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authorDaniel Baumann <daniel.baumann@progress-linux.org>2024-04-21 11:44:51 +0000
committerDaniel Baumann <daniel.baumann@progress-linux.org>2024-04-21 11:44:51 +0000
commit9e3c08db40b8916968b9f30096c7be3f00ce9647 (patch)
treea68f146d7fa01f0134297619fbe7e33db084e0aa /media/libwebp/src/enc/histogram_enc.c
parentInitial commit. (diff)
downloadthunderbird-upstream.tar.xz
thunderbird-upstream.zip
Adding upstream version 1:115.7.0.upstream/1%115.7.0upstream
Signed-off-by: Daniel Baumann <daniel.baumann@progress-linux.org>
Diffstat (limited to 'media/libwebp/src/enc/histogram_enc.c')
-rw-r--r--media/libwebp/src/enc/histogram_enc.c1248
1 files changed, 1248 insertions, 0 deletions
diff --git a/media/libwebp/src/enc/histogram_enc.c b/media/libwebp/src/enc/histogram_enc.c
new file mode 100644
index 0000000000..8418def2e1
--- /dev/null
+++ b/media/libwebp/src/enc/histogram_enc.c
@@ -0,0 +1,1248 @@
+// 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 <float.h>
+#include <math.h>
+
+#include "src/dsp/lossless.h"
+#include "src/dsp/lossless_common.h"
+#include "src/enc/backward_references_enc.h"
+#include "src/enc/histogram_enc.h"
+#include "src/enc/vp8i_enc.h"
+#include "src/utils/utils.h"
+
+#define MAX_BIT_COST FLT_MAX
+
+// 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 literal_size = VP8LHistogramNumCodes(dst_cache_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;
+ memcpy(dst->literal_, src->literal_, literal_size * sizeof(*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,
+ int init_arrays) {
+ p->palette_code_bits_ = palette_code_bits;
+ if (init_arrays) {
+ HistogramClear(p);
+ } else {
+ p->trivial_symbol_ = 0;
+ p->bit_cost_ = 0.;
+ p->literal_cost_ = 0.;
+ p->red_cost_ = 0.;
+ p->blue_cost_ = 0.;
+ memset(p->is_used_, 0, sizeof(p->is_used_));
+ }
+}
+
+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, /*init_arrays=*/ 0);
+ return histo;
+}
+
+// Resets the pointers of the histograms to point to the bit buffer in the set.
+static void HistogramSetResetPointers(VP8LHistogramSet* const set,
+ int cache_bits) {
+ int i;
+ const int histo_size = VP8LGetHistogramSize(cache_bits);
+ uint8_t* memory = (uint8_t*) (set->histograms);
+ memory += set->max_size * sizeof(*set->histograms);
+ for (i = 0; i < set->max_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));
+ memory += histo_size;
+ }
+}
+
+// Returns the total size of the VP8LHistogramSet.
+static size_t HistogramSetTotalSize(int size, int cache_bits) {
+ const int histo_size = VP8LGetHistogramSize(cache_bits);
+ return (sizeof(VP8LHistogramSet) + size * (sizeof(VP8LHistogram*) +
+ histo_size + WEBP_ALIGN_CST));
+}
+
+VP8LHistogramSet* VP8LAllocateHistogramSet(int size, int cache_bits) {
+ int i;
+ VP8LHistogramSet* set;
+ const size_t total_size = HistogramSetTotalSize(size, cache_bits);
+ 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;
+ set->max_size = size;
+ set->size = size;
+ HistogramSetResetPointers(set, cache_bits);
+ for (i = 0; i < size; ++i) {
+ VP8LHistogramInit(set->histograms[i], cache_bits, /*init_arrays=*/ 0);
+ }
+ return set;
+}
+
+void VP8LHistogramSetClear(VP8LHistogramSet* const set) {
+ int i;
+ const int cache_bits = set->histograms[0]->palette_code_bits_;
+ const int size = set->max_size;
+ const size_t total_size = HistogramSetTotalSize(size, cache_bits);
+ uint8_t* memory = (uint8_t*)set;
+
+ memset(memory, 0, total_size);
+ memory += sizeof(*set);
+ set->histograms = (VP8LHistogram**)memory;
+ set->max_size = size;
+ set->size = size;
+ HistogramSetResetPointers(set, cache_bits);
+ for (i = 0; i < size; ++i) {
+ set->histograms[i]->palette_code_bits_ = cache_bits;
+ }
+}
+
+// Removes the histogram 'i' from 'set' by setting it to NULL.
