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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 "../webp/config.h" |
| 14 #endif |
| 15 |
| 16 #include <math.h> |
| 17 |
| 18 #include "./backward_references.h" |
| 19 #include "./histogram.h" |
| 20 #include "../dsp/lossless.h" |
| 21 #include "../utils/utils.h" |
| 22 |
| 23 #define MAX_COST 1.e38 |
| 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 |
| 31 static void HistogramClear(VP8LHistogram* const p) { |
| 32 uint32_t* const literal = p->literal_; |
| 33 const int cache_bits = p->palette_code_bits_; |
| 34 const int histo_size = VP8LGetHistogramSize(cache_bits); |
| 35 memset(p, 0, histo_size); |
| 36 p->palette_code_bits_ = cache_bits; |
| 37 p->literal_ = literal; |
| 38 } |
| 39 |
| 40 static void HistogramCopy(const VP8LHistogram* const src, |
| 41 VP8LHistogram* const dst) { |
| 42 uint32_t* const dst_literal = dst->literal_; |
| 43 const int dst_cache_bits = dst->palette_code_bits_; |
| 44 const int histo_size = VP8LGetHistogramSize(dst_cache_bits); |
| 45 assert(src->palette_code_bits_ == dst_cache_bits); |
| 46 memcpy(dst, src, histo_size); |
| 47 dst->literal_ = dst_literal; |
| 48 } |
| 49 |
| 50 int VP8LGetHistogramSize(int cache_bits) { |
| 51 const int literal_size = VP8LHistogramNumCodes(cache_bits); |
| 52 const size_t total_size = sizeof(VP8LHistogram) + sizeof(int) * literal_size; |
| 53 assert(total_size <= (size_t)0x7fffffff); |
| 54 return (int)total_size; |
| 55 } |
| 56 |
| 57 void VP8LFreeHistogram(VP8LHistogram* const histo) { |
| 58 WebPSafeFree(histo); |
| 59 } |
| 60 |
| 61 void VP8LFreeHistogramSet(VP8LHistogramSet* const histo) { |
| 62 WebPSafeFree(histo); |
| 63 } |
| 64 |
| 65 void VP8LHistogramStoreRefs(const VP8LBackwardRefs* const refs, |
| 66 VP8LHistogram* const histo) { |
| 67 VP8LRefsCursor c = VP8LRefsCursorInit(refs); |
| 68 while (VP8LRefsCursorOk(&c)) { |
| 69 VP8LHistogramAddSinglePixOrCopy(histo, c.cur_pos); |
| 70 VP8LRefsCursorNext(&c); |
| 71 } |
| 72 } |
| 73 |
| 74 void VP8LHistogramCreate(VP8LHistogram* const p, |
| 75 const VP8LBackwardRefs* const refs, |
| 76 int palette_code_bits) { |
| 77 if (palette_code_bits >= 0) { |
| 78 p->palette_code_bits_ = palette_code_bits; |
| 79 } |
| 80 HistogramClear(p); |
| 81 VP8LHistogramStoreRefs(refs, p); |
| 82 } |
| 83 |
| 84 void VP8LHistogramInit(VP8LHistogram* const p, int palette_code_bits) { |
| 85 p->palette_code_bits_ = palette_code_bits; |
| 86 HistogramClear(p); |
| 87 } |
| 88 |
| 89 VP8LHistogram* VP8LAllocateHistogram(int cache_bits) { |
| 90 VP8LHistogram* histo = NULL; |
| 91 const int total_size = VP8LGetHistogramSize(cache_bits); |
| 92 uint8_t* const memory = (uint8_t*)WebPSafeMalloc(total_size, sizeof(*memory)); |
| 93 if (memory == NULL) return NULL; |
| 94 histo = (VP8LHistogram*)memory; |
| 95 // literal_ won't necessary be aligned. |
| 96 histo->literal_ = (uint32_t*)(memory + sizeof(VP8LHistogram)); |
| 97 VP8LHistogramInit(histo, cache_bits); |
| 98 return histo; |
| 99 } |
| 100 |
| 101 VP8LHistogramSet* VP8LAllocateHistogramSet(int size, int cache_bits) { |
| 102 int i; |
| 103 VP8LHistogramSet* set; |
| 104 const size_t total_size = sizeof(*set) |
| 105 + sizeof(*set->histograms) * size |
| 106 + (size_t)VP8LGetHistogramSize(cache_bits) * size; |
| 107 uint8_t* memory = (uint8_t*)WebPSafeMalloc(total_size, sizeof(*memory)); |
| 108 if (memory == NULL) return NULL; |
| 109 |
| 110 set = (VP8LHistogramSet*)memory; |
| 111 memory += sizeof(*set); |
| 112 set->histograms = (VP8LHistogram**)memory; |
| 113 memory += size * sizeof(*set->histograms); |
| 114 set->max_size = size; |
| 115 set->size = size; |
| 116 for (i = 0; i < size; ++i) { |
