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 (at) 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_enc.h" 19 #include "./histogram_enc.h" 20 #include "../dsp/lossless.h" 21 #include "../dsp/lossless_common.h" 22 #include "../utils/utils.h" 23 24 #define MAX_COST 1.e38 25 26 // Number of partitions for the three dominant (literal, red and blue) symbol 27 // costs. 28 #define NUM_PARTITIONS 4 29 // The size of the bin-hash corresponding to the three dominant costs. 30 #define BIN_SIZE (NUM_PARTITIONS * NUM_PARTITIONS * NUM_PARTITIONS) 31 // Maximum number of histograms allowed in greedy combining algorithm. 32 #define MAX_HISTO_GREEDY 100 33 34 static void HistogramClear(VP8LHistogram* const p) { 35 uint32_t* const literal = p->literal_; 36 const int cache_bits = p->palette_code_bits_; 37 const int histo_size = VP8LGetHistogramSize(cache_bits); 38 memset(p, 0, histo_size); 39 p->palette_code_bits_ = cache_bits; 40 p->literal_ = literal; 41 } 42 43 // Swap two histogram pointers. 44 static void HistogramSwap(VP8LHistogram** const A, VP8LHistogram** const B) { 45 VP8LHistogram* const tmp = *A; 46 *A = *B; 47 *B = tmp; 48 } 49 50 static void HistogramCopy(const VP8LHistogram* const src, 51 VP8LHistogram* const dst) { 52 uint32_t* const dst_literal = dst->literal_; 53 const int dst_cache_bits = dst->palette_code_bits_; 54 const int histo_size = VP8LGetHistogramSize(dst_cache_bits); 55 assert(src->palette_code_bits_ == dst_cache_bits); 56 memcpy(dst, src, histo_size); 57 dst->literal_ = dst_literal; 58 } 59 60 int VP8LGetHistogramSize(int cache_bits) { 61 const int literal_size = VP8LHistogramNumCodes(cache_bits); 62 const size_t total_size = sizeof(VP8LHistogram) + sizeof(int) * literal_size; 63 assert(total_size <= (size_t)0x7fffffff); 64 return (int)total_size; 65 } 66 67 void VP8LFreeHistogram(VP8LHistogram* const histo) { 68 WebPSafeFree(histo); 69 } 70 71 void VP8LFreeHistogramSet(VP8LHistogramSet* const histo) { 72 WebPSafeFree(histo); 73 } 74 75 void VP8LHistogramStoreRefs(const VP8LBackwardRefs* const refs, 76 VP8LHistogram* const histo) { 77 VP8LRefsCursor c = VP8LRefsCursorInit(refs); 78 while (VP8LRefsCursorOk(&c)) { 79 VP8LHistogramAddSinglePixOrCopy(histo, c.cur_pos); 80 VP8LRefsCursorNext(&c); 81 } 82 } 83 84 void VP8LHistogramCreate(VP8LHistogram* const p, 85 const VP8LBackwardRefs* const refs, 86 int palette_code_bits) { 87 if (palette_code_bits >= 0) { 88 p->palette_code_bits_ = palette_code_bits; 89 } 90 HistogramClear(p); 91 VP8LHistogramStoreRefs(refs, p); 92 } 93 94 void VP8LHistogramInit(VP8LHistogram* const p, int palette_code_bits) { 95 p->palette_code_bits_ = palette_code_bits; 96 HistogramClear(p); 97 } 98 99 VP8LHistogram* VP8LAllocateHistogram(int cache_bits) { 100 VP8LHistogram* histo = NULL; 101 const int total_size = VP8LGetHistogramSize(cache_bits); 102 uint8_t* const memory = (uint8_t*)WebPSafeMalloc(total_size, sizeof(*memory)); 103 if (memory == NULL) return NULL; 104 histo = (VP8LHistogram*)memory; 105 // literal_ won't necessary be aligned. 106 histo->literal_ = (uint32_t*)(memory + sizeof(VP8LHistogram)); 107 VP8LHistogramInit(histo, cache_bits); 108 return histo; 109 } 110 111 VP8LHistogramSet* VP8LAllocateHistogramSet(int size, int cache_bits) { 112 int i; 113 VP8LHistogramSet* set; 114 const int histo_size = VP8LGetHistogramSize(cache_bits); 115 const size_t total_size = 116 sizeof(*set) + size * (sizeof(*set->histograms) + 117 histo_size + WEBP_ALIGN_CST); 118 uint8_t* memory = (uint8_t*)WebPSafeMalloc(total_size, sizeof(*memory)); 119 if (memory == NULL) return NULL; 120 121 set = (VP8LHistogramSet*)memory; 122 memory += sizeof(*set); 123 set->histograms = (VP8LHistogram**)memory; 124 memory += size * sizeof(*set->histograms); 125 set->max_size = size; 126 set->size = size; 127 for (i = 0; i < size; ++i) { 128 memory = (uint8_t*)WEBP_ALIGN(memory); 129 set->histograms[i] = (VP8LHistogram*)memory; 130 // literal_ won't necessary be aligned. 