| // 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 "third_party/chromium_headless/libwebp/enc/backward_references.h" |
| #include "third_party/chromium_headless/libwebp/enc/histogram.h" |
| #include "third_party/chromium_headless/libwebp/dsp/lossless.h" |
| #include "third_party/chromium_headless/libwebp/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) |
| // Maximum number of histograms allowed in greedy combining algorithm. |
| #define MAX_HISTO_GREEDY 100 |
| |
| 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; |
| } |
| |
| // Swap two histogram pointers. |
| static void HistogramSwap(VP8LHistogram** const A, VP8LHistogram** const B) { |
| VP8LHistogram* const tmp = *A; |
| *A = *B; |
| *B = tmp; |
| } |
| |
| 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 int histo_size = VP8LGetHistogramSize(cache_bits); |
| const size_t total_size = |
| sizeof(*set) + size * (sizeof(*set->histograms) + |
| histo_size + WEBP_ALIGN_CST); |
| 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) { |
| memory = (uint8_t*)WEBP_ALIGN(memory); |
| 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); |
| memory += histo_size; |
| } |
| 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]; |
| } |
| } |
| |
| // ----------------------------------------------------------------------------- |
| // Entropy-related functions. |
| |
| static WEBP_INLINE double BitsEntropyRefine(const VP8LBitEntropy* entropy) { |
| double mix; |
| if (entropy->nonzeros < 5) { |
| if (entropy->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 (entropy->nonzeros == 2) { |
| return 0.99 * entropy->sum + 0.01 * entropy->entropy; |
| } |
| // 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 (entropy->nonzeros == 3) { |
| mix = 0.95; |
| } else { |
| mix = 0.7; // nonzeros == 4. |
| } |
| } else { |
| mix = 0.627; |
| } |
| |
| { |
| double min_limit = 2 * entropy->sum - entropy->max_val; |
| min_limit = mix * min_limit + (1.0 - mix) * entropy->entropy; |
| return (entropy->entropy < min_limit) ? min_limit : entropy->entropy; |
| } |
| } |
| |
| double VP8LBitsEntropy(const uint32_t* const array, int n, |
| uint32_t* const trivial_symbol) { |
| VP8LBitEntropy entropy; |
| VP8LBitsEntropyUnrefined(array, n, &entropy); |
| if (trivial_symbol != NULL) { |
| *trivial_symbol = |
| (entropy.nonzeros == 1) ? entropy.nonzero_code : VP8L_NON_TRIVIAL_SYM; |
| } |
| |
| return BitsEntropyRefine(&entropy); |
| } |
| |
| 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; |
| } |
| |
| // Get the symbol entropy for the distribution 'population'. |
| // Set 'trivial_sym', if there's only one symbol present in the distribution. |
| static double PopulationCost(const uint32_t* const population, int length, |
| uint32_t* const trivial_sym) { |
| VP8LBitEntropy bit_entropy; |
| VP8LStreaks stats; |
| VP8LGetEntropyUnrefined(population, length, &bit_entropy, &stats); |
| if (trivial_sym != NULL) { |
| *trivial_sym = (bit_entropy.nonzeros == 1) ? bit_entropy.nonzero_code |
| : VP8L_NON_TRIVIAL_SYM; |
| } |
| |
| return BitsEntropyRefine(&bit_entropy) + FinalHuffmanCost(&stats); |
| } |
| |
| static WEBP_INLINE double GetCombinedEntropy(const uint32_t* const X, |
| const uint32_t* const Y, |
| int length) { |
| VP8LBitEntropy bit_entropy; |
| VP8LStreaks stats; |
| VP8LGetCombinedEntropyUnrefined(X, Y, length, &bit_entropy, &stats); |
| |
| return BitsEntropyRefine(&bit_entropy) + FinalHuffmanCost(&stats); |
| } |
| |
| // Estimates the Entropy + Huffman + other block overhead size cost. |
| double VP8LHistogramEstimateBits(const VP8LHistogram* const p) { |
| return |
| PopulationCost( |
| p->literal_, VP8LHistogramNumCodes(p->palette_code_bits_), NULL) |
| + PopulationCost(p->red_, NUM_LITERAL_CODES, NULL) |
| + PopulationCost(p->blue_, NUM_LITERAL_CODES, NULL) |
