| Index: third_party/libwebp/enc/histogram.c
|
| diff --git a/third_party/libwebp/enc/histogram.c b/third_party/libwebp/enc/histogram.c
|
| deleted file mode 100644
|
| index 36b7f2262599c94728d30966a8370eb538722f51..0000000000000000000000000000000000000000
|
| --- a/third_party/libwebp/enc/histogram.c
|
| +++ /dev/null
|
| @@ -1,938 +0,0 @@
|
| -// 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)
|
| -// 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 = (HistogramPair*)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 =
|
| - (int*)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;
|
| -}
|
|
|