131 set->histograms[i]->literal_ = (uint32_t*)(memory + sizeof(VP8LHistogram)); 132 VP8LHistogramInit(set->histograms[i], cache_bits); 133 memory += histo_size; 134 } 135 return set; 136 } 137 138 // ----------------------------------------------------------------------------- 139 140 void VP8LHistogramAddSinglePixOrCopy(VP8LHistogram* const histo, 141 const PixOrCopy* const v) { 142 if (PixOrCopyIsLiteral(v)) { 143 ++histo->alpha_[PixOrCopyLiteral(v, 3)]; 144 ++histo->red_[PixOrCopyLiteral(v, 2)]; 145 ++histo->literal_[PixOrCopyLiteral(v, 1)]; 146 ++histo->blue_[PixOrCopyLiteral(v, 0)]; 147 } else if (PixOrCopyIsCacheIdx(v)) { 148 const int literal_ix = 149 NUM_LITERAL_CODES + NUM_LENGTH_CODES + PixOrCopyCacheIdx(v); 150 ++histo->literal_[literal_ix]; 151 } else { 152 int code, extra_bits; 153 VP8LPrefixEncodeBits(PixOrCopyLength(v), &code, &extra_bits); 154 ++histo->literal_[NUM_LITERAL_CODES + code]; 155 VP8LPrefixEncodeBits(PixOrCopyDistance(v), &code, &extra_bits); 156 ++histo->distance_[code]; 157 } 158 } 159 160 // ----------------------------------------------------------------------------- 161 // Entropy-related functions. 162 163 static WEBP_INLINE double BitsEntropyRefine(const VP8LBitEntropy* entropy) { 164 double mix; 165 if (entropy->nonzeros < 5) { 166 if (entropy->nonzeros <= 1) { 167 return 0; 168 } 169 // Two symbols, they will be 0 and 1 in a Huffman code. 170 // Let's mix in a bit of entropy to favor good clustering when 171 // distributions of these are combined. 172 if (entropy->nonzeros == 2) { 173 return 0.99 * entropy->sum + 0.01 * entropy->entropy; 174 } 175 // No matter what the entropy says, we cannot be better than min_limit 176 // with Huffman coding. I am mixing a bit of entropy into the 177 // min_limit since it produces much better (~0.5 %) compression results 178 // perhaps because of better entropy clustering. 179 if (entropy->nonzeros == 3) { 180 mix = 0.95; 181 } else { 182 mix = 0.7; // nonzeros == 4. 183 } 184 } else { 185 mix = 0.627; 186 } 187 188 { 189 double min_limit = 2 * entropy->sum - entropy->max_val; 190 min_limit = mix * min_limit + (1.0 - mix) * entropy->entropy; 191 return (entropy->entropy < min_limit) ? min_limit : entropy->entropy; 192 } 193 } 194 195 double VP8LBitsEntropy(const uint32_t* const array, int n, 196 uint32_t* const trivial_symbol) { 197 VP8LBitEntropy entropy; 198 VP8LBitsEntropyUnrefined(array, n, &entropy); 199 if (trivial_symbol != NULL) { 200 *trivial_symbol = 201 (entropy.nonzeros == 1) ? entropy.nonzero_code : VP8L_NON_TRIVIAL_SYM; 202 } 203 204 return BitsEntropyRefine(&entropy); 205 } 206 207 static double InitialHuffmanCost(void) { 208 // Small bias because Huffman code length is typically not stored in 209 // full length. 210 static const int kHuffmanCodeOfHuffmanCodeSize = CODE_LENGTH_CODES * 3; 211 static const double kSmallBias = 9.1; 212 return kHuffmanCodeOfHuffmanCodeSize - kSmallBias; 213 } 214 215 // Finalize the Huffman cost based on streak numbers and length type (<3 or >=3) 216 static double FinalHuffmanCost(const VP8LStreaks* const stats) { 217 // The constants in this function are experimental and got rounded from 218 // their original values in 1/8 when switched to 1/1024. 219 double retval = InitialHuffmanCost(); 220 // Second coefficient: Many zeros in the histogram are covered efficiently 221 // by a run-length encode. Originally 2/8. 222 retval += stats->counts[0] * 1.5625 + 0.234375 * stats->streaks[0][1]; 223 // Second coefficient: Constant values are encoded less efficiently, but still 224 // RLE'ed. Originally 6/8. 225 retval += stats->counts[1] * 2.578125 + 0.703125 * stats->streaks[1][1]; 226 // 0s are usually encoded more efficiently than non-0s. 227 // Originally 15/8. 228 retval += 1.796875 * stats->streaks[0][0]; 229 // Originally 26/8. 230 retval += 3.28125 * stats->streaks[1][0]; 231 return retval; 232 } 233 234 // Get the symbol entropy for the distribution 'population'. 235 // Set 'trivial_sym', if there's only one symbol present in the distribution. 236 static double PopulationCost(const uint32_t* const population, int length, 237 uint32_t* const trivial_sym) { 238 VP8LBitEntropy bit_entropy; 239 VP8LStreaks stats; 240 VP8LGetEntropyUnrefined(population, length, &bit_entropy, &stats); 241 if (trivial_sym != NULL) { 242 *trivial_sym = (bit_entropy.nonzeros == 1) ? bit_entropy.nonzero_code 243 : VP8L_NON_TRIVIAL_SYM; 244 } 245 246 return BitsEntropyRefine(&bit_entropy) + FinalHuffmanCost(&stats); 247 } 248 249 // trivial_at_end is 1 if the two histograms only have one element that is 250 // non-zero: both the zero-th one, or both the last one. 251 static WEBP_INLINE double GetCombinedEntropy(const uint32_t* const X, 252 const uint32_t* const Y, 253 int length, int trivial_at_end) { 254 VP8LStreaks stats; 255 if (trivial_at_end) { 256 // This configuration is due to palettization that transforms an indexed 257 // pixel into 0xff000000 | (pixel << 8) in VP8LBundleColorMap. 258 // BitsEntropyRefine is 0 for histograms with only one non-zero value. 