| 117 set->histograms[i] = (VP8LHistogram*)memory; |
| 118 // literal_ won't necessary be aligned. |
| 119 set->histograms[i]->literal_ = (uint32_t*)(memory + sizeof(VP8LHistogram)); |
| 120 VP8LHistogramInit(set->histograms[i], cache_bits); |
| 121 // There's no padding/alignment between successive histograms. |
| 122 memory += VP8LGetHistogramSize(cache_bits); |
| 123 } |
| 124 return set; |
| 125 } |
| 126 |
| 127 // ----------------------------------------------------------------------------- |
| 128 |
| 129 void VP8LHistogramAddSinglePixOrCopy(VP8LHistogram* const histo, |
| 130 const PixOrCopy* const v) { |
| 131 if (PixOrCopyIsLiteral(v)) { |
| 132 ++histo->alpha_[PixOrCopyLiteral(v, 3)]; |
| 133 ++histo->red_[PixOrCopyLiteral(v, 2)]; |
| 134 ++histo->literal_[PixOrCopyLiteral(v, 1)]; |
| 135 ++histo->blue_[PixOrCopyLiteral(v, 0)]; |
| 136 } else if (PixOrCopyIsCacheIdx(v)) { |
| 137 const int literal_ix = |
| 138 NUM_LITERAL_CODES + NUM_LENGTH_CODES + PixOrCopyCacheIdx(v); |
| 139 ++histo->literal_[literal_ix]; |
| 140 } else { |
| 141 int code, extra_bits; |
| 142 VP8LPrefixEncodeBits(PixOrCopyLength(v), &code, &extra_bits); |
| 143 ++histo->literal_[NUM_LITERAL_CODES + code]; |
| 144 VP8LPrefixEncodeBits(PixOrCopyDistance(v), &code, &extra_bits); |
| 145 ++histo->distance_[code]; |
| 146 } |
| 147 } |
| 148 |
| 149 static WEBP_INLINE double BitsEntropyRefine(int nonzeros, int sum, int max_val, |
| 150 double retval) { |
| 151 double mix; |
| 152 if (nonzeros < 5) { |
| 153 if (nonzeros <= 1) { |
| 154 return 0; |
| 155 } |
| 156 // Two symbols, they will be 0 and 1 in a Huffman code. |
| 157 // Let's mix in a bit of entropy to favor good clustering when |
| 158 // distributions of these are combined. |
| 159 if (nonzeros == 2) { |
| 160 return 0.99 * sum + 0.01 * retval; |
| 161 } |
| 162 // No matter what the entropy says, we cannot be better than min_limit |
| 163 // with Huffman coding. I am mixing a bit of entropy into the |
| 164 // min_limit since it produces much better (~0.5 %) compression results |
| 165 // perhaps because of better entropy clustering. |
| 166 if (nonzeros == 3) { |
| 167 mix = 0.95; |
| 168 } else { |
| 169 mix = 0.7; // nonzeros == 4. |
| 170 } |
| 171 } else { |
| 172 mix = 0.627; |
| 173 } |
| 174 |
| 175 { |
| 176 double min_limit = 2 * sum - max_val; |
| 177 min_limit = mix * min_limit + (1.0 - mix) * retval; |
| 178 return (retval < min_limit) ? min_limit : retval; |
| 179 } |
| 180 } |
| 181 |
| 182 static double BitsEntropy(const uint32_t* const array, int n) { |
| 183 double retval = 0.; |
| 184 uint32_t sum = 0; |
| 185 int nonzeros = 0; |
| 186 uint32_t max_val = 0; |
| 187 int i; |
| 188 for (i = 0; i < n; ++i) { |
| 189 if (array[i] != 0) { |
| 190 sum += array[i]; |
| 191 ++nonzeros; |
| 192 retval -= VP8LFastSLog2(array[i]); |
| 193 if (max_val < array[i]) { |
| 194 max_val = array[i]; |
| 195 } |
| 196 } |
| 197 } |
| 198 retval += VP8LFastSLog2(sum); |
| 199 return BitsEntropyRefine(nonzeros, sum, max_val, retval); |
| 200 } |
| 201 |
| 202 static double BitsEntropyCombined(const uint32_t* const X, |
| 203 const uint32_t* const Y, int n) { |
| 204 double retval = 0.; |
| 205 int sum = 0; |
| 206 int nonzeros = 0; |
| 207 int max_val = 0; |
| 208 int i; |
| 209 for (i = 0; i < n; ++i) { |
| 210 const int xy = X[i] + Y[i]; |
| 211 if (xy != 0) { |
| 212 sum += xy; |
| 213 ++nonzeros; |
| 214 retval -= VP8LFastSLog2(xy); |
| 215 if (max_val < xy) { |
| 216 max_val = xy; |
| 217 } |
| 218 } |
| 219 } |
| 220 retval += VP8LFastSLog2(sum); |
| 221 return BitsEntropyRefine(nonzeros, sum, max_val, retval); |
| 222 } |
| 223 |
