| // Copyright 2012 Google Inc. All Rights Reserved. |
| // |
| // Use of this source code is governed by a BSD-style license |
| // that can be found in the COPYING file in the root of the source |
| // tree. An additional intellectual property rights grant can be found |
| // in the file PATENTS. All contributing project authors may |
| // be found in the AUTHORS file in the root of the source tree. |
| // ----------------------------------------------------------------------------- |
| // |
| // Author: Jyrki Alakuijala (jyrki@google.com) |
| // |
| #ifdef HAVE_CONFIG_H |
| #include "config.h" |
| #endif |
| |
| #include <math.h> |
| |
| #include "./backward_references.h" |
| #include "./histogram.h" |
| #include "../dsp/lossless.h" |
| #include "../utils/utils.h" |
| |
| #define MAX_COST 1.e38 |
| |
| // Number of partitions for the three dominant (literal, red and blue) symbol |
| // costs. |
| #define NUM_PARTITIONS 4 |
| // The size of the bin-hash corresponding to the three dominant costs. |
| #define BIN_SIZE (NUM_PARTITIONS * NUM_PARTITIONS * NUM_PARTITIONS) |
| |
| static void HistogramClear(VP8LHistogram* const p) { |
| uint32_t* const literal = p->literal_; |
| const int cache_bits = p->palette_code_bits_; |
| const int histo_size = VP8LGetHistogramSize(cache_bits); |
| memset(p, 0, histo_size); |
| p->palette_code_bits_ = cache_bits; |
| p->literal_ = literal; |
| } |
| |
| static void HistogramCopy(const VP8LHistogram* const src, |
| VP8LHistogram* const dst) { |
| uint32_t* const dst_literal = dst->literal_; |
| const int dst_cache_bits = dst->palette_code_bits_; |
| const int histo_size = VP8LGetHistogramSize(dst_cache_bits); |
| assert(src->palette_code_bits_ == dst_cache_bits); |
| memcpy(dst, src, histo_size); |
| dst->literal_ = dst_literal; |
| } |
| |
| int VP8LGetHistogramSize(int cache_bits) { |
| const int literal_size = VP8LHistogramNumCodes(cache_bits); |
| const size_t total_size = sizeof(VP8LHistogram) + sizeof(int) * literal_size; |
| assert(total_size <= (size_t)0x7fffffff); |
| return (int)total_size; |
| } |
| |
| void VP8LFreeHistogram(VP8LHistogram* const histo) { |
| WebPSafeFree(histo); |
| } |
| |
| void VP8LFreeHistogramSet(VP8LHistogramSet* const histo) { |
| WebPSafeFree(histo); |
| } |
| |
| void VP8LHistogramStoreRefs(const VP8LBackwardRefs* const refs, |
| VP8LHistogram* const histo) { |
| VP8LRefsCursor c = VP8LRefsCursorInit(refs); |
| while (VP8LRefsCursorOk(&c)) { |
| VP8LHistogramAddSinglePixOrCopy(histo, c.cur_pos); |
| VP8LRefsCursorNext(&c); |
| } |
| } |
| |
| void VP8LHistogramCreate(VP8LHistogram* const p, |
| const VP8LBackwardRefs* const refs, |
| int palette_code_bits) { |
| if (palette_code_bits >= 0) { |
| p->palette_code_bits_ = palette_code_bits; |
| } |
| HistogramClear(p); |
| VP8LHistogramStoreRefs(refs, p); |
| } |
| |
| void VP8LHistogramInit(VP8LHistogram* const p, int palette_code_bits) { |
| p->palette_code_bits_ = palette_code_bits; |
| HistogramClear(p); |
| } |
| |
| VP8LHistogram* VP8LAllocateHistogram(int cache_bits) { |
| VP8LHistogram* histo = NULL; |
| const int total_size = VP8LGetHistogramSize(cache_bits); |
| uint8_t* const memory = (uint8_t*)WebPSafeMalloc(total_size, sizeof(*memory)); |
| if (memory == NULL) return NULL; |
| histo = (VP8LHistogram*)memory; |
| // literal_ won't necessary be aligned. |
| histo->literal_ = (uint32_t*)(memory + sizeof(VP8LHistogram)); |