259 // Only FinalHuffmanCost needs to be evaluated. 260 memset(&stats, 0, sizeof(stats)); 261 // Deal with the non-zero value at index 0 or length-1. 262 stats.streaks[1][0] += 1; 263 // Deal with the following/previous zero streak. 264 stats.counts[0] += 1; 265 stats.streaks[0][1] += length - 1; 266 return FinalHuffmanCost(&stats); 267 } else { 268 VP8LBitEntropy bit_entropy; 269 VP8LGetCombinedEntropyUnrefined(X, Y, length, &bit_entropy, &stats); 270 271 return BitsEntropyRefine(&bit_entropy) + FinalHuffmanCost(&stats); 272 } 273 } 274 275 // Estimates the Entropy + Huffman + other block overhead size cost. 276 double VP8LHistogramEstimateBits(const VP8LHistogram* const p) { 277 return 278 PopulationCost( 279 p->literal_, VP8LHistogramNumCodes(p->palette_code_bits_), NULL) 280 + PopulationCost(p->red_, NUM_LITERAL_CODES, NULL) 281 + PopulationCost(p->blue_, NUM_LITERAL_CODES, NULL) 282 + PopulationCost(p->alpha_, NUM_LITERAL_CODES, NULL) 283 + PopulationCost(p->distance_, NUM_DISTANCE_CODES, NULL) 284 + VP8LExtraCost(p->literal_ + NUM_LITERAL_CODES, NUM_LENGTH_CODES) 285 + VP8LExtraCost(p->distance_, NUM_DISTANCE_CODES); 286 } 287 288 // ----------------------------------------------------------------------------- 289 // Various histogram combine/cost-eval functions 290 291 static int GetCombinedHistogramEntropy(const VP8LHistogram* const a, 292 const VP8LHistogram* const b, 293 double cost_threshold, 294 double* cost) { 295 const int palette_code_bits = a->palette_code_bits_; 296 int trivial_at_end = 0; 297 assert(a->palette_code_bits_ == b->palette_code_bits_); 298 *cost += GetCombinedEntropy(a->literal_, b->literal_, 299 VP8LHistogramNumCodes(palette_code_bits), 0); 300 *cost += VP8LExtraCostCombined(a->literal_ + NUM_LITERAL_CODES, 301 b->literal_ + NUM_LITERAL_CODES, 302 NUM_LENGTH_CODES); 303 if (*cost > cost_threshold) return 0; 304 305 if (a->trivial_symbol_ != VP8L_NON_TRIVIAL_SYM && 306 a->trivial_symbol_ == b->trivial_symbol_) { 307 // A, R and B are all 0 or 0xff. 308 const uint32_t color_a = (a->trivial_symbol_ >> 24) & 0xff; 309 const uint32_t color_r = (a->trivial_symbol_ >> 16) & 0xff; 310 const uint32_t color_b = (a->trivial_symbol_ >> 0) & 0xff; 311 if ((color_a == 0 || color_a == 0xff) && 312 (color_r == 0 || color_r == 0xff) && 313 (color_b == 0 || color_b == 0xff)) { 314 trivial_at_end = 1; 315 } 316 } 317 318 *cost += 319 GetCombinedEntropy(a->red_, b->red_, NUM_LITERAL_CODES, trivial_at_end); 320 if (*cost > cost_threshold) return 0; 321 322 *cost += 323 GetCombinedEntropy(a->blue_, b->blue_, NUM_LITERAL_CODES, trivial_at_end); 324 if (*cost > cost_threshold) return 0; 325 326 *cost += GetCombinedEntropy(a->alpha_, b->alpha_, NUM_LITERAL_CODES, 327 trivial_at_end); 328 if (*cost > cost_threshold) return 0; 329 330 *cost += 331 GetCombinedEntropy(a->distance_, b->distance_, NUM_DISTANCE_CODES, 0); 332 *cost += 333 VP8LExtraCostCombined(a->distance_, b->distance_, NUM_DISTANCE_CODES); 334 if (*cost > cost_threshold) return 0; 335 336 return 1; 337 } 338 339 static WEBP_INLINE void HistogramAdd(const VP8LHistogram* const a, 340 const VP8LHistogram* const b, 341 VP8LHistogram* const out) { 342 VP8LHistogramAdd(a, b, out); 343 out->trivial_symbol_ = (a->trivial_symbol_ == b->trivial_symbol_) 344 ? a->trivial_symbol_ 345 : VP8L_NON_TRIVIAL_SYM; 346 } 347 348 // Performs out = a + b, computing the cost C(a+b) - C(a) - C(b) while comparing 349 // to the threshold value 'cost_threshold'. The score returned is 350 // Score = C(a+b) - C(a) - C(b), where C(a) + C(b) is known and fixed. 351 // Since the previous score passed is 'cost_threshold', we only need to compare 352 // the partial cost against 'cost_threshold + C(a) + C(b)' to possibly bail-out 353 // early. 354 static double HistogramAddEval(const VP8LHistogram* const a, 355 const VP8LHistogram* const b, 356 VP8LHistogram* const out, 357 double cost_threshold) { 358 double cost = 0; 359 const double sum_cost = a->bit_cost_ + b->bit_cost_; 360 cost_threshold += sum_cost; 361 362 if (GetCombinedHistogramEntropy(a, b, cost_threshold, &cost)) { 363 HistogramAdd(a, b, out); 364 out->bit_cost_ = cost; 365 out->palette_code_bits_ = a->palette_code_bits_; 366 } 367 368 return cost - sum_cost; 369 } 370 371 // Same as HistogramAddEval(), except that the resulting histogram 372 // is not stored. Only the cost C(a+b) - C(a) is evaluated. We omit 373 // the term C(b) which is constant over all the evaluations. 