| 224 static double InitialHuffmanCost(void) { |
| 225 // Small bias because Huffman code length is typically not stored in |
| 226 // full length. |
| 227 static const int kHuffmanCodeOfHuffmanCodeSize = CODE_LENGTH_CODES * 3; |
| 228 static const double kSmallBias = 9.1; |
| 229 return kHuffmanCodeOfHuffmanCodeSize - kSmallBias; |
| 230 } |
| 231 |
| 232 // Finalize the Huffman cost based on streak numbers and length type (<3 or >=3) |
| 233 static double FinalHuffmanCost(const VP8LStreaks* const stats) { |
| 234 double retval = InitialHuffmanCost(); |
| 235 retval += stats->counts[0] * 1.5625 + 0.234375 * stats->streaks[0][1]; |
| 236 retval += stats->counts[1] * 2.578125 + 0.703125 * stats->streaks[1][1]; |
| 237 retval += 1.796875 * stats->streaks[0][0]; |
| 238 retval += 3.28125 * stats->streaks[1][0]; |
| 239 return retval; |
| 240 } |
| 241 |
| 242 // Trampolines |
| 243 static double HuffmanCost(const uint32_t* const population, int length) { |
| 244 const VP8LStreaks stats = VP8LHuffmanCostCount(population, length); |
| 245 return FinalHuffmanCost(&stats); |
| 246 } |
| 247 |
| 248 static double HuffmanCostCombined(const uint32_t* const X, |
| 249 const uint32_t* const Y, int length) { |
| 250 const VP8LStreaks stats = VP8LHuffmanCostCombinedCount(X, Y, length); |
| 251 return FinalHuffmanCost(&stats); |
| 252 } |
| 253 |
| 254 // Aggregated costs |
| 255 static double PopulationCost(const uint32_t* const population, int length) { |
| 256 return BitsEntropy(population, length) + HuffmanCost(population, length); |
| 257 } |
| 258 |
| 259 static double GetCombinedEntropy(const uint32_t* const X, |
| 260 const uint32_t* const Y, int length) { |
| 261 return BitsEntropyCombined(X, Y, length) + HuffmanCostCombined(X, Y, length); |
| 262 } |
| 263 |
| 264 // Estimates the Entropy + Huffman + other block overhead size cost. |
| 265 double VP8LHistogramEstimateBits(const VP8LHistogram* const p) { |
| 266 return |
| 267 PopulationCost(p->literal_, VP8LHistogramNumCodes(p->palette_code_bits_)) |
| 268 + PopulationCost(p->red_, NUM_LITERAL_CODES) |
| 269 + PopulationCost(p->blue_, NUM_LITERAL_CODES) |
| 270 + PopulationCost(p->alpha_, NUM_LITERAL_CODES) |
| 271 + PopulationCost(p->distance_, NUM_DISTANCE_CODES) |
| 272 + VP8LExtraCost(p->literal_ + NUM_LITERAL_CODES, NUM_LENGTH_CODES) |
| 273 + VP8LExtraCost(p->distance_, NUM_DISTANCE_CODES); |
| 274 } |
| 275 |
| 276 double VP8LHistogramEstimateBitsBulk(const VP8LHistogram* const p) { |
| 277 return |
| 278 BitsEntropy(p->literal_, VP8LHistogramNumCodes(p->palette_code_bits_)) |
| 279 + BitsEntropy(p->red_, NUM_LITERAL_CODES) |
| 280 + BitsEntropy(p->blue_, NUM_LITERAL_CODES) |
| 281 + BitsEntropy(p->alpha_, NUM_LITERAL_CODES) |
| 282 + BitsEntropy(p->distance_, NUM_DISTANCE_CODES) |
| 283 + VP8LExtraCost(p->literal_ + NUM_LITERAL_CODES, NUM_LENGTH_CODES) |
| 284 + VP8LExtraCost(p->distance_, NUM_DISTANCE_CODES); |
| 285 } |
| 286 |
| 287 // ----------------------------------------------------------------------------- |
| 288 // Various histogram combine/cost-eval functions |
| 289 |
| 290 static int GetCombinedHistogramEntropy(const VP8LHistogram* const a, |
| 291 const VP8LHistogram* const b, |
| 292 double cost_threshold, |
| 293 double* cost) { |
| 294 const int palette_code_bits = a->palette_code_bits_; |
| 295 assert(a->palette_code_bits_ == b->palette_code_bits_); |
| 296 *cost += GetCombinedEntropy(a->literal_, b->literal_, |
| 297 VP8LHistogramNumCodes(palette_code_bits)); |
| 298 *cost += VP8LExtraCostCombined(a->literal_ + NUM_LITERAL_CODES, |
| 299 b->literal_ + NUM_LITERAL_CODES, |
| 300 NUM_LENGTH_CODES); |
| 301 if (*cost > cost_threshold) return 0; |
| 302 |