| VP8LHistogramInit(histo, cache_bits); |
| return histo; |
| } |
| |
| VP8LHistogramSet* VP8LAllocateHistogramSet(int size, int cache_bits) { |
| int i; |
| VP8LHistogramSet* set; |
| const size_t total_size = sizeof(*set) |
| + sizeof(*set->histograms) * size |
| + (size_t)VP8LGetHistogramSize(cache_bits) * size; |
| uint8_t* memory = (uint8_t*)WebPSafeMalloc(total_size, sizeof(*memory)); |
| if (memory == NULL) return NULL; |
| |
| set = (VP8LHistogramSet*)memory; |
| memory += sizeof(*set); |
| set->histograms = (VP8LHistogram**)memory; |
| memory += size * sizeof(*set->histograms); |
| set->max_size = size; |
| set->size = size; |
| for (i = 0; i < size; ++i) { |
| set->histograms[i] = (VP8LHistogram*)memory; |
| // literal_ won't necessary be aligned. |
| set->histograms[i]->literal_ = (uint32_t*)(memory + sizeof(VP8LHistogram)); |
| VP8LHistogramInit(set->histograms[i], cache_bits); |
| // There's no padding/alignment between successive histograms. |
| memory += VP8LGetHistogramSize(cache_bits); |
| } |
| return set; |
| } |
| |
| // ----------------------------------------------------------------------------- |
| |
| void VP8LHistogramAddSinglePixOrCopy(VP8LHistogram* const histo, |
| const PixOrCopy* const v) { |
| if (PixOrCopyIsLiteral(v)) { |
| ++histo->alpha_[PixOrCopyLiteral(v, 3)]; |
| ++histo->red_[PixOrCopyLiteral(v, 2)]; |
| ++histo->literal_[PixOrCopyLiteral(v, 1)]; |
| ++histo->blue_[PixOrCopyLiteral(v, 0)]; |
| } else if (PixOrCopyIsCacheIdx(v)) { |
| const int literal_ix = |
| NUM_LITERAL_CODES + NUM_LENGTH_CODES + PixOrCopyCacheIdx(v); |
| ++histo->literal_[literal_ix]; |
| } else { |
| int code, extra_bits; |
| VP8LPrefixEncodeBits(PixOrCopyLength(v), &code, &extra_bits); |
| ++histo->literal_[NUM_LITERAL_CODES + code]; |
| VP8LPrefixEncodeBits(PixOrCopyDistance(v), &code, &extra_bits); |
| ++histo->distance_[code]; |
| } |
| } |
| |
| static WEBP_INLINE double BitsEntropyRefine(int nonzeros, int sum, int max_val, |
| double retval) { |
| double mix; |
| if (nonzeros < 5) { |
| if (nonzeros <= 1) { |
| return 0; |
| } |
| // Two symbols, they will be 0 and 1 in a Huffman code. |
| // Let's mix in a bit of entropy to favor good clustering when |
| // distributions of these are combined. |
| if (nonzeros == 2) { |
| return 0.99 * sum + 0.01 * retval; |
| } |
| // No matter what the entropy says, we cannot be better than min_limit |
| // with Huffman coding. I am mixing a bit of entropy into the |
| // min_limit since it produces much better (~0.5 %) compression results |
| // perhaps because of better entropy clustering. |
| if (nonzeros == 3) { |
| mix = 0.95; |
| } else { |
| mix = 0.7; // nonzeros == 4. |
| } |
| } else { |
| mix = 0.627; |
| } |
| |
| { |
| double min_limit = 2 * sum - max_val; |
| min_limit = mix * min_limit + (1.0 - mix) * retval; |
| return (retval < min_limit) ? min_limit : retval; |
| } |
| } |
| |
| static double BitsEntropy(const uint32_t* const array, int n) { |
| double retval = 0.; |
| uint32_t sum = 0; |
| int nonzeros = 0; |
| uint32_t max_val = 0; |
| int i; |
| for (i = 0; i < n; ++i) { |
| if (array[i] != 0) { |
| sum += array[i]; |
| ++nonzeros; |
| retval -= VP8LFastSLog2(array[i]); |
| if (max_val < array[i]) { |
| max_val = array[i]; |
| } |
| } |
| } |
| retval += VP8LFastSLog2(sum); |
| return BitsEntropyRefine(nonzeros, sum, max_val, retval); |
| } |
| |