374 static double HistogramAddThresh(const VP8LHistogram* const a, 375 const VP8LHistogram* const b, 376 double cost_threshold) { 377 double cost = -a->bit_cost_; 378 GetCombinedHistogramEntropy(a, b, cost_threshold, &cost); 379 return cost; 380 } 381 382 // ----------------------------------------------------------------------------- 383 384 // The structure to keep track of cost range for the three dominant entropy 385 // symbols. 386 // TODO(skal): Evaluate if float can be used here instead of double for 387 // representing the entropy costs. 388 typedef struct { 389 double literal_max_; 390 double literal_min_; 391 double red_max_; 392 double red_min_; 393 double blue_max_; 394 double blue_min_; 395 } DominantCostRange; 396 397 static void DominantCostRangeInit(DominantCostRange* const c) { 398 c->literal_max_ = 0.; 399 c->literal_min_ = MAX_COST; 400 c->red_max_ = 0.; 401 c->red_min_ = MAX_COST; 402 c->blue_max_ = 0.; 403 c->blue_min_ = MAX_COST; 404 } 405 406 static void UpdateDominantCostRange( 407 const VP8LHistogram* const h, DominantCostRange* const c) { 408 if (c->literal_max_ < h->literal_cost_) c->literal_max_ = h->literal_cost_; 409 if (c->literal_min_ > h->literal_cost_) c->literal_min_ = h->literal_cost_; 410 if (c->red_max_ < h->red_cost_) c->red_max_ = h->red_cost_; 411 if (c->red_min_ > h->red_cost_) c->red_min_ = h->red_cost_; 412 if (c->blue_max_ < h->blue_cost_) c->blue_max_ = h->blue_cost_; 413 if (c->blue_min_ > h->blue_cost_) c->blue_min_ = h->blue_cost_; 414 } 415 416 static void UpdateHistogramCost(VP8LHistogram* const h) { 417 uint32_t alpha_sym, red_sym, blue_sym; 418 const double alpha_cost = 419 PopulationCost(h->alpha_, NUM_LITERAL_CODES, &alpha_sym); 420 const double distance_cost = 421 PopulationCost(h->distance_, NUM_DISTANCE_CODES, NULL) + 422 VP8LExtraCost(h->distance_, NUM_DISTANCE_CODES); 423 const int num_codes = VP8LHistogramNumCodes(h->palette_code_bits_); 424 h->literal_cost_ = PopulationCost(h->literal_, num_codes, NULL) + 425 VP8LExtraCost(h->literal_ + NUM_LITERAL_CODES, 426 NUM_LENGTH_CODES); 427 h->red_cost_ = PopulationCost(h->red_, NUM_LITERAL_CODES, &red_sym); 428 h->blue_cost_ = PopulationCost(h->blue_, NUM_LITERAL_CODES, &blue_sym); 429 h->bit_cost_ = h->literal_cost_ + h->red_cost_ + h->blue_cost_ + 430 alpha_cost + distance_cost; 431 if ((alpha_sym | red_sym | blue_sym) == VP8L_NON_TRIVIAL_SYM) { 432 h->trivial_symbol_ = VP8L_NON_TRIVIAL_SYM; 433 } else { 434 h->trivial_symbol_ = 435 ((uint32_t)alpha_sym << 24) | (red_sym << 16) | (blue_sym << 0); 436 } 437 } 438 439 static int GetBinIdForEntropy(double min, double max, double val) { 440 const double range = max - min; 441 if (range > 0.) { 442 const double delta = val - min; 443 return (int)((NUM_PARTITIONS - 1e-6) * delta / range); 444 } else { 445 return 0; 446 } 447 } 448 449 static int GetHistoBinIndex(const VP8LHistogram* const h, 450 const DominantCostRange* const c, int low_effort) { 451 int bin_id = GetBinIdForEntropy(c->literal_min_, c->literal_max_, 452 h->literal_cost_); 453 assert(bin_id < NUM_PARTITIONS); 454 if (!low_effort) { 455 bin_id = bin_id * NUM_PARTITIONS 456 + GetBinIdForEntropy(c->red_min_, c->red_max_, h->red_cost_); 457 bin_id = bin_id * NUM_PARTITIONS 458 + GetBinIdForEntropy(c->blue_min_, c->blue_max_, h->blue_cost_); 459 assert(bin_id < BIN_SIZE); 460 } 461 return bin_id; 462 } 463 464 // Construct the histograms from backward references. 465 static void HistogramBuild( 466 int xsize, int histo_bits, const VP8LBackwardRefs* const backward_refs, 467 VP8LHistogramSet* const image_histo) { 468 int x = 0, y = 0; 469 const int histo_xsize = VP8LSubSampleSize(xsize, histo_bits); 470 VP8LHistogram** const histograms = image_histo->histograms; 471 VP8LRefsCursor c = VP8LRefsCursorInit(backward_refs); 472 assert(histo_bits > 0); 473 while (VP8LRefsCursorOk(&c)) { 474 const PixOrCopy* const v = c.cur_pos; 475 const int ix = (y >> histo_bits) * histo_xsize + (x >> histo_bits); 476 VP8LHistogramAddSinglePixOrCopy(histograms[ix], v); 477 x += PixOrCopyLength(v); 478 while (x >= xsize) { 479 x -= xsize; 480 ++y; 481 } 482 VP8LRefsCursorNext(&c); 483 } 484 } 485 486 // Copies the histograms and computes its bit_cost. 487 static void HistogramCopyAndAnalyze( 488 VP8LHistogramSet* const orig_histo, VP8LHistogramSet* const image_histo) { 489 int i; 490 const int histo_size = orig_histo->size; 491 VP8LHistogram** const orig_histograms = orig_histo->histograms; 492 VP8LHistogram** const histograms = image_histo->histograms; 493 for (i = 0; i < histo_size; ++i) { 494 VP8LHistogram* const histo = orig_histograms[i]; 495 UpdateHistogramCost(histo); 496 // Copy histograms from orig_histo[] to image_histo[]. 