| 303 *cost += GetCombinedEntropy(a->red_, b->red_, NUM_LITERAL_CODES); |
| 304 if (*cost > cost_threshold) return 0; |
| 305 |
| 306 *cost += GetCombinedEntropy(a->blue_, b->blue_, NUM_LITERAL_CODES); |
| 307 if (*cost > cost_threshold) return 0; |
| 308 |
| 309 *cost += GetCombinedEntropy(a->alpha_, b->alpha_, NUM_LITERAL_CODES); |
| 310 if (*cost > cost_threshold) return 0; |
| 311 |
| 312 *cost += GetCombinedEntropy(a->distance_, b->distance_, NUM_DISTANCE_CODES); |
| 313 *cost += VP8LExtraCostCombined(a->distance_, b->distance_, |
| 314 NUM_DISTANCE_CODES); |
| 315 if (*cost > cost_threshold) return 0; |
| 316 |
| 317 return 1; |
| 318 } |
| 319 |
| 320 // Performs out = a + b, computing the cost C(a+b) - C(a) - C(b) while comparing |
| 321 // to the threshold value 'cost_threshold'. The score returned is |
| 322 // Score = C(a+b) - C(a) - C(b), where C(a) + C(b) is known and fixed. |
| 323 // Since the previous score passed is 'cost_threshold', we only need to compare |
| 324 // the partial cost against 'cost_threshold + C(a) + C(b)' to possibly bail-out |
| 325 // early. |
| 326 static double HistogramAddEval(const VP8LHistogram* const a, |
| 327 const VP8LHistogram* const b, |
| 328 VP8LHistogram* const out, |
| 329 double cost_threshold) { |
| 330 double cost = 0; |
| 331 const double sum_cost = a->bit_cost_ + b->bit_cost_; |
| 332 cost_threshold += sum_cost; |
| 333 |
| 334 if (GetCombinedHistogramEntropy(a, b, cost_threshold, &cost)) { |
| 335 VP8LHistogramAdd(a, b, out); |
| 336 out->bit_cost_ = cost; |
| 337 out->palette_code_bits_ = a->palette_code_bits_; |
| 338 } |
| 339 |
| 340 return cost - sum_cost; |
| 341 } |
| 342 |
| 343 // Same as HistogramAddEval(), except that the resulting histogram |
| 344 // is not stored. Only the cost C(a+b) - C(a) is evaluated. We omit |
| 345 // the term C(b) which is constant over all the evaluations. |
| 346 static double HistogramAddThresh(const VP8LHistogram* const a, |
| 347 const VP8LHistogram* const b, |
| 348 double cost_threshold) { |
| 349 double cost = -a->bit_cost_; |
| 350 GetCombinedHistogramEntropy(a, b, cost_threshold, &cost); |
| 351 return cost; |
| 352 } |
| 353 |
| 354 // ----------------------------------------------------------------------------- |
| 355 |
| 356 // The structure to keep track of cost range for the three dominant entropy |
| 357 // symbols. |
| 358 // TODO(skal): Evaluate if float can be used here instead of double for |
| 359 // representing the entropy costs. |
| 360 typedef struct { |
| 361 double literal_max_; |
| 362 double literal_min_; |
| 363 double red_max_; |
| 364 double red_min_; |
| 365 double blue_max_; |
| 366 double blue_min_; |
| 367 } DominantCostRange; |
| 368 |
| 369 static void DominantCostRangeInit(DominantCostRange* const c) { |
| 370 c->literal_max_ = 0.; |
| 371 c->literal_min_ = MAX_COST; |
| 372 c->red_max_ = 0.; |
| 373 c->red_min_ = MAX_COST; |
| 374 c->blue_max_ = 0.; |
| 375 c->blue_min_ = MAX_COST; |
| 376 } |
| 377 |
| 378 static void UpdateDominantCostRange( |
| 379 const VP8LHistogram* const h, DominantCostRange* const c) { |
| 380 if (c->literal_max_ < h->literal_cost_) c->literal_max_ = h->literal_cost_; |
| 381 if (c->literal_min_ > h->literal_cost_) c->literal_min_ = h->literal_cost_; |
| 382 if (c->red_max_ < h->red_cost_) c->red_max_ = h->red_cost_; |
| 383 if (c->red_min_ > h->red_cost_) c->red_min_ = h->red_cost_; |
| 384 if (c->blue_max_ < h->blue_cost_) c->blue_max_ = h->blue_cost_; |
| 385 if (c->blue_min_ > h->blue_cost_) c->blue_min_ = h->blue_cost_; |
| 386 } |
| 387 |
| 388 static void UpdateHistogramCost(VP8LHistogram* const h) { |
| 389 const double alpha_cost = PopulationCost(h->alpha_, NUM_LITERAL_CODES); |