+static void HistogramSetRemoveHistogram(VP8LHistogramSet* const set, int i,
+ int* const num_used) {
+ assert(set->histograms[i] != NULL);
+ set->histograms[i] = NULL;
+ --*num_used;
+ // If we remove the last valid one, shrink until the next valid one.
+ if (i == set->size - 1) {
+ while (set->size >= 1 && set->histograms[set->size - 1] == NULL) {
+ --set->size;
+ }
+ }
+}
+
+// -----------------------------------------------------------------------------
+
+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);
+ assert(histo->palette_code_bits_ != 0);
+ ++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 float BitsEntropyRefine(const VP8LBitEntropy* entropy) {
+ float 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 0.99f * entropy->sum + 0.01f * 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 = 0.95f;
+ } else {
+ mix = 0.7f; // nonzeros == 4.
+ }
+ } else {
+ mix = 0.627f;
+ }
+
+ {
+ float min_limit = 2.f * entropy->sum - entropy->max_val;
+ min_limit = mix * min_limit + (1.f - mix) * entropy->entropy;
+ return (entropy->entropy < min_limit) ? min_limit : entropy->entropy;
+ }
+}
+
+float VP8LBitsEntropy(const uint32_t* const array, int n) {
+ VP8LBitEntropy entropy;
+ VP8LBitsEntropyUnrefined(array, n, &entropy);
+
+ return BitsEntropyRefine(&entropy);
+}
+
+static float 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 float kSmallBias = 9.1f;
+ return kHuffmanCodeOfHuffmanCodeSize - kSmallBias;
+}
+
+// Finalize the Huffman cost based on streak numbers and length type (<3 or >=3)
+static float 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.
+ float retval = InitialHuffmanCost();
+ // Second coefficient: Many zeros in the histogram are covered efficiently
+ // by a run-length encode. Originally 2/8.
+ retval += stats->counts[0] * 1.5625f + 0.234375f * stats->streaks[0][1];
+ // Second coefficient: Constant values are encoded less efficiently, but still
+ // RLE'ed. Originally 6/8.
+ retval += stats->counts[1] * 2.578125f + 0.703125f * stats->streaks[1][1];
+ // 0s are usually encoded more efficiently than non-0s.
+ // Originally 15/8.
+ retval += 1.796875f * stats->streaks[0][0];
+ // Originally 26/8.
+ retval += 3.28125f * 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 float PopulationCost(const uint32_t* const population, int length,
+ uint32_t* const trivial_sym,
+ uint8_t* const is_used) {
+ 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;
+ }
+ // The histogram is used if there is at least one non-zero streak.
+ *is_used = (stats.streaks[1][0] != 0 || stats.streaks[1][1] != 0);
+
+ 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 float GetCombinedEntropy(const uint32_t* const X,
+ const uint32_t* const Y, int length,
+ int is_X_used, int is_Y_used,
+ 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;
+ if (is_X_used) {
+ if (is_Y_used) {
+ VP8LGetCombinedEntropyUnrefined(X, Y, length, &bit_entropy, &stats);
+ } else {
+ VP8LGetEntropyUnrefined(X, length, &bit_entropy, &stats);
+ }
+ } else {
+ if (is_Y_used) {
+ VP8LGetEntropyUnrefined(Y, length, &bit_entropy, &stats);
+ } else {
+ memset(&stats, 0, sizeof(stats));
+ stats.counts[0] = 1;
+ stats.streaks[0][length > 3] = length;
+ VP8LBitEntropyInit(&bit_entropy);
+ }
+ }
+
+ return BitsEntropyRefine(&bit_entropy) + FinalHuffmanCost(&stats);
+ }
+}
+
+// Estimates the Entropy + Huffman + other block overhead size cost.