497 HistogramCopy(histo, histograms[i]); 498 } 499 } 500 501 // Partition histograms to different entropy bins for three dominant (literal, 502 // red and blue) symbol costs and compute the histogram aggregate bit_cost. 503 static void HistogramAnalyzeEntropyBin(VP8LHistogramSet* const image_histo, 504 uint16_t* const bin_map, 505 int low_effort) { 506 int i; 507 VP8LHistogram** const histograms = image_histo->histograms; 508 const int histo_size = image_histo->size; 509 DominantCostRange cost_range; 510 DominantCostRangeInit(&cost_range); 511 512 // Analyze the dominant (literal, red and blue) entropy costs. 513 for (i = 0; i < histo_size; ++i) { 514 UpdateDominantCostRange(histograms[i], &cost_range); 515 } 516 517 // bin-hash histograms on three of the dominant (literal, red and blue) 518 // symbol costs and store the resulting bin_id for each histogram. 519 for (i = 0; i < histo_size; ++i) { 520 bin_map[i] = GetHistoBinIndex(histograms[i], &cost_range, low_effort); 521 } 522 } 523 524 // Compact image_histo[] by merging some histograms with same bin_id together if 525 // it's advantageous. 526 static VP8LHistogram* HistogramCombineEntropyBin( 527 VP8LHistogramSet* const image_histo, 528 VP8LHistogram* cur_combo, 529 const uint16_t* const bin_map, int bin_map_size, int num_bins, 530 double combine_cost_factor, int low_effort) { 531 VP8LHistogram** const histograms = image_histo->histograms; 532 int idx; 533 // Work in-place: processed histograms are put at the beginning of 534 // image_histo[]. At the end, we just have to truncate the array. 535 int size = 0; 536 struct { 537 int16_t first; // position of the histogram that accumulates all 538 // histograms with the same bin_id 539 uint16_t num_combine_failures; // number of combine failures per bin_id 540 } bin_info[BIN_SIZE]; 541 542 assert(num_bins <= BIN_SIZE); 543 for (idx = 0; idx < num_bins; ++idx) { 544 bin_info[idx].first = -1; 545 bin_info[idx].num_combine_failures = 0; 546 } 547 548 for (idx = 0; idx < bin_map_size; ++idx) { 549 const int bin_id = bin_map[idx]; 550 const int first = bin_info[bin_id].first; 551 assert(size <= idx); 552 if (first == -1) { 553 // just move histogram #idx to its final position 554 histograms[size] = histograms[idx]; 555 bin_info[bin_id].first = size++; 556 } else if (low_effort) { 557 HistogramAdd(histograms[idx], histograms[first], histograms[first]); 558 } else { 559 // try to merge #idx into #first (both share the same bin_id) 560 const double bit_cost = histograms[idx]->bit_cost_; 561 const double bit_cost_thresh = -bit_cost * combine_cost_factor; 562 const double curr_cost_diff = 563 HistogramAddEval(histograms[first], histograms[idx], 564 cur_combo, bit_cost_thresh); 565 if (curr_cost_diff < bit_cost_thresh) { 566 // Try to merge two histograms only if the combo is a trivial one or 567 // the two candidate histograms are already non-trivial. 568 // For some images, 'try_combine' turns out to be false for a lot of 569 // histogram pairs. In that case, we fallback to combining 570 // histograms as usual to avoid increasing the header size. 571 const int try_combine = 572 (cur_combo->trivial_symbol_ != VP8L_NON_TRIVIAL_SYM) || 573 ((histograms[idx]->trivial_symbol_ == VP8L_NON_TRIVIAL_SYM) && 574 (histograms[first]->trivial_symbol_ == VP8L_NON_TRIVIAL_SYM)); 575 const int max_combine_failures = 32; 576 if (try_combine || 577 bin_info[bin_id].num_combine_failures >= max_combine_failures) { 578 // move the (better) merged histogram to its final slot 579 HistogramSwap(&cur_combo, &histograms[first]); 580 } else { 581 histograms[size++] = histograms[idx]; 582 ++bin_info[bin_id].num_combine_failures; 583 } 584 } else { 585 histograms[size++] = histograms[idx]; 586 } 587 } 588 } 589 image_histo->size = size; 590 if (low_effort) { 591 // for low_effort case, update the final cost when everything is merged 592 for (idx = 0; idx < size; ++idx) { 593 UpdateHistogramCost(histograms[idx]); 594 } 595 } 596 return cur_combo; 597 } 598 599 static uint32_t MyRand(uint32_t* const seed) { 600 *seed = (*seed * 16807ull) & 0xffffffffu; 601 if (*seed == 0) { 602 *seed = 1; 603 } 604 return *seed; 605 } 606 607 // ----------------------------------------------------------------------------- 608 // Histogram pairs priority queue 609 610 // Pair of