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authorRémi Verschelde <rverschelde@gmail.com>2017-12-12 00:14:26 +0100
committerGitHub <noreply@github.com>2017-12-12 00:14:26 +0100
commit3a078603112710d1d2719d7919711ab76ae161f0 (patch)
treef01b1d94887864387026e2955b9a69b7dd10318c /thirdparty/libwebp/src/enc/histogram_enc.c
parent33db6a14df19a8d3feecac5d4254699c34625fc1 (diff)
parent043103fe6a1168729abf74dd56b8982ce54eea43 (diff)
Merge pull request #14561 from volzhs/libwebp-0.6.1
Update libwebp to 0.6.1
Diffstat (limited to 'thirdparty/libwebp/src/enc/histogram_enc.c')
-rw-r--r--thirdparty/libwebp/src/enc/histogram_enc.c1043
1 files changed, 1043 insertions, 0 deletions
diff --git a/thirdparty/libwebp/src/enc/histogram_enc.c b/thirdparty/libwebp/src/enc/histogram_enc.c
new file mode 100644
index 0000000000..056a972dda
--- /dev/null
+++ b/thirdparty/libwebp/src/enc/histogram_enc.c
@@ -0,0 +1,1043 @@
+// 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 "src/webp/config.h"
+#endif
+
+#include <math.h>
+
+#include "src/enc/backward_references_enc.h"
+#include "src/enc/histogram_enc.h"
+#include "src/dsp/lossless.h"
+#include "src/dsp/lossless_common.h"
+#include "src/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, NULL, 0);
+ 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,
+ int (*const distance_modifier)(int, int),
+ int distance_modifier_arg0) {
+ 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];
+ if (distance_modifier == NULL) {
+ VP8LPrefixEncodeBits(PixOrCopyDistance(v), &code, &extra_bits);
+ } else {
+ VP8LPrefixEncodeBits(
+ distance_modifier(distance_modifier_arg0, 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) {
+ // The constants in this function are experimental and got rounded from
+ // their original values in 1/8 when switched to 1/1024.
+ double retval = InitialHuffmanCost();
+ // Second coefficient: Many zeros in the histogram are covered efficiently
+ // by a run-length encode. Originally 2/8.
+ retval += stats->counts[0] * 1.5625 + 0.234375 * stats->streaks[0][1];
+ // Second coefficient: Constant values are encoded less efficiently, but still
+ // RLE'ed. Originally 6/8.
+ retval += stats->counts[1] * 2.578125 + 0.703125 * stats->streaks[1][1];
+ // 0s are usually encoded more efficiently than non-0s.
+ // Originally 15/8.
+ retval += 1.796875 * stats->streaks[0][0];
+ // Originally 26/8.
+ 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);
+}
+
+// trivial_at_end is 1 if the two histograms only have one element that is
+// non-zero: both the zero-th one, or both the last one.
+static WEBP_INLINE double GetCombinedEntropy(const uint32_t* const X,
+ const uint32_t* const Y,
+ int length, int trivial_at_end) {
+ VP8LStreaks stats;
+ if (trivial_at_end) {
+ // This configuration is due to palettization that transforms an indexed
+ // pixel into 0xff000000 | (pixel << 8) in VP8LBundleColorMap.
+ // BitsEntropyRefine is 0 for histograms with only one non-zero value.
+ // Only FinalHuffmanCost needs to be evaluated.
+ memset(&stats, 0, sizeof(stats));
+ // Deal with the non-zero value at index 0 or length-1.
+ stats.streaks[1][0] += 1;
+ // Deal with the following/previous zero streak.
+ stats.counts[0] += 1;
+ stats.streaks[0][1] += length - 1;
+ return FinalHuffmanCost(&stats);
+ } else {
+ VP8LBitEntropy bit_entropy;
+ 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_;
+ int trivial_at_end = 0;
+ assert(a->palette_code_bits_ == b->palette_code_bits_);
+ *cost += GetCombinedEntropy(a->literal_, b->literal_,
+ VP8LHistogramNumCodes(palette_code_bits), 0);
+ *cost += VP8LExtraCostCombined(a->literal_ + NUM_LITERAL_CODES,
+ b->literal_ + NUM_LITERAL_CODES,
+ NUM_LENGTH_CODES);
+ if (*cost > cost_threshold) return 0;
+
+ if (a->trivial_symbol_ != VP8L_NON_TRIVIAL_SYM &&
+ a->trivial_symbol_ == b->trivial_symbol_) {
+ // A, R and B are all 0 or 0xff.
