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Diffstat (limited to 'src/main/jni/libwebp/enc/histogram.c')
| -rw-r--r-- | src/main/jni/libwebp/enc/histogram.c | 741 |
1 files changed, 741 insertions, 0 deletions
diff --git a/src/main/jni/libwebp/enc/histogram.c b/src/main/jni/libwebp/enc/histogram.c new file mode 100644 index 000000000..7c6abb4d6 --- /dev/null +++ b/src/main/jni/libwebp/enc/histogram.c @@ -0,0 +1,741 @@ +// 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 "../webp/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; +} |