| 390 const double distance_cost = |
| 391 PopulationCost(h->distance_, NUM_DISTANCE_CODES) + |
| 392 VP8LExtraCost(h->distance_, NUM_DISTANCE_CODES); |
| 393 const int num_codes = VP8LHistogramNumCodes(h->palette_code_bits_); |
| 394 h->literal_cost_ = PopulationCost(h->literal_, num_codes) + |
| 395 VP8LExtraCost(h->literal_ + NUM_LITERAL_CODES, |
| 396 NUM_LENGTH_CODES); |
| 397 h->red_cost_ = PopulationCost(h->red_, NUM_LITERAL_CODES); |
| 398 h->blue_cost_ = PopulationCost(h->blue_, NUM_LITERAL_CODES); |
| 399 h->bit_cost_ = h->literal_cost_ + h->red_cost_ + h->blue_cost_ + |
| 400 alpha_cost + distance_cost; |
| 401 } |
| 402 |
| 403 static int GetBinIdForEntropy(double min, double max, double val) { |
| 404 const double range = max - min + 1e-6; |
| 405 const double delta = val - min; |
| 406 return (int)(NUM_PARTITIONS * delta / range); |
| 407 } |
| 408 |
| 409 // TODO(vikasa): Evaluate, if there's any correlation between red & blue. |
| 410 static int GetHistoBinIndex( |
| 411 const VP8LHistogram* const h, const DominantCostRange* const c) { |
| 412 const int bin_id = |
| 413 GetBinIdForEntropy(c->blue_min_, c->blue_max_, h->blue_cost_) + |
| 414 NUM_PARTITIONS * GetBinIdForEntropy(c->red_min_, c->red_max_, |
| 415 h->red_cost_) + |
| 416 NUM_PARTITIONS * NUM_PARTITIONS * GetBinIdForEntropy(c->literal_min_, |
| 417 c->literal_max_, |
| 418 h->literal_cost_); |
| 419 assert(bin_id < BIN_SIZE); |
| 420 return bin_id; |
| 421 } |
| 422 |
| 423 // Construct the histograms from backward references. |
| 424 static void HistogramBuild( |
| 425 int xsize, int histo_bits, const VP8LBackwardRefs* const backward_refs, |
| 426 VP8LHistogramSet* const image_histo) { |
| 427 int x = 0, y = 0; |
| 428 const int histo_xsize = VP8LSubSampleSize(xsize, histo_bits); |
| 429 VP8LHistogram** const histograms = image_histo->histograms; |
| 430 VP8LRefsCursor c = VP8LRefsCursorInit(backward_refs); |
| 431 assert(histo_bits > 0); |
| 432 // Construct the Histo from a given backward references. |
| 433 while (VP8LRefsCursorOk(&c)) { |
| 434 const PixOrCopy* const v = c.cur_pos; |
| 435 const int ix = (y >> histo_bits) * histo_xsize + (x >> histo_bits); |
| 436 VP8LHistogramAddSinglePixOrCopy(histograms[ix], v); |
| 437 x += PixOrCopyLength(v); |
| 438 while (x >= xsize) { |
| 439 x -= xsize; |
| 440 ++y; |
| 441 } |
| 442 VP8LRefsCursorNext(&c); |
| 443 } |
| 444 } |
| 445 |
| 446 // Copies the histograms and computes its bit_cost. |
| 447 static void HistogramCopyAndAnalyze( |
| 448 VP8LHistogramSet* const orig_histo, VP8LHistogramSet* const image_histo) { |
| 449 int i; |
| 450 const int histo_size = orig_histo->size; |
| 451 VP8LHistogram** const orig_histograms = orig_histo->histograms; |
| 452 VP8LHistogram** const histograms = image_histo->histograms; |
| 453 for (i = 0; i < histo_size; ++i) { |
| 454 VP8LHistogram* const histo = orig_histograms[i]; |
| 455 UpdateHistogramCost(histo); |
| 456 // Copy histograms from orig_histo[] to image_histo[]. |
| 457 HistogramCopy(histo, histograms[i]); |
| 458 } |
| 459 } |
| 460 |
| 461 // Partition histograms to different entropy bins for three dominant (literal, |
| 462 // red and blue) symbol costs and compute the histogram aggregate bit_cost. |
| 463 static void HistogramAnalyzeEntropyBin( |
| 464 VP8LHistogramSet* const image_histo, int16_t* const bin_map) { |
| 465 int i; |
| 466 VP8LHistogram** const histograms = image_histo->histograms; |
| 467 const int histo_size = image_histo->size; |
| 468 const int bin_depth = histo_size + 1; |
| 469 DominantCostRange cost_range; |
| 470 DominantCostRangeInit(&cost_range); |
| 471 |