+ const uint32_t color_a = (a->trivial_symbol_ >> 24) & 0xff;
+ const uint32_t color_r = (a->trivial_symbol_ >> 16) & 0xff;
+ const uint32_t color_b = (a->trivial_symbol_ >> 0) & 0xff;
+ if ((color_a == 0 || color_a == 0xff) &&
+ (color_r == 0 || color_r == 0xff) &&
+ (color_b == 0 || color_b == 0xff)) {
+ trivial_at_end = 1;
+ }
+ }
+
+ *cost +=
+ GetCombinedEntropy(a->red_, b->red_, NUM_LITERAL_CODES, trivial_at_end);
+ if (*cost > cost_threshold) return 0;
+
+ *cost +=
+ GetCombinedEntropy(a->blue_, b->blue_, NUM_LITERAL_CODES, trivial_at_end);
+ if (*cost > cost_threshold) return 0;
+
+ *cost += GetCombinedEntropy(a->alpha_, b->alpha_, NUM_LITERAL_CODES,
+ trivial_at_end);
+ if (*cost > cost_threshold) return 0;
+
+ *cost +=
+ GetCombinedEntropy(a->distance_, b->distance_, NUM_DISTANCE_CODES, 0);
+ *cost +=
+ VP8LExtraCostCombined(a->distance_, b->distance_, NUM_DISTANCE_CODES);
+ if (*cost > cost_threshold) return 0;
+
+ return 1;
+}
+
+static WEBP_INLINE void HistogramAdd(const VP8LHistogram* const a,
+ const VP8LHistogram* const b,
+ VP8LHistogram* const out) {
+ VP8LHistogramAdd(a, b, out);
+ out->trivial_symbol_ = (a->trivial_symbol_ == b->trivial_symbol_)
+ ? a->trivial_symbol_
+ : VP8L_NON_TRIVIAL_SYM;
+}
+
+// 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)) {
+ HistogramAdd(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) {
+ 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, NULL, 0);
+ 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,
+ uint16_t* const bin_map,
+ int low_effort) {
+ int i;
+ VP8LHistogram** const histograms = image_histo->histograms;
+ const int histo_size = image_histo->size;
+ DominantCostRange cost_range;
+ DominantCostRangeInit(&cost_range);
+
+ // Analyze the dominant (literal, red and blue) entropy costs.
+ for (i = 0; i < histo_size; ++i) {
+ UpdateDominantCostRange(histograms[i], &cost_range);
+ }
+
+ // bin-hash histograms on three of the dominant (literal, red and blue)
+ // symbol costs and store the resulting bin_id for each histogram.
+ for (i = 0; i < histo_size; ++i) {
+ bin_map[i] = GetHistoBinIndex(histograms[i], &cost_range, low_effort);
+ }
+}
+
+// Compact image_histo[] by merging some histograms with same bin_id together if
+// it's advantageous.
+static void HistogramCombineEntropyBin(VP8LHistogramSet* const image_histo,
+ VP8LHistogram* cur_combo,
+ const uint16_t* const bin_map,
+ int bin_map_size, int num_bins,
+ double combine_cost_factor,
+ int low_effort) {
+ VP8LHistogram** const histograms = image_histo->histograms;
+ int idx;
+ // Work in-place: processed histograms are put at the beginning of
+ // image_histo[]. At the end, we just have to truncate the array.