+float VP8LHistogramEstimateBits(VP8LHistogram* const p) {
+ return
+ PopulationCost(p->literal_, VP8LHistogramNumCodes(p->palette_code_bits_),
+ NULL, &p->is_used_[0])
+ + PopulationCost(p->red_, NUM_LITERAL_CODES, NULL, &p->is_used_[1])
+ + PopulationCost(p->blue_, NUM_LITERAL_CODES, NULL, &p->is_used_[2])
+ + PopulationCost(p->alpha_, NUM_LITERAL_CODES, NULL, &p->is_used_[3])
+ + PopulationCost(p->distance_, NUM_DISTANCE_CODES, NULL, &p->is_used_[4])
+ + 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,
+ float cost_threshold, float* 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),
+ a->is_used_[0], b->is_used_[0], 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, a->is_used_[1],
+ b->is_used_[1], trivial_at_end);
+ if (*cost > cost_threshold) return 0;
+
+ *cost +=
+ GetCombinedEntropy(a->blue_, b->blue_, NUM_LITERAL_CODES, a->is_used_[2],
+ b->is_used_[2], trivial_at_end);
+ if (*cost > cost_threshold) return 0;
+
+ *cost +=
+ GetCombinedEntropy(a->alpha_, b->alpha_, NUM_LITERAL_CODES,
+ a->is_used_[3], b->is_used_[3], trivial_at_end);
+ if (*cost > cost_threshold) return 0;
+
+ *cost +=
+ GetCombinedEntropy(a->distance_, b->distance_, NUM_DISTANCE_CODES,
+ a->is_used_[4], b->is_used_[4], 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 float HistogramAddEval(const VP8LHistogram* const a,
+ const VP8LHistogram* const b,
+ VP8LHistogram* const out, float cost_threshold) {
+ float cost = 0;
+ const float 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 float HistogramAddThresh(const VP8LHistogram* const a,
+ const VP8LHistogram* const b,
+ float cost_threshold) {
+ float cost;
+ assert(a != NULL && b != NULL);
+ 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.
+typedef struct {
+ float literal_max_;
+ float literal_min_;
+ float red_max_;
+ float red_min_;
+ float blue_max_;
+ float blue_min_;
+} DominantCostRange;
+
+static void DominantCostRangeInit(DominantCostRange* const c) {
+ c->literal_max_ = 0.;
+ c->literal_min_ = MAX_BIT_COST;
+ c->red_max_ = 0.;
+ c->red_min_ = MAX_BIT_COST;
+ c->blue_max_ = 0.;
+ c->blue_min_ = MAX_BIT_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 float alpha_cost =
+ PopulationCost(h->alpha_, NUM_LITERAL_CODES, &alpha_sym, &h->is_used_[3]);
+ const float distance_cost =
+ PopulationCost(h->distance_, NUM_DISTANCE_CODES, NULL, &h->is_used_[4]) +
+ VP8LExtraCost(h->distance_, NUM_DISTANCE_CODES);
+ const int num_codes = VP8LHistogramNumCodes(h->palette_code_bits_);
+ h->literal_cost_ =
+ PopulationCost(h->literal_, num_codes, NULL, &h->is_used_[0]) +
+ VP8LExtraCost(h->literal_ + NUM_LITERAL_CODES, NUM_LENGTH_CODES);
+ h->red_cost_ =
+ PopulationCost(h->red_, NUM_LITERAL_CODES, &red_sym, &h->is_used_[1]);
+ h->blue_cost_ =