histograms. Negative idx1 value means that pair is out-of-date. 611 typedef struct { 612 int idx1; 613 int idx2; 614 double cost_diff; 615 double cost_combo; 616 } HistogramPair; 617 618 typedef struct { 619 HistogramPair* queue; 620 int size; 621 int max_size; 622 } HistoQueue; 623 624 static int HistoQueueInit(HistoQueue* const histo_queue, const int max_index) { 625 histo_queue->size = 0; 626 // max_index^2 for the queue size is safe. If you look at 627 // HistogramCombineGreedy, and imagine that UpdateQueueFront always pushes 628 // data to the queue, you insert at most: 629 // - max_index*(max_index-1)/2 (the first two for loops) 630 // - max_index - 1 in the last for loop at the first iteration of the while 631 // loop, max_index - 2 at the second iteration ... therefore 632 // max_index*(max_index-1)/2 overall too 633 histo_queue->max_size = max_index * max_index; 634 // We allocate max_size + 1 because the last element at index "size" is 635 // used as temporary data (and it could be up to max_size). 636 histo_queue->queue = (HistogramPair*)WebPSafeMalloc( 637 histo_queue->max_size + 1, sizeof(*histo_queue->queue)); 638 return histo_queue->queue != NULL; 639 } 640 641 static void HistoQueueClear(HistoQueue* const histo_queue) { 642 assert(histo_queue != NULL); 643 WebPSafeFree(histo_queue->queue); 644 } 645 646 static void SwapHistogramPairs(HistogramPair *p1, 647 HistogramPair *p2) { 648 const HistogramPair tmp = *p1; 649 *p1 = *p2; 650 *p2 = tmp; 651 } 652 653 // Given a valid priority queue in range [0, queue_size) this function checks 654 // whether histo_queue[queue_size] should be accepted and swaps it with the 655 // front if it is smaller. Otherwise, it leaves it as is. 656 static void UpdateQueueFront(HistoQueue* const histo_queue) { 657 if (histo_queue->queue[histo_queue->size].cost_diff >= 0) return; 658 659 if (histo_queue->queue[histo_queue->size].cost_diff < 660 histo_queue->queue[0].cost_diff) { 661 SwapHistogramPairs(histo_queue->queue, 662 histo_queue->queue + histo_queue->size); 663 } 664 ++histo_queue->size; 665 666 // We cannot add more elements than the capacity. 667 // The allocation adds an extra element to the official capacity so that 668 // histo_queue->queue[histo_queue->max_size] is read/written within bound. 669 assert(histo_queue->size <= histo_queue->max_size); 670 } 671 672 // ----------------------------------------------------------------------------- 673 674 static void PreparePair(VP8LHistogram** histograms, int idx1, int idx2, 675 HistogramPair* const pair) { 676 VP8LHistogram* h1; 677 VP8LHistogram* h2; 678 double sum_cost; 679 680 if (idx1 > idx2) { 681 const int tmp = idx2; 682 idx2 = idx1; 683 idx1 = tmp; 684 } 685 pair->idx1 = idx1; 686 pair->idx2 = idx2; 687 h1 = histograms[idx1]; 688 h2 = histograms[idx2]; 689 sum_cost = h1->bit_cost_ + h2->bit_cost_; 690 pair->cost_combo = 0.; 691 GetCombinedHistogramEntropy(h1, h2, sum_cost, &pair->cost_combo); 692 pair->cost_diff = pair->cost_combo - sum_cost; 693 } 694 695 // Combines histograms by continuously choosing the one with the highest cost 696 // reduction. 697 static int HistogramCombineGreedy(VP8LHistogramSet* const image_histo) { 698 int ok = 0; 699 int image_histo_size = image_histo->size; 700 int i, j; 701 VP8LHistogram** const histograms = image_histo->histograms; 702 // Indexes of remaining histograms. 703 int* const clusters = 704 (int*)WebPSafeMalloc(image_histo_size, sizeof(*clusters)); 705 // Priority queue of histogram pairs. 706 HistoQueue histo_queue; 707 708 if (!HistoQueueInit(&histo_queue, image_histo_size) || clusters == NULL) { 709 goto End; 710 } 711 712 for (i = 0; i < image_histo_size; ++i) { 713 // Initialize clusters indexes. 714 clusters[i] = i; 715 for (j = i + 1; j < image_histo_size; ++j) { 716 // Initialize positions array. 717 PreparePair(histograms, i, j, &histo_queue.queue[histo_queue.size]); 718 UpdateQueueFront(&histo_queue); 719 } 720 } 721 722 while (image_histo_size > 1 && histo_queue.size > 0) { 723 HistogramPair* copy_to; 724 const int idx1 = histo_queue.queue[0].idx1; 725 const int idx2 = histo_queue.queue[0].idx2; 726 HistogramAdd(histograms[idx2], histograms[idx1], histograms[idx1]); 727 histograms[idx1]->bit_cost_ = histo_queue.queue[0].cost_combo; 728 // Remove merged histogram. 729 for (i = 0; i + 1 < image_histo_size; ++i) { 730 if (clusters[i] >= idx2) { 731 clusters[i] = clusters[i + 1]; 732 } 733 } 734 --image_histo_size; 735 736 // Remove pairs intersecting the just combined best pair. This will 737 // therefore pop the head of the queue. 