Bundled libwebp updated to version 0.6.0

This commit imports libwebp 0.6.0, including AUTHORS, COPYING, ChangeLog,
NEWS, PATENTS, README and src directories. In src, only includes header
and source files.

Upstream changes since 0.5.1 have been merged in.
Also updated version in qt_attribution.json.

Conflicts:
	src/3rdparty/libwebp.pri
	src/3rdparty/libwebp/qt_attribution.json
	src/3rdparty/libwebp/src/webp/config.h

Change-Id: I001aa7a3fabf0130b54f9005c23aa822bc1d0ec1
Reviewed-by: Eirik Aavitsland <eirik.aavitsland@qt.io>

1 files changed, 990 insertions, 0 deletions

diff --git a/src/3rdparty/libwebp/src/enc/histogram_enc.c b/src/3rdparty/libwebp/src/enc/histogram_enc.c
new file mode 100644
index 0000000..808b6f7
--- /dev/null
+++ b/src/3rdparty/libwebp/src/enc/histogram_enc.c
@@ -0,0 +1,990 @@
+// 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_enc.h"
+#include "./histogram_enc.h"
+#include "../dsp/lossless.h"
+#include "../dsp/lossless_common.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) {
+  // 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);
+    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 VP8LHistogram* 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]);
+    }
+  }
+  return cur_combo;
+}
+
+static uint32_t MyRand(uint32_t* const seed) {
+  *seed = (*seed * 16807ull) & 0xffffffffu;
+  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;
+    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. 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;
+  int idx2_max = image_histo_size - 1;
+  int do_brute_dorce = 0;
+  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;
+    int num_tries =
+        (num_pairs < image_histo_size) ? num_pairs : image_histo_size;
+    // Use a brute force approach if:
+    // - stochastic has not worked for a while and
+    // - if the number of iterations for brute force is less than the number of
+    // iterations if we never find a match ever again stochastically (hence
+    // num_tries times the number of remaining outer iterations).
+    do_brute_dorce =
+        (tries_with_no_success > 10) &&
+        (idx2_max * (idx2_max + 1) < 2 * num_tries * (outer_iters - iter));
+    if (do_brute_dorce) num_tries = idx2_max;
+
+    seed += iter;
+    for (j = 0; j < num_tries; ++j) {
+      double curr_cost_diff;
+      // Choose two histograms at random and try to combine them.
+      uint32_t idx1, idx2;
+      if (do_brute_dorce) {
+        // Use a brute force approach.
+        idx1 = (uint32_t)j;
+        idx2 = (uint32_t)idx2_max;
+      } else {
+        const uint32_t tmp = (j & 7) + 1;
+        const uint32_t diff =
+            (tmp < 3) ? tmp : MyRand(&seed) % (image_histo_size - 1);
+        idx1 = MyRand(&seed) % image_histo_size;
+        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 (do_brute_dorce) --idx2_max;
+
+    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 (idx2_max >= image_histo_size) idx2_max = image_histo_size - 1;
+      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 || idx2_max == 0) {
+      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];
+    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,
+                             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;
+  VP8LHistogramSet* const orig_histo =
+      VP8LAllocateHistogramSet(image_histo_raw_size, cache_bits);
+  VP8LHistogram* cur_combo;
+  // 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);
+
+  cur_combo = tmp_histos->histograms[1];  // pick up working slot
+  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.
+    cur_combo = HistogramCombineEntropyBin(image_histo, cur_combo,
+                                           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));
+    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:
+  VP8LFreeHistogramSet(orig_histo);
+  return ok;
+}