+ PopulationCost(h->blue_, NUM_LITERAL_CODES, &blue_sym, &h->is_used_[2]);
+ 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(float min, float max, float val) {
+ const float range = max - min;
+ if (range > 0.) {
+ const float 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);
+ VP8LHistogramSetClear(image_histo);
+ 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 const uint16_t kInvalidHistogramSymbol = (uint16_t)(-1);
+static void HistogramCopyAndAnalyze(VP8LHistogramSet* const orig_histo,
+ VP8LHistogramSet* const image_histo,
+ int* const num_used,
+ uint16_t* const histogram_symbols) {
+ int i, cluster_id;
+ int num_used_orig = *num_used;
+ VP8LHistogram** const orig_histograms = orig_histo->histograms;
+ VP8LHistogram** const histograms = image_histo->histograms;
+ assert(image_histo->max_size == orig_histo->max_size);
+ for (cluster_id = 0, i = 0; i < orig_histo->max_size; ++i) {
+ VP8LHistogram* const histo = orig_histograms[i];
+ UpdateHistogramCost(histo);
+
+ // Skip the histogram if it is completely empty, which can happen for tiles
+ // with no information (when they are skipped because of LZ77).
+ if (!histo->is_used_[0] && !histo->is_used_[1] && !histo->is_used_[2]
+ && !histo->is_used_[3] && !histo->is_used_[4]) {
+ // The first histogram is always used. If an histogram is empty, we set
+ // its id to be the same as the previous one: this will improve
+ // compressibility for later LZ77.
+ assert(i > 0);
+ HistogramSetRemoveHistogram(image_histo, i, num_used);
+ HistogramSetRemoveHistogram(orig_histo, i, &num_used_orig);
+ histogram_symbols[i] = kInvalidHistogramSymbol;
+ } else {
+ // Copy histograms from orig_histo[] to image_histo[].
+ HistogramCopy(histo, histograms[i]);
+ histogram_symbols[i] = cluster_id++;
+ assert(cluster_id <= image_histo->max_size);
+ }
+ }
+}
+
+// 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) {
+ if (histograms[i] == NULL) continue;
+ 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] is not set to a special value as its use will later be guarded
+ // by another (histograms[i] == NULL).
+ if (histograms[i] == NULL) continue;
+ bin_map[i] = GetHistoBinIndex(histograms[i], &cost_range, low_effort);
+ }
+}
+
+// Merges some histograms with same bin_id together if it's advantageous.
+// Sets the remaining histograms to NULL.
+static void HistogramCombineEntropyBin(
+ VP8LHistogramSet* const image_histo, int* num_used,
+ const uint16_t* const clusters, uint16_t* const cluster_mappings,
+ VP8LHistogram* cur_combo, const uint16_t* const bin_map, int num_bins,
+ float combine_cost_factor, int low_effort) {
+ VP8LHistogram** const histograms = image_histo->histograms;
+ int idx;
+ 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;
+ }
+
+ // By default, a cluster matches itself.