738 copy_to = histo_queue.queue; 739 for (i = 0; i < histo_queue.size; ++i) { 740 HistogramPair* const p = histo_queue.queue + i; 741 if (p->idx1 == idx1 || p->idx2 == idx1 || 742 p->idx1 == idx2 || p->idx2 == idx2) { 743 // Do not copy the invalid pair. 744 continue; 745 } 746 if (p->cost_diff < histo_queue.queue[0].cost_diff) { 747 // Replace the top of the queue if we found better. 748 SwapHistogramPairs(histo_queue.queue, p); 749 } 750 SwapHistogramPairs(copy_to, p); 751 ++copy_to; 752 } 753 histo_queue.size = (int)(copy_to - histo_queue.queue); 754 755 // Push new pairs formed with combined histogram to the queue. 756 for (i = 0; i < image_histo_size; ++i) { 757 if (clusters[i] != idx1) { 758 PreparePair(histograms, idx1, clusters[i], 759 &histo_queue.queue[histo_queue.size]); 760 UpdateQueueFront(&histo_queue); 761 } 762 } 763 } 764 // Move remaining histograms to the beginning of the array. 765 for (i = 0; i < image_histo_size; ++i) { 766 if (i != clusters[i]) { // swap the two histograms 767 HistogramSwap(&histograms[i], &histograms[clusters[i]]); 768 } 769 } 770 771 image_histo->size = image_histo_size; 772 ok = 1; 773 774 End: 775 WebPSafeFree(clusters); 776 HistoQueueClear(&histo_queue); 777 return ok; 778 } 779 780 static void HistogramCombineStochastic(VP8LHistogramSet* const image_histo, 781 VP8LHistogram* tmp_histo, 782 VP8LHistogram* best_combo, 783 int quality, int min_cluster_size) { 784 int iter; 785 uint32_t seed = 0; 786 int tries_with_no_success = 0; 787 int image_histo_size = image_histo->size; 788 const int iter_mult = (quality < 25) ? 2 : 2 + (quality - 25) / 8; 789 const int outer_iters = image_histo_size * iter_mult; 790 const int num_pairs = image_histo_size / 2; 791 const int num_tries_no_success = outer_iters / 2; 792 int idx2_max = image_histo_size - 1; 793 int do_brute_dorce = 0; 794 VP8LHistogram** const histograms = image_histo->histograms; 795 796 // Collapse similar histograms in 'image_histo'. 797 ++min_cluster_size; 798 for (iter = 0; 799 iter < outer_iters && image_histo_size >= min_cluster_size; 800 ++iter) { 801 double best_cost_diff = 0.; 802 int best_idx1 = -1, best_idx2 = 1; 803 int j; 804 int num_tries = 805 (num_pairs < image_histo_size) ? num_pairs : image_histo_size; 806 // Use a brute force approach if: 807 // - stochastic has not worked for a while and 808 // - if the number of iterations for brute force is less than the number of 809 // iterations if we never find a match ever again stochastically (hence 810 // num_tries times the number of remaining outer iterations). 811 do_brute_dorce = 812 (tries_with_no_success > 10) && 813 (idx2_max * (idx2_max + 1) < 2 * num_tries * (outer_iters - iter)); 814 if (do_brute_dorce) num_tries = idx2_max; 815 816 seed += iter; 817 for (j = 0; j < num_tries; ++j) { 818 double curr_cost_diff; 819 // Choose two histograms at random and try to combine them. 820 uint32_t idx1, idx2; 821 if (do_brute_dorce) { 822 // Use a brute force approach. 823 idx1 = (uint32_t)j; 824 idx2 = (uint32_t)idx2_max; 825 } else { 826 const uint32_t tmp = (j & 7) + 1; 827 const uint32_t diff = 828 (tmp < 3) ? tmp : MyRand(&seed) % (image_histo_size - 1); 829 idx1 = MyRand(&seed) % image_histo_size; 830 idx2 = (idx1 + diff + 1) % image_histo_size; 831 if (idx1 == idx2) { 832 continue; 833 } 834 } 835 836 // Calculate cost reduction on combining. 837 curr_cost_diff = HistogramAddEval(histograms[idx1], histograms[idx2], 838 tmp_histo, best_cost_diff); 839 if (curr_cost_diff < best_cost_diff) { // found a better pair? 840 HistogramSwap(&best_combo, &tmp_histo); 841 best_cost_diff = curr_cost_diff; 842 best_idx1 = idx1; 843 best_idx2 = idx2; 844 } 845 } 846 if (do_brute_dorce) --idx2_max; 847 848 if (best_idx1 >= 0) { 849 HistogramSwap(&best_combo, &histograms[best_idx1]); 850 // swap best_idx2 slot with last one (which is now unused) 851 --image_histo_size; 852 if (idx2_max >= image_histo_size) idx2_max = image_histo_size - 1; 853 if (best_idx2 != image_histo_size) { 854 HistogramSwap(&histograms[image_histo_size], &histograms[best_idx2]); 855 histograms[image_histo_size] = NULL; 856 } 857 tries_with_no_success = 0; 858 } 859 if (++tries_with_no_success >= num_tries_no_success || idx2_max == 0) { 860 break; 861 } 862 } 863 image_histo->size = image_histo_size; 864 } 865 866 // ----------------------------------------------------------------------------- 867 // Histogram refinement 868 869 // Find the best 'out' histogram for each of the 'in' histograms. 