| 472 // Analyze the dominant (literal, red and blue) entropy costs. |
| 473 for (i = 0; i < histo_size; ++i) { |
| 474 VP8LHistogram* const histo = histograms[i]; |
| 475 UpdateDominantCostRange(histo, &cost_range); |
| 476 } |
| 477 |
| 478 // bin-hash histograms on three of the dominant (literal, red and blue) |
| 479 // symbol costs. |
| 480 for (i = 0; i < histo_size; ++i) { |
| 481 int num_histos; |
| 482 VP8LHistogram* const histo = histograms[i]; |
| 483 const int16_t bin_id = (int16_t)GetHistoBinIndex(histo, &cost_range); |
| 484 const int bin_offset = bin_id * bin_depth; |
| 485 // bin_map[n][0] for every bin 'n' maintains the counter for the number of |
| 486 // histograms in that bin. |
| 487 // Get and increment the num_histos in that bin. |
| 488 num_histos = ++bin_map[bin_offset]; |
| 489 assert(bin_offset + num_histos < bin_depth * BIN_SIZE); |
| 490 // Add histogram i'th index at num_histos (last) position in the bin_map. |
| 491 bin_map[bin_offset + num_histos] = i; |
| 492 } |
| 493 } |
| 494 |
| 495 // Compact the histogram set by moving the valid one left in the set to the |
| 496 // head and moving the ones that have been merged to other histograms towards |
| 497 // the end. |
| 498 // TODO(vikasa): Evaluate if this method can be avoided by altering the code |
| 499 // logic of HistogramCombineEntropyBin main loop. |
| 500 static void HistogramCompactBins(VP8LHistogramSet* const image_histo) { |
| 501 int start = 0; |
| 502 int end = image_histo->size - 1; |
| 503 VP8LHistogram** const histograms = image_histo->histograms; |
| 504 while (start < end) { |
| 505 while (start <= end && histograms[start] != NULL && |
| 506 histograms[start]->bit_cost_ != 0.) { |
| 507 ++start; |
| 508 } |
| 509 while (start <= end && histograms[end]->bit_cost_ == 0.) { |
| 510 histograms[end] = NULL; |
| 511 --end; |
| 512 } |
| 513 if (start < end) { |
| 514 assert(histograms[start] != NULL); |
| 515 assert(histograms[end] != NULL); |
| 516 HistogramCopy(histograms[end], histograms[start]); |
| 517 histograms[end] = NULL; |
| 518 --end; |
| 519 } |
| 520 } |
| 521 image_histo->size = end + 1; |
| 522 } |
| 523 |
| 524 static void HistogramCombineEntropyBin(VP8LHistogramSet* const image_histo, |
| 525 VP8LHistogram* const histos, |
| 526 int16_t* const bin_map, int bin_depth, |
| 527 double combine_cost_factor) { |
| 528 int bin_id; |
| 529 VP8LHistogram* cur_combo = histos; |
| 530 VP8LHistogram** const histograms = image_histo->histograms; |
| 531 |
| 532 for (bin_id = 0; bin_id < BIN_SIZE; ++bin_id) { |
| 533 const int bin_offset = bin_id * bin_depth; |
| 534 const int num_histos = bin_map[bin_offset]; |
| 535 const int idx1 = bin_map[bin_offset + 1]; |
| 536 int n; |
| 537 for (n = 2; n <= num_histos; ++n) { |
| 538 const int idx2 = bin_map[bin_offset + n]; |
| 539 const double bit_cost_idx2 = histograms[idx2]->bit_cost_; |
| 540 if (bit_cost_idx2 > 0.) { |
| 541 const double bit_cost_thresh = -bit_cost_idx2 * combine_cost_factor; |
| 542 const double curr_cost_diff = |
| 543 HistogramAddEval(histograms[idx1], histograms[idx2], |
| 544 cur_combo, bit_cost_thresh); |
| 545 if (curr_cost_diff < bit_cost_thresh) { |
| 546 HistogramCopy(cur_combo, histograms[idx1]); |
| 547 histograms[idx2]->bit_cost_ = 0.; |
| 548 } |
| 549 } |
| 550 } |
| 551 } |
| 552 HistogramCompactBins(image_histo); |
| 553 } |
| 554 |
| 555 static uint32_t MyRand(uint32_t *seed) { |
| 556 *seed *= 16807U; |
| 557 if (*seed == 0) { |
| 558 *seed = 1; |
| 559 } |
| 560 return *seed; |
| 561 } |
| 562 |
| 563 static void HistogramCombine(VP8LHistogramSet* const image_histo, |
| 564 VP8LHistogramSet* const histos, int quality) { |
| 565 int iter; |