+ for (idx = 0; idx < *num_used; ++idx) cluster_mappings[idx] = idx;
+ for (idx = 0; idx < image_histo->size; ++idx) {
+ int bin_id, first;
+ if (histograms[idx] == NULL) continue;
+ bin_id = bin_map[idx];
+ first = bin_info[bin_id].first;
+ if (first == -1) {
+ bin_info[bin_id].first = idx;
+ } else if (low_effort) {
+ HistogramAdd(histograms[idx], histograms[first], histograms[first]);
+ HistogramSetRemoveHistogram(image_histo, idx, num_used);
+ cluster_mappings[clusters[idx]] = clusters[first];
+ } else {
+ // try to merge #idx into #first (both share the same bin_id)
+ const float bit_cost = histograms[idx]->bit_cost_;
+ const float bit_cost_thresh = -bit_cost * combine_cost_factor;
+ const float 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]);
+ HistogramSetRemoveHistogram(image_histo, idx, num_used);
+ cluster_mappings[clusters[idx]] = clusters[first];
+ } else {
+ ++bin_info[bin_id].num_combine_failures;
+ }
+ }
+ }
+ }
+ if (low_effort) {
+ // for low_effort case, update the final cost when everything is merged
+ for (idx = 0; idx < image_histo->size; ++idx) {
+ if (histograms[idx] == NULL) continue;
+ 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;
+ float cost_diff;
+ float cost_combo;
+} HistogramPair;
+
+typedef struct {
+ HistogramPair* queue;
+ int size;
+ int max_size;
+} HistoQueue;
+
+static int HistoQueueInit(HistoQueue* const histo_queue, const int max_size) {
+ histo_queue->size = 0;
+ histo_queue->max_size = max_size;
+ // 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;
+ }
+}
+
+// Update the cost diff and combo of a pair of histograms. This needs to be
+// called when the the histograms have been merged with a third one.
+static void HistoQueueUpdatePair(const VP8LHistogram* const h1,
+ const VP8LHistogram* const h2, float threshold,
+ HistogramPair* const pair) {
+ const float 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;
+}
+
+// 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 float HistoQueuePush(HistoQueue* const histo_queue,
+ VP8LHistogram** const histograms, int idx1,
+ int idx2, float threshold) {
+ const VP8LHistogram* h1;
+ const VP8LHistogram* h2;
+ HistogramPair pair;
+
+ // Stop here if the queue is full.
+ if (histo_queue->size == histo_queue->max_size) return 0.;
+ 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];
+
+ HistoQueueUpdatePair(h1, h2, threshold, &pair);
+
+ // Do not even consider the pair if it does not improve the entropy.
+ if (pair.cost_diff >= threshold) return 0.;
+
+ 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* const num_used) {
+ int ok = 0;
+ const int image_histo_size = image_histo->size;
+ int i, j;
+ VP8LHistogram** const histograms = image_histo->histograms;
+ // Priority queue of histogram pairs.
+ HistoQueue histo_queue;
+
+ // image_histo_size^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:
+ // - image_histo_size*(image_histo_size-1)/2 (the first two for loops)
+ // - image_histo_size - 1 in the last for loop at the first iteration of
+ // the while loop, image_histo_size - 2 at the second iteration ...
+ // therefore image_histo_size*(image_histo_size-1)/2 overall too
+ if (!HistoQueueInit(&histo_queue, image_histo_size * image_histo_size)) {
+ goto End;
+ }
+
+ for (i = 0; i < image_histo_size; ++i) {
+ if (image_histo->histograms[i] == NULL) continue;
+ for (j = i + 1; j < image_histo_size; ++j) {
+ // Initialize queue.
+ if (image_histo->histograms[j] == NULL) continue;
+ HistoQueuePush(&histo_queue, histograms, i, j, 0.);
+ }
+ }
+
+ while (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.
+ HistogramSetRemoveHistogram(image_histo, idx2, num_used);
+
+ // 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 (i == idx1 || image_histo->histograms[i] == NULL) continue;
+ HistoQueuePush(&histo_queue, image_histo->histograms, idx1, i, 0.);
+ }
+ }
+
+ ok = 1;
+
+ End:
+ 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 PairComparison(const void* idx1, const void* idx2) {
+ // To be used with bsearch: <0 when *idx1<*idx2, >0 if >, 0 when ==.