| static double BitsEntropyCombined(const uint32_t* const X, |
| const uint32_t* const Y, int n) { |
| double retval = 0.; |
| int sum = 0; |
| int nonzeros = 0; |
| int max_val = 0; |
| int i; |
| for (i = 0; i < n; ++i) { |
| const int xy = X[i] + Y[i]; |
| if (xy != 0) { |
| sum += xy; |
| ++nonzeros; |
| retval -= VP8LFastSLog2(xy); |
| if (max_val < xy) { |
| max_val = xy; |
| } |
| } |
| } |
| retval += VP8LFastSLog2(sum); |
| return BitsEntropyRefine(nonzeros, sum, max_val, retval); |
| } |
| |
| static double InitialHuffmanCost(void) { |
| // Small bias because Huffman code length is typically not stored in |
| // full length. |
| static const int kHuffmanCodeOfHuffmanCodeSize = CODE_LENGTH_CODES * 3; |
| static const double kSmallBias = 9.1; |
| return kHuffmanCodeOfHuffmanCodeSize - kSmallBias; |
| } |
| |
| // Finalize the Huffman cost based on streak numbers and length type (<3 or >=3) |
| static double FinalHuffmanCost(const VP8LStreaks* const stats) { |
| double retval = InitialHuffmanCost(); |
| retval += stats->counts[0] * 1.5625 + 0.234375 * stats->streaks[0][1]; |
| retval += stats->counts[1] * 2.578125 + 0.703125 * stats->streaks[1][1]; |
| retval += 1.796875 * stats->streaks[0][0]; |
| retval += 3.28125 * stats->streaks[1][0]; |
| return retval; |
| } |
| |
| // Trampolines |
| static double HuffmanCost(const uint32_t* const population, int length) { |
| const VP8LStreaks stats = VP8LHuffmanCostCount(population, length); |
| return FinalHuffmanCost(&stats); |
| } |
| |
| static double HuffmanCostCombined(const uint32_t* const X, |
| const uint32_t* const Y, int length) { |
| const VP8LStreaks stats = VP8LHuffmanCostCombinedCount(X, Y, length); |
| return FinalHuffmanCost(&stats); |
| } |
| |
| // Aggregated costs |
| static double PopulationCost(const uint32_t* const population, int length) { |
| return BitsEntropy(population, length) + HuffmanCost(population, length); |
| } |
| |
| static double GetCombinedEntropy(const uint32_t* const X, |
| const uint32_t* const Y, int length) { |
| return BitsEntropyCombined(X, Y, length) + HuffmanCostCombined(X, Y, length); |
| } |
| |
| // Estimates the Entropy + Huffman + other block overhead size cost. |
| double VP8LHistogramEstimateBits(const VP8LHistogram* const p) { |
| return |
| PopulationCost(p->literal_, VP8LHistogramNumCodes(p->palette_code_bits_)) |
| + PopulationCost(p->red_, NUM_LITERAL_CODES) |
| + PopulationCost(p->blue_, NUM_LITERAL_CODES) |
| + PopulationCost(p->alpha_, NUM_LITERAL_CODES) |
| + PopulationCost(p->distance_, NUM_DISTANCE_CODES) |
| + VP8LExtraCost(p->literal_ + NUM_LITERAL_CODES, NUM_LENGTH_CODES) |
| + VP8LExtraCost(p->distance_, NUM_DISTANCE_CODES); |
| } |
| |
| double VP8LHistogramEstimateBitsBulk(const VP8LHistogram* const p) { |
| return |
| BitsEntropy(p->literal_, VP8LHistogramNumCodes(p->palette_code_bits_)) |
| + BitsEntropy(p->red_, NUM_LITERAL_CODES) |
| + BitsEntropy(p->blue_, NUM_LITERAL_CODES) |
| + BitsEntropy(p->alpha_, NUM_LITERAL_CODES) |
| + BitsEntropy(p->distance_, NUM_DISTANCE_CODES) |
| + VP8LExtraCost(p->literal_ + NUM_LITERAL_CODES, NUM_LENGTH_CODES) |
| + VP8LExtraCost(p->distance_, NUM_DISTANCE_CODES); |
| } |
| |
| // ----------------------------------------------------------------------------- |
| // Various histogram combine/cost-eval functions |
| |
| static int GetCombinedHistogramEntropy(const VP8LHistogram* const a, |
| const VP8LHistogram* const b, |