| 566 uint32_t seed = 0; |
| 567 int tries_with_no_success = 0; |
| 568 int image_histo_size = image_histo->size; |
| 569 const int iter_mult = (quality < 25) ? 2 : 2 + (quality - 25) / 8; |
| 570 const int outer_iters = image_histo_size * iter_mult; |
| 571 const int num_pairs = image_histo_size / 2; |
| 572 const int num_tries_no_success = outer_iters / 2; |
| 573 const int min_cluster_size = 2; |
| 574 VP8LHistogram** const histograms = image_histo->histograms; |
| 575 VP8LHistogram* cur_combo = histos->histograms[0]; // trial histogram |
| 576 VP8LHistogram* best_combo = histos->histograms[1]; // best histogram so far |
| 577 |
| 578 // Collapse similar histograms in 'image_histo'. |
| 579 for (iter = 0; |
| 580 iter < outer_iters && image_histo_size >= min_cluster_size; |
| 581 ++iter) { |
| 582 double best_cost_diff = 0.; |
| 583 int best_idx1 = -1, best_idx2 = 1; |
| 584 int j; |
| 585 const int num_tries = |
| 586 (num_pairs < image_histo_size) ? num_pairs : image_histo_size; |
| 587 seed += iter; |
| 588 for (j = 0; j < num_tries; ++j) { |
| 589 double curr_cost_diff; |
| 590 // Choose two histograms at random and try to combine them. |
| 591 const uint32_t idx1 = MyRand(&seed) % image_histo_size; |
| 592 const uint32_t tmp = (j & 7) + 1; |
| 593 const uint32_t diff = |
| 594 (tmp < 3) ? tmp : MyRand(&seed) % (image_histo_size - 1); |
| 595 const uint32_t idx2 = (idx1 + diff + 1) % image_histo_size; |
| 596 if (idx1 == idx2) { |
| 597 continue; |
| 598 } |
| 599 |
| 600 // Calculate cost reduction on combining. |
| 601 curr_cost_diff = HistogramAddEval(histograms[idx1], histograms[idx2], |
| 602 cur_combo, best_cost_diff); |
| 603 if (curr_cost_diff < best_cost_diff) { // found a better pair? |
| 604 { // swap cur/best combo histograms |
| 605 VP8LHistogram* const tmp_histo = cur_combo; |
| 606 cur_combo = best_combo; |
| 607 best_combo = tmp_histo; |
| 608 } |
| 609 best_cost_diff = curr_cost_diff; |
| 610 best_idx1 = idx1; |
| 611 best_idx2 = idx2; |
| 612 } |
| 613 } |
| 614 |
| 615 if (best_idx1 >= 0) { |
| 616 HistogramCopy(best_combo, histograms[best_idx1]); |
| 617 // swap best_idx2 slot with last one (which is now unused) |
| 618 --image_histo_size; |
| 619 if (best_idx2 != image_histo_size) { |
| 620 HistogramCopy(histograms[image_histo_size], histograms[best_idx2]); |
| 621 histograms[image_histo_size] = NULL; |
| 622 } |
| 623 tries_with_no_success = 0; |
| 624 } |
| 625 if (++tries_with_no_success >= num_tries_no_success) { |
| 626 break; |
| 627 } |
| 628 } |
| 629 image_histo->size = image_histo_size; |
| 630 } |
| 631 |
| 632 // ----------------------------------------------------------------------------- |
| 633 // Histogram refinement |
| 634 |
| 635 // Find the best 'out' histogram for each of the 'in' histograms. |
| 636 // Note: we assume that out[]->bit_cost_ is already up-to-date. |
| 637 static void HistogramRemap(const VP8LHistogramSet* const orig_histo, |
| 638 const VP8LHistogramSet* const image_histo, |
| 639 uint16_t* const symbols) { |
| 640 int i; |
| 641 VP8LHistogram** const orig_histograms = orig_histo->histograms; |
| 642 VP8LHistogram** const histograms = image_histo->histograms; |
| 643 for (i = 0; i < orig_histo->size; ++i) { |
| 644 int best_out = 0; |
| 645 double best_bits = |
| 646 HistogramAddThresh(histograms[0], orig_histograms[i], MAX_COST); |
| 647 int k; |
| 648 for (k = 1; k < image_histo->size; ++k) { |
| 649 const double cur_bits = |
| 650 HistogramAddThresh(histograms[k], orig_histograms[i], best_bits); |
| 651 if (cur_bits < best_bits) { |
| 652 best_bits = cur_bits; |
| 653 best_out = k; |
| 654 } |
| 655 } |
| 656 symbols[i] = best_out; |
| 657 } |