+ return (*(int*) idx1 - *(int*) idx2);
+}
+static int HistogramCombineStochastic(VP8LHistogramSet* const image_histo,
+ int* const num_used, int min_cluster_size,
+ int* const do_greedy) {
+ int j, iter;
+ uint32_t seed = 1;
+ int tries_with_no_success = 0;
+ const int outer_iters = *num_used;
+ const int num_tries_no_success = outer_iters / 2;
+ VP8LHistogram** const histograms = image_histo->histograms;
+ // Priority queue of histogram pairs. Its size of 'kHistoQueueSize'
+ // impacts the quality of the compression and the speed: the smaller the
+ // faster but the worse for the compression.
+ HistoQueue histo_queue;
+ const int kHistoQueueSize = 9;
+ int ok = 0;
+ // mapping from an index in image_histo with no NULL histogram to the full
+ // blown image_histo.
+ int* mappings;
+
+ if (*num_used < min_cluster_size) {
+ *do_greedy = 1;
+ return 1;
+ }
+
+ mappings = (int*) WebPSafeMalloc(*num_used, sizeof(*mappings));
+ if (mappings == NULL) return 0;
+ if (!HistoQueueInit(&histo_queue, kHistoQueueSize)) goto End;
+ // Fill the initial mapping.
+ for (j = 0, iter = 0; iter < image_histo->size; ++iter) {
+ if (histograms[iter] == NULL) continue;
+ mappings[j++] = iter;
+ }
+ assert(j == *num_used);
+
+ // Collapse similar histograms in 'image_histo'.
+ for (iter = 0;
+ iter < outer_iters && *num_used >= min_cluster_size &&
+ ++tries_with_no_success < num_tries_no_success;
+ ++iter) {
+ int* mapping_index;
+ float best_cost =
+ (histo_queue.size == 0) ? 0.f : histo_queue.queue[0].cost_diff;
+ int best_idx1 = -1, best_idx2 = 1;
+ const uint32_t rand_range = (*num_used - 1) * (*num_used);
+ // (*num_used) / 2 was chosen empirically. Less means faster but worse
+ // compression.
+ const int num_tries = (*num_used) / 2;
+
+ // Pick random samples.
+ for (j = 0; *num_used >= 2 && j < num_tries; ++j) {
+ float curr_cost;
+ // Choose two different histograms at random and try to combine them.
+ const uint32_t tmp = MyRand(&seed) % rand_range;
+ uint32_t idx1 = tmp / (*num_used - 1);
+ uint32_t idx2 = tmp % (*num_used - 1);
+ if (idx2 >= idx1) ++idx2;
+ idx1 = mappings[idx1];
+ idx2 = mappings[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;
+
+ // Get the best histograms.
+ best_idx1 = histo_queue.queue[0].idx1;
+ best_idx2 = histo_queue.queue[0].idx2;
+ assert(best_idx1 < best_idx2);
+ // Pop best_idx2 from mappings.
+ mapping_index = (int*) bsearch(&best_idx2, mappings, *num_used,
+ sizeof(best_idx2), &PairComparison);
+ assert(mapping_index != NULL);
+ memmove(mapping_index, mapping_index + 1, sizeof(*mapping_index) *
+ ((*num_used) - (mapping_index - mappings) - 1));
+ // Merge the histograms and remove best_idx2 from the queue.
+ HistogramAdd(histograms[best_idx2], histograms[best_idx1],
+ histograms[best_idx1]);
+ histograms[best_idx1]->bit_cost_ = histo_queue.queue[0].cost_combo;
+ HistogramSetRemoveHistogram(image_histo, best_idx2, num_used);
+ // 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;
+ }
+ // 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.
+ HistoQueueUpdatePair(histograms[p->idx1], histograms[p->idx2], 0., p);
+ if (p->cost_diff >= 0.) {
+ HistoQueuePopPair(&histo_queue, p);
+ continue;
+ }
+ }
+ HistoQueueUpdateHead(&histo_queue, p);
+ ++j;
+ }
+ tries_with_no_success = 0;
+ }
+ *do_greedy = (*num_used <= min_cluster_size);
+ ok = 1;
+
+ End:
+ HistoQueueClear(&histo_queue);
+ WebPSafeFree(mappings);
+ return ok;
+}
+
+// -----------------------------------------------------------------------------
+// Histogram refinement
+
+// Find the best 'out' histogram for each of the 'in' histograms.
