (do_greedy) {
1260
0
      RemoveEmptyHistograms(image_histo);
1261
0
      if (!HistogramCombineGreedy(image_histo, &num_used)) {
1262
0
        WebPEncodingSetError(pic, VP8_ENC_ERROR_OUT_OF_MEMORY);
1263
0
        goto Error;
1264
0
      }
1265
0
    }
1266
0
  }
1267
1268
  // Find the optimal map from original histograms to the final ones.
1269
0
  RemoveEmptyHistograms(image_histo);
1270
0
  HistogramRemap(orig_histo, image_histo, histogram_symbols);
1271
1272
0
  if (!WebPReportProgress(pic, *percent + percent_range, percent)) {
1273
0
    goto Error;
1274
0
  }
1275
1276
0
 Error:
1277
0
  VP8LFreeHistogramSet(orig_histo);
1278
0
  WebPSafeFree(map_tmp);
1279
0
  return (pic->error_code == VP8_ENC_OK);
1280
0
}