| + PopulationCost(p->alpha_, NUM_LITERAL_CODES, NULL) |
| + PopulationCost(p->distance_, NUM_DISTANCE_CODES, NULL) |
| + 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_; |
| out->trivial_symbol_ = (a->trivial_symbol_ == b->trivial_symbol_) ? |
| a->trivial_symbol_ : VP8L_NON_TRIVIAL_SYM; |
| } |
| |
| 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) { |
| uint32_t alpha_sym, red_sym, blue_sym; |
| const double alpha_cost = |
| PopulationCost(h->alpha_, NUM_LITERAL_CODES, &alpha_sym); |
| const double distance_cost = |
| PopulationCost(h->distance_, NUM_DISTANCE_CODES, NULL) + |
| VP8LExtraCost(h->distance_, NUM_DISTANCE_CODES); |
| const int num_codes = VP8LHistogramNumCodes(h->palette_code_bits_); |
| h->literal_cost_ = PopulationCost(h->literal_, num_codes, NULL) + |
| VP8LExtraCost(h->literal_ + NUM_LITERAL_CODES, |
| NUM_LENGTH_CODES); |
| h->red_cost_ = PopulationCost(h->red_, NUM_LITERAL_CODES, &red_sym); |
| h->blue_cost_ = PopulationCost(h->blue_, NUM_LITERAL_CODES, &blue_sym); |
| h->bit_cost_ = h->literal_cost_ + h->red_cost_ + h->blue_cost_ + |
| alpha_cost + distance_cost; |
| if ((alpha_sym | red_sym | blue_sym) == VP8L_NON_TRIVIAL_SYM) { |
| h->trivial_symbol_ = VP8L_NON_TRIVIAL_SYM; |
| } else { |
| h->trivial_symbol_ = |
| ((uint32_t)alpha_sym << 24) | (red_sym << 16) | (blue_sym << 0); |
| } |
| } |
| |
| static int GetBinIdForEntropy(double min, double max, double val) { |
| const double range = max - min; |
| if (range > 0.) { |
| const double delta = val - min; |
| return (int)((NUM_PARTITIONS - 1e-6) * delta / range); |
| } else { |
| return 0; |
| } |
| } |
| |
| static int GetHistoBinIndex(const VP8LHistogram* const h, |
| const DominantCostRange* const c, int low_effort) { |
| int bin_id = GetBinIdForEntropy(c->literal_min_, c->literal_max_, |
| h->literal_cost_); |
| assert(bin_id < NUM_PARTITIONS); |
| if (!low_effort) { |
| bin_id = bin_id * NUM_PARTITIONS |
| + GetBinIdForEntropy(c->red_min_, c->red_max_, h->red_cost_); |
| bin_id = bin_id * NUM_PARTITIONS |
| + GetBinIdForEntropy(c->blue_min_, c->blue_max_, h->blue_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); |
| 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 low_effort) { |
| 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) { |
| const VP8LHistogram* const histo = histograms[i]; |
| const int bin_id = GetHistoBinIndex(histo, &cost_range, low_effort); |
| 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. |
| const int 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 removing unused entries. |
| static void HistogramCompactBins(VP8LHistogramSet* const image_histo) { |
| VP8LHistogram** const histograms = image_histo->histograms; |
| int i, j; |
| |
| for (i = 0, j = 0; i < image_histo->size; ++i) { |
| if (histograms[i] != NULL && histograms[i]->bit_cost_ != 0.) { |
| if (j < i) { |
| histograms[j] = histograms[i]; |
| histograms[i] = NULL; |
| } |
| ++j; |
| } |
| } |
| image_histo->size = j; |
| } |
| |
| static VP8LHistogram* HistogramCombineEntropyBin( |
| VP8LHistogramSet* const image_histo, |
| VP8LHistogram* cur_combo, |
| int16_t* const bin_map, int bin_depth, int num_bins, |
| double combine_cost_factor, int low_effort) { |
| int bin_id; |
| VP8LHistogram** const histograms = image_histo->histograms; |
| |
| for (bin_id = 0; bin_id < num_bins; ++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 num_combine_failures = 0; |
| int n; |
| for (n = 2; n <= num_histos; ++n) { |
| const int idx2 = bin_map[bin_offset + n]; |
| if (low_effort) { |
| // Merge all histograms with the same bin index, irrespective of cost of |
| // the merged histograms. |
| VP8LHistogramAdd(histograms[idx1], histograms[idx2], histograms[idx1]); |
| histograms[idx2]->bit_cost_ = 0.; |
| } else { |
| 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) { |