+// At call-time, 'out' contains the histograms of the clusters.
+// Note: we assume that out[]->bit_cost_ is already up-to-date.
+static void HistogramRemap(const VP8LHistogramSet* const in,
+ 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 = out->max_size;
+ const int out_size = out->size;
+ if (out_size > 1) {
+ for (i = 0; i < in_size; ++i) {
+ int best_out = 0;
+ float best_bits = MAX_BIT_COST;
+ int k;
+ if (in_histo[i] == NULL) {
+ // Arbitrarily set to the previous value if unused to help future LZ77.
+ symbols[i] = symbols[i - 1];
+ continue;
+ }
+ for (k = 0; k < out_size; ++k) {
+ float cur_bits;
+ 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.
+ VP8LHistogramSetClear(out);
+ out->size = out_size;
+
+ for (i = 0; i < in_size; ++i) {
+ int idx;
+ if (in_histo[i] == NULL) continue;
+ idx = symbols[i];
+ HistogramAdd(in_histo[i], out_histo[idx], out_histo[idx]);
+ }
+}
+
+static float GetCombineCostFactor(int histo_size, int quality) {
+ float combine_cost_factor = 0.16f;
+ if (quality < 90) {
+ if (histo_size > 256) combine_cost_factor /= 2.f;
+ if (histo_size > 512) combine_cost_factor /= 2.f;
+ if (histo_size > 1024) combine_cost_factor /= 2.f;
+ if (quality <= 50) combine_cost_factor /= 2.f;
+ }
+ return combine_cost_factor;
+}
+
+// Given a HistogramSet 'set', the mapping of clusters 'cluster_mapping' and the
+// current assignment of the cells in 'symbols', merge the clusters and
+// assign the smallest possible clusters values.
+static void OptimizeHistogramSymbols(const VP8LHistogramSet* const set,
+ uint16_t* const cluster_mappings,
+ int num_clusters,
+ uint16_t* const cluster_mappings_tmp,
+ uint16_t* const symbols) {
+ int i, cluster_max;
+ int do_continue = 1;
+ // First, assign the lowest cluster to each pixel.
+ while (do_continue) {
+ do_continue = 0;
+ for (i = 0; i < num_clusters; ++i) {
+ int k;
+ k = cluster_mappings[i];
+ while (k != cluster_mappings[k]) {
+ cluster_mappings[k] = cluster_mappings[cluster_mappings[k]];
+ k = cluster_mappings[k];
+ }
+ if (k != cluster_mappings[i]) {
+ do_continue = 1;
+ cluster_mappings[i] = k;
+ }
+ }
+ }
+ // Create a mapping from a cluster id to its minimal version.
+ cluster_max = 0;
+ memset(cluster_mappings_tmp, 0,
+ set->max_size * sizeof(*cluster_mappings_tmp));
+ assert(cluster_mappings[0] == 0);
+ // Re-map the ids.
+ for (i = 0; i < set->max_size; ++i) {
+ int cluster;
+ if (symbols[i] == kInvalidHistogramSymbol) continue;
+ cluster = cluster_mappings[symbols[i]];
+ assert(symbols[i] < num_clusters);
+ if (cluster > 0 && cluster_mappings_tmp[cluster] == 0) {
+ ++cluster_max;
+ cluster_mappings_tmp[cluster] = cluster_max;
+ }
+ symbols[i] = cluster_mappings_tmp[cluster];
+ }
+
+ // Make sure all cluster values are used.