| double cost_threshold, |
| double* cost) { |
| const int palette_code_bits = a->palette_code_bits_; |
| assert(a->palette_code_bits_ == b->palette_code_bits_); |
| *cost += GetCombinedEntropy(a->literal_, b->literal_, |
| VP8LHistogramNumCodes(palette_code_bits)); |
| *cost += VP8LExtraCostCombined(a->literal_ + NUM_LITERAL_CODES, |
| b->literal_ + NUM_LITERAL_CODES, |
| NUM_LENGTH_CODES); |
| if (*cost > cost_threshold) return 0; |
| |
| *cost += GetCombinedEntropy(a->red_, b->red_, NUM_LITERAL_CODES); |
| if (*cost > cost_threshold) return 0; |
| |
| *cost += GetCombinedEntropy(a->blue_, b->blue_, NUM_LITERAL_CODES); |
| if (*cost > cost_threshold) return 0; |
| |
| *cost += GetCombinedEntropy(a->alpha_, b->alpha_, NUM_LITERAL_CODES); |
| if (*cost > cost_threshold) return 0; |
| |
| *cost += GetCombinedEntropy(a->distance_, b->distance_, NUM_DISTANCE_CODES); |
| *cost += VP8LExtraCostCombined(a->distance_, b->distance_, |
| NUM_DISTANCE_CODES); |
| if (*cost > cost_threshold) return 0; |
| |
| return 1; |
| } |
| |
| // Performs out = a + b, computing the cost C(a+b) - C(a) - C(b) while comparing |
| // to the threshold value 'cost_threshold'. The score returned is |
| // Score = C(a+b) - C(a) - C(b), where C(a) + C(b) is known and fixed. |
| // Since the previous score passed is 'cost_threshold', we only need to compare |
| // the partial cost against 'cost_threshold + C(a) + C(b)' to possibly bail-out |
| // early. |
| static double HistogramAddEval(const VP8LHistogram* const a, |
| const VP8LHistogram* const b, |
| VP8LHistogram* const out, |
| double cost_threshold) { |
| double cost = 0; |
| const double sum_cost = a->bit_cost_ + b->bit_cost_; |
| cost_threshold += sum_cost; |
| |
| if (GetCombinedHistogramEntropy(a, b, cost_threshold, &cost)) { |
| VP8LHistogramAdd(a, b, out); |
| out->bit_cost_ = cost; |
| out->palette_code_bits_ = a->palette_code_bits_; |
| } |
| |
| return cost - sum_cost; |
| } |
| |
| // Same as HistogramAddEval(), except that the resulting histogram |
| // is not stored. Only the cost C(a+b) - C(a) is evaluated. We omit |
| // the term C(b) which is constant over all the evaluations. |
| static double HistogramAddThresh(const VP8LHistogram* const a, |
| const VP8LHistogram* const b, |
| double cost_threshold) { |
| double cost = -a->bit_cost_; |
| GetCombinedHistogramEntropy(a, b, cost_threshold, &cost); |
| return cost; |
| } |
| |
| // ----------------------------------------------------------------------------- |
| |
| // The structure to keep track of cost range for the three dominant entropy |
| // symbols. |
| // TODO(skal): Evaluate if float can be used here instead of double for |
| // representing the entropy costs. |
| typedef struct { |
| double literal_max_; |
| double literal_min_; |
| double red_max_; |
| double red_min_; |
| double blue_max_; |
| double blue_min_; |
| } DominantCostRange; |
| |
| static void DominantCostRangeInit(DominantCostRange* const c) { |
| c->literal_max_ = 0.; |
| c->literal_min_ = MAX_COST; |
| c->red_max_ = 0.; |
| c->red_min_ = MAX_COST; |
| c->blue_max_ = 0.; |
| c->blue_min_ = MAX_COST; |
| } |
| |
| static void UpdateDominantCostRange( |
| const VP8LHistogram* const h, DominantCostRange* const c) { |
| if (c->literal_max_ < h->literal_cost_) c->literal_max_ = h->literal_cost_; |
| if (c->literal_min_ > h->literal_cost_) c->literal_min_ = h->literal_cost_; |