870 // Note: we assume that out[]->bit_cost_ is already up-to-date. 871 static void HistogramRemap(const VP8LHistogramSet* const in, 872 const VP8LHistogramSet* const out, 873 uint16_t* const symbols) { 874 int i; 875 VP8LHistogram** const in_histo = in->histograms; 876 VP8LHistogram** const out_histo = out->histograms; 877 const int in_size = in->size; 878 const int out_size = out->size; 879 if (out_size > 1) { 880 for (i = 0; i < in_size; ++i) { 881 int best_out = 0; 882 double best_bits = MAX_COST; 883 int k; 884 for (k = 0; k < out_size; ++k) { 885 const double cur_bits = 886 HistogramAddThresh(out_histo[k], in_histo[i], best_bits); 887 if (k == 0 || cur_bits < best_bits) { 888 best_bits = cur_bits; 889 best_out = k; 890 } 891 } 892 symbols[i] = best_out; 893 } 894 } else { 895 assert(out_size == 1); 896 for (i = 0; i < in_size; ++i) { 897 symbols[i] = 0; 898 } 899 } 900 901 // Recompute each out based on raw and symbols. 902 for (i = 0; i < out_size; ++i) { 903 HistogramClear(out_histo[i]); 904 } 905 906 for (i = 0; i < in_size; ++i) { 907 const int idx = symbols[i]; 908 HistogramAdd(in_histo[i], out_histo[idx], out_histo[idx]); 909 } 910 } 911 912 static double GetCombineCostFactor(int histo_size, int quality) { 913 double combine_cost_factor = 0.16; 914 if (quality < 90) { 915 if (histo_size > 256) combine_cost_factor /= 2.; 916 if (histo_size > 512) combine_cost_factor /= 2.; 917 if (histo_size > 1024) combine_cost_factor /= 2.; 918 if (quality <= 50) combine_cost_factor /= 2.; 919 } 920 return combine_cost_factor; 921 } 922 923 int VP8LGetHistoImageSymbols(int xsize, int ysize, 924 const VP8LBackwardRefs* const refs, 925 int quality, int low_effort, 926 int histo_bits, int cache_bits, 927 VP8LHistogramSet* const image_histo, 928 VP8LHistogramSet* const tmp_histos, 929 uint16_t* const histogram_symbols) { 930 int ok = 0; 931 const int histo_xsize = histo_bits ? VP8LSubSampleSize(xsize, histo_bits) : 1; 932 const int histo_ysize = histo_bits ? VP8LSubSampleSize(ysize, histo_bits) : 1; 933 const int image_histo_raw_size = histo_xsize * histo_ysize; 934 VP8LHistogramSet* const orig_histo = 935 VP8LAllocateHistogramSet(image_histo_raw_size, cache_bits); 936 VP8LHistogram* cur_combo; 937 // Don't attempt linear bin-partition heuristic for 938 // histograms of small sizes (as bin_map will be very sparse) and 939 // maximum quality q==100 (to preserve the compression gains at that level). 940 const int entropy_combine_num_bins = low_effort ? NUM_PARTITIONS : BIN_SIZE; 941 const int entropy_combine = 942 (orig_histo->size > entropy_combine_num_bins * 2) && (quality < 100); 943 944 if (orig_histo == NULL) goto Error; 945 946 // Construct the histograms from backward references. 947 HistogramBuild(xsize, histo_bits, refs, orig_histo); 948 // Copies the histograms and computes its bit_cost. 949 HistogramCopyAndAnalyze(orig_histo, image_histo); 950 951 cur_combo = tmp_histos->histograms[1]; // pick up working slot 952 if (entropy_combine) { 953 const int bin_map_size = orig_histo->size; 954 // Reuse histogram_symbols storage. By definition, it's guaranteed to be ok. 955 uint16_t* const bin_map = histogram_symbols; 956 const double combine_cost_factor = 957 GetCombineCostFactor(image_histo_raw_size, quality); 958 959 HistogramAnalyzeEntropyBin(orig_histo, bin_map, low_effort); 960 // Collapse histograms with similar entropy. 961 cur_combo = HistogramCombineEntropyBin(image_histo, cur_combo, 962 bin_map, bin_map_size, 963 entropy_combine_num_bins, 964 combine_cost_factor, low_effort); 965 } 966 967 // Don't combine the histograms using stochastic and greedy heuristics for 968 // low-effort compression mode. 969 if (!low_effort || !entropy_combine) { 970 const float x = quality / 100.f; 971 // cubic ramp between 1 and MAX_HISTO_GREEDY: 972 const int threshold_size = (int)(1 + (x * x * x) * (MAX_HISTO_GREEDY - 1)); 973 HistogramCombineStochastic(image_histo, tmp_histos->histograms[0], 974 cur_combo, quality, threshold_size); 975 if ((image_histo->size <= threshold_size) && 976 !HistogramCombineGreedy(image_histo)) { 977 goto Error; 978 } 979 } 980 981 // TODO(vikasa): Optimize HistogramRemap for low-effort compression mode also. 982 // Find the optimal map from original histograms to the final ones. 983 HistogramRemap(orig_histo, image_histo, histogram_symbols); 984 985 ok = 1; 986 987 Error: 988 VP8LFreeHistogramSet(orig_histo); 989 return ok; 990 } 991