| // Try to merge two histograms only if the combo is a trivial one or |
| // the two candidate histograms are already non-trivial. |
| // For some images, 'try_combine' turns out to be false for a lot of |
| // histogram pairs. In that case, we fallback to combining |
| // histograms as usual to avoid increasing the header size. |
| const int try_combine = |
| (cur_combo->trivial_symbol_ != VP8L_NON_TRIVIAL_SYM) || |
| ((histograms[idx1]->trivial_symbol_ == VP8L_NON_TRIVIAL_SYM) && |
| (histograms[idx2]->trivial_symbol_ == VP8L_NON_TRIVIAL_SYM)); |
| const int max_combine_failures = 32; |
| if (try_combine || (num_combine_failures >= max_combine_failures)) { |
| HistogramSwap(&cur_combo, &histograms[idx1]); |
| histograms[idx2]->bit_cost_ = 0.; |
| } else { |
| ++num_combine_failures; |
| } |
| } |
| } |
| } |
| } |
| if (low_effort) { |
| // Update the bit_cost for the merged histograms (per bin index). |
| UpdateHistogramCost(histograms[idx1]); |
| } |
| } |
| HistogramCompactBins(image_histo); |
| return cur_combo; |
| } |
| |
| static uint32_t MyRand(uint32_t *seed) { |
| *seed *= 16807U; |
| if (*seed == 0) { |
| *seed = 1; |
| } |
| return *seed; |
| } |
| |
| // ----------------------------------------------------------------------------- |
| // Histogram pairs priority queue |
| |
| // Pair of histograms. Negative idx1 value means that pair is out-of-date. |
| typedef struct { |
| int idx1; |
| int idx2; |
| double cost_diff; |
| double cost_combo; |
| } HistogramPair; |
| |
| typedef struct { |
| HistogramPair* queue; |
| int size; |
| int max_size; |
| } HistoQueue; |
| |
| static int HistoQueueInit(HistoQueue* const histo_queue, const int max_index) { |
| histo_queue->size = 0; |
| // max_index^2 for the queue size is safe. If you look at |
| // HistogramCombineGreedy, and imagine that UpdateQueueFront always pushes |
| // data to the queue, you insert at most: |
| // - max_index*(max_index-1)/2 (the first two for loops) |
| // - max_index - 1 in the last for loop at the first iteration of the while |
| // loop, max_index - 2 at the second iteration ... therefore |
| // max_index*(max_index-1)/2 overall too |
| histo_queue->max_size = max_index * max_index; |
| // We allocate max_size + 1 because the last element at index "size" is |
| // used as temporary data (and it could be up to max_size). |
| histo_queue->queue = WebPSafeMalloc(histo_queue->max_size + 1, |
| sizeof(*histo_queue->queue)); |
| return histo_queue->queue != NULL; |
| } |
| |
| static void HistoQueueClear(HistoQueue* const histo_queue) { |
| assert(histo_queue != NULL); |
| WebPSafeFree(histo_queue->queue); |
| } |
| |
| static void SwapHistogramPairs(HistogramPair *p1, |
| HistogramPair *p2) { |
| const HistogramPair tmp = *p1; |
| *p1 = *p2; |
| *p2 = tmp; |
| } |
| |
| // Given a valid priority queue in range [0, queue_size) this function checks |
| // whether histo_queue[queue_size] should be accepted and swaps it with the |
| // front if it is smaller. Otherwise, it leaves it as is. |
| static void UpdateQueueFront(HistoQueue* const histo_queue) { |
| if (histo_queue->queue[histo_queue->size].cost_diff >= 0) return; |
| |
| if (histo_queue->queue[histo_queue->size].cost_diff < |
| histo_queue->queue[0].cost_diff) { |
| SwapHistogramPairs(histo_queue->queue, |
| histo_queue->queue + histo_queue->size); |
| } |
| ++histo_queue->size; |
| |
| // We cannot add more elements than the capacity. |
| // The allocation adds an extra element to the official capacity so that |
| // histo_queue->queue[histo_queue->max_size] is read/written within bound. |
| assert(histo_queue->size <= histo_queue->max_size); |
| } |
| |
| // ----------------------------------------------------------------------------- |
| |
| static void PreparePair(VP8LHistogram** histograms, int idx1, int idx2, |