+ cluster_max = 0;
+ for (i = 0; i < set->max_size; ++i) {
+ if (symbols[i] == kInvalidHistogramSymbol) continue;
+ if (symbols[i] <= cluster_max) continue;
+ ++cluster_max;
+ assert(symbols[i] == cluster_max);
+ }
+}
+
+static void RemoveEmptyHistograms(VP8LHistogramSet* const image_histo) {
+ uint32_t size;
+ int i;
+ for (i = 0, size = 0; i < image_histo->size; ++i) {
+ if (image_histo->histograms[i] == NULL) continue;
+ image_histo->histograms[size++] = image_histo->histograms[i];
+ }
+ image_histo->size = size;
+}
+
+int VP8LGetHistoImageSymbols(int xsize, int ysize,
+ const VP8LBackwardRefs* const refs, int quality,
+ int low_effort, int histogram_bits, int cache_bits,
+ VP8LHistogramSet* const image_histo,
+ VP8LHistogram* const tmp_histo,
+ uint16_t* const histogram_symbols,
+ const WebPPicture* const pic, int percent_range,
+ int* const percent) {
+ const int histo_xsize =
+ histogram_bits ? VP8LSubSampleSize(xsize, histogram_bits) : 1;
+ const int histo_ysize =
+ histogram_bits ? VP8LSubSampleSize(ysize, histogram_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;
+ int entropy_combine;
+ uint16_t* const map_tmp =
+ WebPSafeMalloc(2 * image_histo_raw_size, sizeof(map_tmp));
+ uint16_t* const cluster_mappings = map_tmp + image_histo_raw_size;
+ int num_used = image_histo_raw_size;
+ if (orig_histo == NULL || map_tmp == NULL) {
+ WebPEncodingSetError(pic, VP8_ENC_ERROR_OUT_OF_MEMORY);
+ goto Error;
+ }
+
+ // Construct the histograms from backward references.
+ HistogramBuild(xsize, histogram_bits, refs, orig_histo);
+ // Copies the histograms and computes its bit_cost.
+ // histogram_symbols is optimized
+ HistogramCopyAndAnalyze(orig_histo, image_histo, &num_used,
+ histogram_symbols);
+
+ entropy_combine =
+ (num_used > entropy_combine_num_bins * 2) && (quality < 100);
+
+ if (entropy_combine) {
+ uint16_t* const bin_map = map_tmp;
+ const float combine_cost_factor =
+ GetCombineCostFactor(image_histo_raw_size, quality);
+ const uint32_t num_clusters = num_used;
+
+ HistogramAnalyzeEntropyBin(image_histo, bin_map, low_effort);
+ // Collapse histograms with similar entropy.
+ HistogramCombineEntropyBin(
+ image_histo, &num_used, histogram_symbols, cluster_mappings, tmp_histo,
+ bin_map, entropy_combine_num_bins, combine_cost_factor, low_effort);
+ OptimizeHistogramSymbols(image_histo, cluster_mappings, num_clusters,
+ map_tmp, histogram_symbols);
+ }
+
+ // 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, &num_used, threshold_size,
+ &do_greedy)) {
+ WebPEncodingSetError(pic, VP8_ENC_ERROR_OUT_OF_MEMORY);
+ goto Error;
+ }
+ if (do_greedy) {
+ RemoveEmptyHistograms(image_histo);
+ if (!HistogramCombineGreedy(image_histo, &num_used)) {
+ WebPEncodingSetError(pic, VP8_ENC_ERROR_OUT_OF_MEMORY);
+ goto Error;
+ }
+ }
+ }
+
+ // Find the optimal map from original histograms to the final ones.
+ RemoveEmptyHistograms(image_histo);
+ HistogramRemap(orig_histo, image_histo, histogram_symbols);
+
+ if (!WebPReportProgress(pic, *percent + percent_range, percent)) {
+ goto Error;
+ }
+
+ Error:
+ VP8LFreeHistogramSet(orig_histo);
+ WebPSafeFree(map_tmp);
+ return (pic->error_code == VP8_ENC_OK);
+}