| if (c->red_max_ < h->red_cost_) c->red_max_ = h->red_cost_; |
| if (c->red_min_ > h->red_cost_) c->red_min_ = h->red_cost_; |
| if (c->blue_max_ < h->blue_cost_) c->blue_max_ = h->blue_cost_; |
| if (c->blue_min_ > h->blue_cost_) c->blue_min_ = h->blue_cost_; |
| } |
| |
| static void UpdateHistogramCost(VP8LHistogram* const h) { |
| const double alpha_cost = PopulationCost(h->alpha_, NUM_LITERAL_CODES); |
| const double distance_cost = |
| PopulationCost(h->distance_, NUM_DISTANCE_CODES) + |
| VP8LExtraCost(h->distance_, NUM_DISTANCE_CODES); |
| const int num_codes = VP8LHistogramNumCodes(h->palette_code_bits_); |
| h->literal_cost_ = PopulationCost(h->literal_, num_codes) + |
| VP8LExtraCost(h->literal_ + NUM_LITERAL_CODES, |
| NUM_LENGTH_CODES); |
| h->red_cost_ = PopulationCost(h->red_, NUM_LITERAL_CODES); |
| h->blue_cost_ = PopulationCost(h->blue_, NUM_LITERAL_CODES); |
| h->bit_cost_ = h->literal_cost_ + h->red_cost_ + h->blue_cost_ + |
| alpha_cost + distance_cost; |
| } |
| |
| static int GetBinIdForEntropy(double min, double max, double val) { |
| const double range = max - min + 1e-6; |
| const double delta = val - min; |
| return (int)(NUM_PARTITIONS * delta / range); |
| } |
| |
| // TODO(vikasa): Evaluate, if there's any correlation between red & blue. |
| static int GetHistoBinIndex( |
| const VP8LHistogram* const h, const DominantCostRange* const c) { |
| const int bin_id = |
| GetBinIdForEntropy(c->blue_min_, c->blue_max_, h->blue_cost_) + |
| NUM_PARTITIONS * GetBinIdForEntropy(c->red_min_, c->red_max_, |
| h->red_cost_) + |
| NUM_PARTITIONS * NUM_PARTITIONS * GetBinIdForEntropy(c->literal_min_, |
| c->literal_max_, |
| h->literal_cost_); |
| assert(bin_id < BIN_SIZE); |
| return bin_id; |
| } |
| |
| // Construct the histograms from backward references. |
| static void HistogramBuild( |
| int xsize, int histo_bits, const VP8LBackwardRefs* const backward_refs, |
| VP8LHistogramSet* const image_histo) { |
| int x = 0, y = 0; |
| const int histo_xsize = VP8LSubSampleSize(xsize, histo_bits); |
| VP8LHistogram** const histograms = image_histo->histograms; |
| VP8LRefsCursor c = VP8LRefsCursorInit(backward_refs); |
| assert(histo_bits > 0); |
| // Construct the Histo from a given backward references. |
| while (VP8LRefsCursorOk(&c)) { |
| const PixOrCopy* const v = c.cur_pos; |
| const int ix = (y >> histo_bits) * histo_xsize + (x >> histo_bits); |
| VP8LHistogramAddSinglePixOrCopy(histograms[ix], v); |
| x += PixOrCopyLength(v); |
| while (x >= xsize) { |
| x -= xsize; |
| ++y; |
| } |
| VP8LRefsCursorNext(&c); |
| } |
| } |
| |
| // Copies the histograms and computes its bit_cost. |
| static void HistogramCopyAndAnalyze( |
| VP8LHistogramSet* const orig_histo, VP8LHistogramSet* const image_histo) { |
| int i; |
| const int histo_size = orig_histo->size; |
| VP8LHistogram** const orig_histograms = orig_histo->histograms; |
| VP8LHistogram** const histograms = image_histo->histograms; |
| for (i = 0; i < histo_size; ++i) { |
| VP8LHistogram* const histo = orig_histograms[i]; |
| UpdateHistogramCost(histo); |
| // Copy histograms from orig_histo[] to image_histo[]. |
| HistogramCopy(histo, histograms[i]); |
| } |
| } |
| |
| // Partition histograms to different entropy bins for three dominant (literal, |
| // red and blue) symbol costs and compute the histogram aggregate bit_cost. |
| static void HistogramAnalyzeEntropyBin( |