| HistogramPair* const pair) { |
| VP8LHistogram* h1; |
| VP8LHistogram* h2; |
| double sum_cost; |
| |
| if (idx1 > idx2) { |
| const int tmp = idx2; |
| idx2 = idx1; |
| idx1 = tmp; |
| } |
| pair->idx1 = idx1; |
| pair->idx2 = idx2; |
| h1 = histograms[idx1]; |
| h2 = histograms[idx2]; |
| sum_cost = h1->bit_cost_ + h2->bit_cost_; |
| pair->cost_combo = 0.; |
| GetCombinedHistogramEntropy(h1, h2, sum_cost, &pair->cost_combo); |
| pair->cost_diff = pair->cost_combo - sum_cost; |
| } |
| |
| // Combines histograms by continuously choosing the one with the highest cost |
| // reduction. |
| static int HistogramCombineGreedy(VP8LHistogramSet* const image_histo) { |
| int ok = 0; |
| int image_histo_size = image_histo->size; |
| int i, j; |
| VP8LHistogram** const histograms = image_histo->histograms; |
| // Indexes of remaining histograms. |
| int* const clusters = WebPSafeMalloc(image_histo_size, sizeof(*clusters)); |
| // Priority queue of histogram pairs. |
| HistoQueue histo_queue; |
| |
| if (!HistoQueueInit(&histo_queue, image_histo_size) || clusters == NULL) { |
| goto End; |
| } |
| |
| for (i = 0; i < image_histo_size; ++i) { |
| // Initialize clusters indexes. |
| clusters[i] = i; |
| for (j = i + 1; j < image_histo_size; ++j) { |
| // Initialize positions array. |
| PreparePair(histograms, i, j, &histo_queue.queue[histo_queue.size]); |
| UpdateQueueFront(&histo_queue); |
| } |
| } |
| |
| while (image_histo_size > 1 && histo_queue.size > 0) { |
| HistogramPair* copy_to; |
| const int idx1 = histo_queue.queue[0].idx1; |
| const int idx2 = histo_queue.queue[0].idx2; |
| VP8LHistogramAdd(histograms[idx2], histograms[idx1], histograms[idx1]); |
| histograms[idx1]->bit_cost_ = histo_queue.queue[0].cost_combo; |
| // Remove merged histogram. |
| for (i = 0; i + 1 < image_histo_size; ++i) { |
| if (clusters[i] >= idx2) { |
| clusters[i] = clusters[i + 1]; |
| } |
| } |
| --image_histo_size; |
| |
| // Remove pairs intersecting the just combined best pair. This will |
| // therefore pop the head of the queue. |
| copy_to = histo_queue.queue; |
| for (i = 0; i < histo_queue.size; ++i) { |
| HistogramPair* const p = histo_queue.queue + i; |
| if (p->idx1 == idx1 || p->idx2 == idx1 || |
| p->idx1 == idx2 || p->idx2 == idx2) { |
| // Do not copy the invalid pair. |
| continue; |
| } |
| if (p->cost_diff < histo_queue.queue[0].cost_diff) { |
| // Replace the top of the queue if we found better. |
| SwapHistogramPairs(histo_queue.queue, p); |
| } |
| SwapHistogramPairs(copy_to, p); |
| ++copy_to; |
| } |
| histo_queue.size = (int)(copy_to - histo_queue.queue); |
| |
| // Push new pairs formed with combined histogram to the queue. |
| for (i = 0; i < image_histo_size; ++i) { |
| if (clusters[i] != idx1) { |
| PreparePair(histograms, idx1, clusters[i], |
| &histo_queue.queue[histo_queue.size]); |
| UpdateQueueFront(&histo_queue); |
| } |
| } |
| } |
| // Move remaining histograms to the beginning of the array. |
| for (i = 0; i < image_histo_size; ++i) { |
| if (i != clusters[i]) { // swap the two histograms |
| HistogramSwap(&histograms[i], &histograms[clusters[i]]); |
| } |
| } |
| |
| image_histo->size = image_histo_size; |
| ok = 1; |
| |
| End: |
| WebPSafeFree(clusters); |
| HistoQueueClear(&histo_queue); |
| return ok; |
| } |
| |
| static void HistogramCombineStochastic(VP8LHistogramSet* const image_histo, |
| VP8LHistogram* tmp_histo, |
| VP8LHistogram* best_combo, |
| int quality, int min_cluster_size) { |
| 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; |
| VP8LHistogram** const histograms = image_histo->histograms; |
| |
| // Collapse similar histograms in 'image_histo'. |
| ++min_cluster_size; |
| 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], |
| tmp_histo, best_cost_diff); |
| if (curr_cost_diff < best_cost_diff) { // found a better pair? |