+ int size = 0;
+ struct {
+ int16_t first; // position of the histogram that accumulates all
+ // histograms with the same bin_id
+ uint16_t num_combine_failures; // number of combine failures per bin_id
+ } bin_info[BIN_SIZE];
+
+ assert(num_bins <= BIN_SIZE);
+ for (idx = 0; idx < num_bins; ++idx) {
+ bin_info[idx].first = -1;
+ bin_info[idx].num_combine_failures = 0;
+ }
+
+ for (idx = 0; idx < bin_map_size; ++idx) {
+ const int bin_id = bin_map[idx];
+ const int first = bin_info[bin_id].first;
+ assert(size <= idx);
+ if (first == -1) {
+ // just move histogram #idx to its final position
+ histograms[size] = histograms[idx];
+ bin_info[bin_id].first = size++;
+ } else if (low_effort) {
+ HistogramAdd(histograms[idx], histograms[first], histograms[first]);
+ } else {
+ // try to merge #idx into #first (both share the same bin_id)
+ const double bit_cost = histograms[idx]->bit_cost_;
+ const double bit_cost_thresh = -bit_cost * combine_cost_factor;
+ const double curr_cost_diff =
+ HistogramAddEval(histograms[first], histograms[idx],
+ 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[idx]->trivial_symbol_ == VP8L_NON_TRIVIAL_SYM) &&
+ (histograms[first]->trivial_symbol_ == VP8L_NON_TRIVIAL_SYM));
+ const int max_combine_failures = 32;
+ if (try_combine ||
+ bin_info[bin_id].num_combine_failures >= max_combine_failures) {
+ // move the (better) merged histogram to its final slot
+ HistogramSwap(&cur_combo, &histograms[first]);
+ } else {
+ histograms[size++] = histograms[idx];
+ ++bin_info[bin_id].num_combine_failures;
+ }
+ } else {
+ histograms[size++] = histograms[idx];
+ }
+ }
+ }
+ image_histo->size = size;
+ if (low_effort) {
+ // for low_effort case, update the final cost when everything is merged
+ for (idx = 0; idx < size; ++idx) {
+ UpdateHistogramCost(histograms[idx]);
+ }
+ }
+}
+
+// Implement a Lehmer random number generator with a multiplicative constant of
+// 48271 and a modulo constant of 2^31 − 1.
+static uint32_t MyRand(uint32_t* const seed) {
+ *seed = (uint32_t)(((uint64_t)(*seed) * 48271u) % 2147483647u);
+ assert(*seed > 0);
+ 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);
+ histo_queue->size = 0;
+ histo_queue->max_size = 0;
+}
+
+// Pop a specific pair in the queue by replacing it with the last one
+// and shrinking the queue.
+static void HistoQueuePopPair(HistoQueue* const histo_queue,
+ HistogramPair* const pair) {
+ assert(pair >= histo_queue->queue &&
+ pair < (histo_queue->queue + histo_queue->size));
+ assert(histo_queue->size > 0);
+ *pair = histo_queue->queue[histo_queue->size - 1];
+ --histo_queue->size;
+}
+
+// Check whether a pair in the queue should be updated as head or not.
+static void HistoQueueUpdateHead(HistoQueue* const histo_queue,
+ HistogramPair* const pair) {
+ assert(pair->cost_diff < 0.);
+ assert(pair >= histo_queue->queue &&
+ pair < (histo_queue->queue + histo_queue->size));
+ assert(histo_queue->size > 0);
+ if (pair->cost_diff < histo_queue->queue[0].cost_diff) {
+ // Replace the best pair.
+ const HistogramPair tmp = histo_queue->queue[0];
+ histo_queue->queue[0] = *pair;
+ *pair = tmp;
+ }
+}
+
+// Create a pair from indices "idx1" and "idx2" provided its cost
+// is inferior to "threshold", a negative entropy.
+// It returns the cost of the pair, or 0. if it superior to threshold.
+static double HistoQueuePush(HistoQueue* const histo_queue,
+ VP8LHistogram** const histograms, int idx1,
+ int idx2, double threshold) {
+ const VP8LHistogram* h1;
+ const VP8LHistogram* h2;
+ HistogramPair pair;
+ double sum_cost;
+
+ assert(threshold <= 0.);
+ 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 + threshold, &pair.cost_combo);
+ pair.cost_diff = pair.cost_combo - sum_cost;
+
+ // Do not even consider the pair if it does not improve the entropy.