| 658 |
| 659 // Recompute each out based on raw and symbols. |
| 660 for (i = 0; i < image_histo->size; ++i) { |
| 661 HistogramClear(histograms[i]); |
| 662 } |
| 663 |
| 664 for (i = 0; i < orig_histo->size; ++i) { |
| 665 const int idx = symbols[i]; |
| 666 VP8LHistogramAdd(orig_histograms[i], histograms[idx], histograms[idx]); |
| 667 } |
| 668 } |
| 669 |
| 670 static double GetCombineCostFactor(int histo_size, int quality) { |
| 671 double combine_cost_factor = 0.16; |
| 672 if (histo_size > 256) combine_cost_factor /= 2.; |
| 673 if (histo_size > 512) combine_cost_factor /= 2.; |
| 674 if (histo_size > 1024) combine_cost_factor /= 2.; |
| 675 if (quality <= 50) combine_cost_factor /= 2.; |
| 676 return combine_cost_factor; |
| 677 } |
| 678 |
| 679 int VP8LGetHistoImageSymbols(int xsize, int ysize, |
| 680 const VP8LBackwardRefs* const refs, |
| 681 int quality, int histo_bits, int cache_bits, |
| 682 VP8LHistogramSet* const image_histo, |
| 683 uint16_t* const histogram_symbols) { |
| 684 int ok = 0; |
| 685 const int histo_xsize = histo_bits ? VP8LSubSampleSize(xsize, histo_bits) : 1; |
| 686 const int histo_ysize = histo_bits ? VP8LSubSampleSize(ysize, histo_bits) : 1; |
| 687 const int image_histo_raw_size = histo_xsize * histo_ysize; |
| 688 |
| 689 // The bin_map for every bin follows following semantics: |
| 690 // bin_map[n][0] = num_histo; // The number of histograms in that bin. |
| 691 // bin_map[n][1] = index of first histogram in that bin; |
| 692 // bin_map[n][num_histo] = index of last histogram in that bin; |
| 693 // bin_map[n][num_histo + 1] ... bin_map[n][bin_depth - 1] = un-used indices. |
| 694 const int bin_depth = image_histo_raw_size + 1; |
| 695 int16_t* bin_map = NULL; |
| 696 VP8LHistogramSet* const histos = VP8LAllocateHistogramSet(2, cache_bits); |
| 697 VP8LHistogramSet* const orig_histo = |
| 698 VP8LAllocateHistogramSet(image_histo_raw_size, cache_bits); |
| 699 |
| 700 if (orig_histo == NULL || histos == NULL) { |
| 701 goto Error; |
| 702 } |
| 703 |
| 704 // Don't attempt linear bin-partition heuristic for: |
| 705 // histograms of small sizes, as bin_map will be very sparse and; |
| 706 // Higher qualities (> 90), to preserve the compression gains at those |
| 707 // quality settings. |
| 708 if (orig_histo->size > 2 * BIN_SIZE && quality < 90) { |
| 709 const int bin_map_size = bin_depth * BIN_SIZE; |
| 710 bin_map = (int16_t*)WebPSafeCalloc(bin_map_size, sizeof(*bin_map)); |
| 711 if (bin_map == NULL) goto Error; |
| 712 } |
| 713 |
| 714 // Construct the histograms from backward references. |
| 715 HistogramBuild(xsize, histo_bits, refs, orig_histo); |
| 716 // Copies the histograms and computes its bit_cost. |
| 717 HistogramCopyAndAnalyze(orig_histo, image_histo); |
| 718 |
| 719 if (bin_map != NULL) { |
| 720 const double combine_cost_factor = |
| 721 GetCombineCostFactor(image_histo_raw_size, quality); |
| 722 HistogramAnalyzeEntropyBin(orig_histo, bin_map); |
| 723 // Collapse histograms with similar entropy. |
| 724 HistogramCombineEntropyBin(image_histo, histos->histograms[0], |
| 725 bin_map, bin_depth, combine_cost_factor); |
| 726 } |
| 727 |
| 728 // Collapse similar histograms by random histogram-pair compares. |
| 729 HistogramCombine(image_histo, histos, quality); |
| 730 |
| 731 // Find the optimal map from original histograms to the final ones. |
| 732 HistogramRemap(orig_histo, image_histo, histogram_symbols); |
| 733 |
| 734 ok = 1; |
| 735 |
| 736 Error: |
| 737 WebPSafeFree(bin_map); |
| 738 VP8LFreeHistogramSet(orig_histo); |
| 739 VP8LFreeHistogramSet(histos); |
| 740 return ok; |
| 741 } |
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