| HistogramSwap(&best_combo, &tmp_histo); |
| best_cost_diff = curr_cost_diff; |
| best_idx1 = idx1; |
| best_idx2 = idx2; |
| } |
| } |
| |
| if (best_idx1 >= 0) { |
| HistogramSwap(&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) { |
| HistogramSwap(&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 in, |
| const VP8LHistogramSet* const out, |
| uint16_t* const symbols) { |
| int i; |
| VP8LHistogram** const in_histo = in->histograms; |
| VP8LHistogram** const out_histo = out->histograms; |
| const int in_size = in->size; |
| const int out_size = out->size; |
| if (out_size > 1) { |
| for (i = 0; i < in_size; ++i) { |
| int best_out = 0; |
| double best_bits = MAX_COST; |
| int k; |
| for (k = 0; k < out_size; ++k) { |
| const double cur_bits = |
| HistogramAddThresh(out_histo[k], in_histo[i], best_bits); |
| if (k == 0 || cur_bits < best_bits) { |
| best_bits = cur_bits; |
| best_out = k; |
| } |
| } |
| symbols[i] = best_out; |
| } |
| } else { |
| assert(out_size == 1); |
| for (i = 0; i < in_size; ++i) { |
| symbols[i] = 0; |
| } |
| } |
| |
| // Recompute each out based on raw and symbols. |
| for (i = 0; i < out_size; ++i) { |
| HistogramClear(out_histo[i]); |
| } |
| |
| for (i = 0; i < in_size; ++i) { |
| const int idx = symbols[i]; |
| VP8LHistogramAdd(in_histo[i], out_histo[idx], out_histo[idx]); |
| } |
| } |
| |
| static double GetCombineCostFactor(int histo_size, int quality) { |
| double combine_cost_factor = 0.16; |
| if (quality < 90) { |
| 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 low_effort, |
| int histo_bits, int cache_bits, |
| VP8LHistogramSet* const image_histo, |
| VP8LHistogramSet* const tmp_histos, |
| 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; |
| const int entropy_combine_num_bins = low_effort ? NUM_PARTITIONS : BIN_SIZE; |
| |
| // 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] = unused indices. |
| const int bin_depth = image_histo_raw_size + 1; |
| int16_t* bin_map = NULL; |
| VP8LHistogramSet* const orig_histo = |
| VP8LAllocateHistogramSet(image_histo_raw_size, cache_bits); |
| VP8LHistogram* cur_combo; |
| const int entropy_combine = |
| (orig_histo->size > entropy_combine_num_bins * 2) && (quality < 100); |
| |
| if (orig_histo == NULL) goto Error; |
| |
| // Don't attempt linear bin-partition heuristic for: |
| // histograms of small sizes, as bin_map will be very sparse and; |
| // Maximum quality (q==100), to preserve the compression gains at that level. |
| if (entropy_combine) { |
| const int bin_map_size = bin_depth * entropy_combine_num_bins; |
| 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); |
| |
| cur_combo = tmp_histos->histograms[1]; // pick up working slot |
| if (entropy_combine) { |
| const double combine_cost_factor = |
| GetCombineCostFactor(image_histo_raw_size, quality); |
| HistogramAnalyzeEntropyBin(orig_histo, bin_map, low_effort); |
| // Collapse histograms with similar entropy. |
| cur_combo = HistogramCombineEntropyBin(image_histo, cur_combo, bin_map, |
| bin_depth, entropy_combine_num_bins, |
| combine_cost_factor, low_effort); |
| } |
| |
| // Don't combine the histograms using stochastic and greedy heuristics for |
| // low-effort compression mode. |
| if (!low_effort || !entropy_combine) { |
| const float x = quality / 100.f; |
| // cubic ramp between 1 and MAX_HISTO_GREEDY: |
| const int threshold_size = (int)(1 + (x * x * x) * (MAX_HISTO_GREEDY - 1)); |
| HistogramCombineStochastic(image_histo, tmp_histos->histograms[0], |
| cur_combo, quality, threshold_size); |
| if ((image_histo->size <= threshold_size) && |
| !HistogramCombineGreedy(image_histo)) { |
| goto Error; |
| } |
| } |
| |
| // TODO(vikasa): Optimize HistogramRemap for low-effort compression mode also. |
| // 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); |
| return ok; |
| } |