+ if (pair.cost_diff >= threshold) return 0.;
+
+ // We cannot add more elements than the capacity.
+ assert(histo_queue->size < histo_queue->max_size);
+ histo_queue->queue[histo_queue->size++] = pair;
+ HistoQueueUpdateHead(histo_queue, &histo_queue->queue[histo_queue->size - 1]);
+
+ return pair.cost_diff;
+}
+
+// -----------------------------------------------------------------------------
+
+// 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.
+ HistoQueuePush(&histo_queue, histograms, i, j, 0.);
+ }
+ }
+
+ while (image_histo_size > 1 && histo_queue.size > 0) {
+ const int idx1 = histo_queue.queue[0].idx1;
+ const int idx2 = histo_queue.queue[0].idx2;
+ HistogramAdd(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.
+ for (i = 0; i < histo_queue.size;) {
+ HistogramPair* const p = histo_queue.queue + i;
+ if (p->idx1 == idx1 || p->idx2 == idx1 ||
+ p->idx1 == idx2 || p->idx2 == idx2) {
+ HistoQueuePopPair(&histo_queue, p);
+ } else {
+ HistoQueueUpdateHead(&histo_queue, p);
+ ++i;
+ }
+ }
+
+ // Push new pairs formed with combined histogram to the queue.
+ for (i = 0; i < image_histo_size; ++i) {
+ if (clusters[i] != idx1) {
+ HistoQueuePush(&histo_queue, histograms, idx1, clusters[i], 0.);
+ }
+ }
+ }
+ // 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;
+}
+
+// Perform histogram aggregation using a stochastic approach.
+// 'do_greedy' is set to 1 if a greedy approach needs to be performed
+// afterwards, 0 otherwise.
+static int HistogramCombineStochastic(VP8LHistogramSet* const image_histo,
+ int min_cluster_size,
+ int* const do_greedy) {
+ int iter;
+ uint32_t seed = 1;
+ int tries_with_no_success = 0;
+ int image_histo_size = image_histo->size;
+ const int outer_iters = image_histo_size;
+ const int num_tries_no_success = outer_iters / 2;
+ VP8LHistogram** const histograms = image_histo->histograms;
+ // Priority queue of histogram pairs. Its size of "kCostHeapSizeSqrt"^2
+ // impacts the quality of the compression and the speed: the smaller the
+ // faster but the worse for the compression.
+ HistoQueue histo_queue;
+ const int kHistoQueueSizeSqrt = 3;
+ int ok = 0;
+
+ if (!HistoQueueInit(&histo_queue, kHistoQueueSizeSqrt)) {
+ goto End;
+ }
+ // Collapse similar histograms in 'image_histo'.
+ ++min_cluster_size;
+ for (iter = 0; iter < outer_iters && image_histo_size >= min_cluster_size &&
+ ++tries_with_no_success < num_tries_no_success;
+ ++iter) {
+ double best_cost =
+ (histo_queue.size == 0) ? 0. : histo_queue.queue[0].cost_diff;
+ int best_idx1 = -1, best_idx2 = 1;
+ int j;
+ const uint32_t rand_range = (image_histo_size - 1) * image_histo_size;
+ // image_histo_size / 2 was chosen empirically. Less means faster but worse
+ // compression.
+ const int num_tries = image_histo_size / 2;
+
+ for (j = 0; j < num_tries; ++j) {
+ double curr_cost;
+ // Choose two different histograms at random and try to combine them.
+ const uint32_t tmp = MyRand(&seed) % rand_range;
+ const uint32_t idx1 = tmp / (image_histo_size - 1);
+ uint32_t idx2 = tmp % (image_histo_size - 1);
+ if (idx2 >= idx1) ++idx2;
+
+ // Calculate cost reduction on combination.
+ curr_cost =
+ HistoQueuePush(&histo_queue, histograms, idx1, idx2, best_cost);
+ if (curr_cost < 0) { // found a better pair?
+ best_cost = curr_cost;
+ // Empty the queue if we reached full capacity.