| VP8LHistogramSet* const image_histo, int16_t* const bin_map) { |
| int i; |
| VP8LHistogram** const histograms = image_histo->histograms; |
| const int histo_size = image_histo->size; |
| const int bin_depth = histo_size + 1; |
| DominantCostRange cost_range; |
| DominantCostRangeInit(&cost_range); |
| |
| // Analyze the dominant (literal, red and blue) entropy costs. |
| for (i = 0; i < histo_size; ++i) { |
| VP8LHistogram* const histo = histograms[i]; |
| UpdateDominantCostRange(histo, &cost_range); |
| } |
| |
| // bin-hash histograms on three of the dominant (literal, red and blue) |
| // symbol costs. |
| for (i = 0; i < histo_size; ++i) { |
| int num_histos; |
| VP8LHistogram* const histo = histograms[i]; |
| const int16_t bin_id = (int16_t)GetHistoBinIndex(histo, &cost_range); |
| const int bin_offset = bin_id * bin_depth; |
| // bin_map[n][0] for every bin 'n' maintains the counter for the number of |
| // histograms in that bin. |
| // Get and increment the num_histos in that bin. |
| num_histos = ++bin_map[bin_offset]; |
| assert(bin_offset + num_histos < bin_depth * BIN_SIZE); |
| // Add histogram i'th index at num_histos (last) position in the bin_map. |
| bin_map[bin_offset + num_histos] = i; |
| } |
| } |
| |
| // Compact the histogram set by moving the valid one left in the set to the |
| // head and moving the ones that have been merged to other histograms towards |
| // the end. |
| // TODO(vikasa): Evaluate if this method can be avoided by altering the code |
| // logic of HistogramCombineEntropyBin main loop. |
| static void HistogramCompactBins(VP8LHistogramSet* const image_histo) { |
| int start = 0; |
| int end = image_histo->size - 1; |
| VP8LHistogram** const histograms = image_histo->histograms; |
| while (start < end) { |
| while (start <= end && histograms[start] != NULL && |
| histograms[start]->bit_cost_ != 0.) { |
| ++start; |
| } |
| while (start <= end && histograms[end]->bit_cost_ == 0.) { |
| histograms[end] = NULL; |
| --end; |
| } |
| if (start < end) { |
| assert(histograms[start] != NULL); |
| assert(histograms[end] != NULL); |
| HistogramCopy(histograms[end], histograms[start]); |
| histograms[end] = NULL; |
| --end; |
| } |
| } |
| image_histo->size = end + 1; |
| } |
| |
| static void HistogramCombineEntropyBin(VP8LHistogramSet* const image_histo, |
| VP8LHistogram* const histos, |
| int16_t* const bin_map, int bin_depth, |
| double combine_cost_factor) { |
| int bin_id; |
| VP8LHistogram* cur_combo = histos; |
| VP8LHistogram** const histograms = image_histo->histograms; |
| |
| for (bin_id = 0; bin_id < BIN_SIZE; ++bin_id) { |
| const int bin_offset = bin_id * bin_depth; |
| const int num_histos = bin_map[bin_offset]; |
| const int idx1 = bin_map[bin_offset + 1]; |
| int n; |
| for (n = 2; n <= num_histos; ++n) { |
| const int idx2 = bin_map[bin_offset + n]; |
| const double bit_cost_idx2 = histograms[idx2]->bit_cost_; |
| if (bit_cost_idx2 > 0.) { |
| const double bit_cost_thresh = -bit_cost_idx2 * combine_cost_factor; |
| const double curr_cost_diff = |
| HistogramAddEval(histograms[idx1], histograms[idx2], |
| cur_combo, bit_cost_thresh); |
| if (curr_cost_diff < bit_cost_thresh) { |
| HistogramCopy(cur_combo, histograms[idx1]); |
| histograms[idx2]->bit_cost_ = 0.; |
| } |
| } |
| } |
| } |
| HistogramCompactBins(image_histo); |
| } |
| |
| static uint32_t MyRand(uint32_t *seed) { |
| *seed *= 16807U; |