+ if (histo_queue.size == histo_queue.max_size) break;
+ }
+ }
+ if (histo_queue.size == 0) continue;
+
+ // Merge the two best histograms.
+ best_idx1 = histo_queue.queue[0].idx1;
+ best_idx2 = histo_queue.queue[0].idx2;
+ assert(best_idx1 < best_idx2);
+ HistogramAddEval(histograms[best_idx1], histograms[best_idx2],
+ histograms[best_idx1], 0);
+ // Swap the best_idx2 histogram with the 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;
+ // Parse the queue and update each pair that deals with best_idx1,
+ // best_idx2 or image_histo_size.
+ for (j = 0; j < histo_queue.size;) {
+ HistogramPair* const p = histo_queue.queue + j;
+ const int is_idx1_best = p->idx1 == best_idx1 || p->idx1 == best_idx2;
+ const int is_idx2_best = p->idx2 == best_idx1 || p->idx2 == best_idx2;
+ int do_eval = 0;
+ // The front pair could have been duplicated by a random pick so
+ // check for it all the time nevertheless.
+ if (is_idx1_best && is_idx2_best) {
+ HistoQueuePopPair(&histo_queue, p);
+ continue;
+ }
+ // Any pair containing one of the two best indices should only refer to
+ // best_idx1. Its cost should also be updated.
+ if (is_idx1_best) {
+ p->idx1 = best_idx1;
+ do_eval = 1;
+ } else if (is_idx2_best) {
+ p->idx2 = best_idx1;
+ do_eval = 1;
+ }
+ if (p->idx2 == image_histo_size) {
+ // No need to re-evaluate here as it does not involve a pair
+ // containing best_idx1 or best_idx2.
+ p->idx2 = best_idx2;
+ }
+ assert(p->idx2 < image_histo_size);
+ // Make sure the index order is respected.
+ if (p->idx1 > p->idx2) {
+ const int tmp = p->idx2;
+ p->idx2 = p->idx1;
+ p->idx1 = tmp;
+ }
+ if (do_eval) {
+ // Re-evaluate the cost of an updated pair.
+ GetCombinedHistogramEntropy(histograms[p->idx1], histograms[p->idx2], 0,
+ &p->cost_diff);
+ if (p->cost_diff >= 0.) {
+ HistoQueuePopPair(&histo_queue, p);
+ continue;
+ }
+ }
+ HistoQueueUpdateHead(&histo_queue, p);
+ ++j;
+ }
+
+ tries_with_no_success = 0;
+ }
+ image_histo->size = image_histo_size;
+ *do_greedy = (image_histo->size <= min_cluster_size);
+ ok = 1;
+
+End:
+ HistoQueueClear(&histo_queue);
+ return ok;
+}
+
+// -----------------------------------------------------------------------------
+// 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];
+ HistogramAdd(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,
+ VP8LHistogram* const tmp_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;
+ VP8LHistogramSet* const orig_histo =
+ VP8LAllocateHistogramSet(image_histo_raw_size, cache_bits);
+ // 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).
+ const int entropy_combine_num_bins = low_effort ? NUM_PARTITIONS : BIN_SIZE;
+ const int entropy_combine =
+ (orig_histo->size > entropy_combine_num_bins * 2) && (quality < 100);
+
+ if (orig_histo == 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 (entropy_combine) {
+ const int bin_map_size = orig_histo->size;
+ // Reuse histogram_symbols storage. By definition, it's guaranteed to be ok.
+ uint16_t* const bin_map = histogram_symbols;
+ const double combine_cost_factor =
+ GetCombineCostFactor(image_histo_raw_size, quality);
+
+ HistogramAnalyzeEntropyBin(orig_histo, bin_map, low_effort);
+ // Collapse histograms with similar entropy.
+ HistogramCombineEntropyBin(image_histo, tmp_histo, bin_map, bin_map_size,
+ 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));
+ int do_greedy;
+ if (!HistogramCombineStochastic(image_histo, threshold_size, &do_greedy)) {
+ goto Error;
+ }
+ if (do_greedy && !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:
+ VP8LFreeHistogramSet(orig_histo);
+ return ok;
+}