| if (*seed == 0) { |
| *seed = 1; |
| } |
| return *seed; |
| } |
| |
| static void HistogramCombine(VP8LHistogramSet* const image_histo, |
| VP8LHistogramSet* const histos, int quality) { |
| int iter; |
| uint32_t seed = 0; |
| int tries_with_no_success = 0; |
| int image_histo_size = image_histo->size; |
| const int iter_mult = (quality < 25) ? 2 : 2 + (quality - 25) / 8; |
| const int outer_iters = image_histo_size * iter_mult; |
| const int num_pairs = image_histo_size / 2; |
| const int num_tries_no_success = outer_iters / 2; |
| const int min_cluster_size = 2; |
| VP8LHistogram** const histograms = image_histo->histograms; |
| VP8LHistogram* cur_combo = histos->histograms[0]; // trial histogram |
| VP8LHistogram* best_combo = histos->histograms[1]; // best histogram so far |
| |
| // Collapse similar histograms in 'image_histo'. |
| for (iter = 0; |
| iter < outer_iters && image_histo_size >= min_cluster_size; |
| ++iter) { |
| double best_cost_diff = 0.; |
| int best_idx1 = -1, best_idx2 = 1; |
| int j; |
| const int num_tries = |
| (num_pairs < image_histo_size) ? num_pairs : image_histo_size; |
| seed += iter; |
| for (j = 0; j < num_tries; ++j) { |
| double curr_cost_diff; |
| // Choose two histograms at random and try to combine them. |
| const uint32_t idx1 = MyRand(&seed) % image_histo_size; |
| const uint32_t tmp = (j & 7) + 1; |
| const uint32_t diff = |
| (tmp < 3) ? tmp : MyRand(&seed) % (image_histo_size - 1); |
| const uint32_t idx2 = (idx1 + diff + 1) % image_histo_size; |
| if (idx1 == idx2) { |
| continue; |
| } |
| |
| // Calculate cost reduction on combining. |
| curr_cost_diff = HistogramAddEval(histograms[idx1], histograms[idx2], |
| cur_combo, best_cost_diff); |
| if (curr_cost_diff < best_cost_diff) { // found a better pair? |
| { // swap cur/best combo histograms |
| VP8LHistogram* const tmp_histo = cur_combo; |
| cur_combo = best_combo; |
| best_combo = tmp_histo; |
| } |
| best_cost_diff = curr_cost_diff; |
| best_idx1 = idx1; |
| best_idx2 = idx2; |
| } |
| } |
| |
| if (best_idx1 >= 0) { |
| HistogramCopy(best_combo, histograms[best_idx1]); |
| // swap best_idx2 slot with last one (which is now unused) |
| --image_histo_size; |
| if (best_idx2 != image_histo_size) { |
| HistogramCopy(histograms[image_histo_size], histograms[best_idx2]); |
| histograms[image_histo_size] = NULL; |
| } |
| tries_with_no_success = 0; |
| } |
| if (++tries_with_no_success >= num_tries_no_success) { |
| break; |
| } |
| } |
| image_histo->size = image_histo_size; |
| } |
| |
| // ----------------------------------------------------------------------------- |
| // Histogram refinement |
| |
| // Find the best 'out' histogram for each of the 'in' histograms. |
| // Note: we assume that out[]->bit_cost_ is already up-to-date. |
| static void HistogramRemap(const VP8LHistogramSet* const orig_histo, |
| const VP8LHistogramSet* const image_histo, |
| uint16_t* const symbols) { |
| int i; |
| VP8LHistogram** const orig_histograms = orig_histo->histograms; |
| VP8LHistogram** const histograms = image_histo->histograms; |
| for (i = 0; i < orig_histo->size; ++i) { |
| int best_out = 0; |
| double best_bits = |
| HistogramAddThresh(histograms[0], orig_histograms[i], MAX_COST); |
| int k; |
| for (k = 1; k < image_histo->size; ++k) { |
| const double cur_bits = |
| HistogramAddThresh(histograms[k], orig_histograms[i], best_bits); |
| if (cur_bits < best_bits) { |
| best_bits = cur_bits; |
| best_out = k; |
| } |
| } |
| symbols[i] = best_out; |
| } |
| |
| // Recompute each out based on raw and symbols. |
| for (i = 0; i < image_histo->size; ++i) { |
| HistogramClear(histograms[i]); |
| } |
| |
| for (i = 0; i < orig_histo->size; ++i) { |
| const int idx = symbols[i]; |
| VP8LHistogramAdd(orig_histograms[i], histograms[idx], histograms[idx]); |
| } |
| } |
| |
| static double GetCombineCostFactor(int histo_size, int quality) { |
| double combine_cost_factor = 0.16; |
| if (histo_size > 256) combine_cost_factor /= 2.; |
| if (histo_size > 512) combine_cost_factor /= 2.; |
| if (histo_size > 1024) combine_cost_factor /= 2.; |
| if (quality <= 50) combine_cost_factor /= 2.; |
| return combine_cost_factor; |
| } |
| |
| int VP8LGetHistoImageSymbols(int xsize, int ysize, |
| const VP8LBackwardRefs* const refs, |
| int quality, int histo_bits, int cache_bits, |
| VP8LHistogramSet* const image_histo, |
| uint16_t* const histogram_symbols) { |
| int ok = 0; |
| const int histo_xsize = histo_bits ? VP8LSubSampleSize(xsize, histo_bits) : 1; |
| const int histo_ysize = histo_bits ? VP8LSubSampleSize(ysize, histo_bits) : 1; |
| const int image_histo_raw_size = histo_xsize * histo_ysize; |
| |
| // The bin_map for every bin follows following semantics: |
| // bin_map[n][0] = num_histo; // The number of histograms in that bin. |
| // bin_map[n][1] = index of first histogram in that bin; |
| // bin_map[n][num_histo] = index of last histogram in that bin; |
| // bin_map[n][num_histo + 1] ... bin_map[n][bin_depth - 1] = un-used indices. |
| const int bin_depth = image_histo_raw_size + 1; |
| int16_t* bin_map = NULL; |
| VP8LHistogramSet* const histos = VP8LAllocateHistogramSet(2, cache_bits); |
| VP8LHistogramSet* const orig_histo = |
| VP8LAllocateHistogramSet(image_histo_raw_size, cache_bits); |
| |
| if (orig_histo == NULL || histos == NULL) { |
| goto Error; |
| } |
| |
| // Don't attempt linear bin-partition heuristic for: |
| // histograms of small sizes, as bin_map will be very sparse and; |
| // Higher qualities (> 90), to preserve the compression gains at those |
| // quality settings. |
| if (orig_histo->size > 2 * BIN_SIZE && quality < 90) { |
| const int bin_map_size = bin_depth * BIN_SIZE; |
| bin_map = (int16_t*)WebPSafeCalloc(bin_map_size, sizeof(*bin_map)); |
| if (bin_map == NULL) goto Error; |
| } |
| |
| // Construct the histograms from backward references. |
| HistogramBuild(xsize, histo_bits, refs, orig_histo); |
| // Copies the histograms and computes its bit_cost. |
| HistogramCopyAndAnalyze(orig_histo, image_histo); |
| |
| if (bin_map != NULL) { |
| const double combine_cost_factor = |
| GetCombineCostFactor(image_histo_raw_size, quality); |
| HistogramAnalyzeEntropyBin(orig_histo, bin_map); |
| // Collapse histograms with similar entropy. |
| HistogramCombineEntropyBin(image_histo, histos->histograms[0], |
| bin_map, bin_depth, combine_cost_factor); |
| } |
| |
| // Collapse similar histograms by random histogram-pair compares. |
| HistogramCombine(image_histo, histos, quality); |
| |
| // Find the optimal map from original histograms to the final ones. |
| HistogramRemap(orig_histo, image_histo, histogram_symbols); |
| |
| ok = 1; |
| |
| Error: |
| WebPSafeFree(bin_map); |
| VP8LFreeHistogramSet(orig_histo); |
| VP8LFreeHistogramSet(histos); |
| return ok; |
| } |
