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a4183d94c7
libwebp/src/enc/histogram_enc.c
Vincent Rabaud a4183d94c7 Remove the computation of ExtraCost when comparing histograms 
Entropy clustering merges symbol histograms to reduce the overall
entropy. The cost of 2 added histograms is compared to the 2 costs
of the individual histograms and if it is smaller, a merge is done.

Except for some symbols (distance and length), the computed cost is
 the real final cost based on the histogram, and some constant cost
(independent from the probabilities of the symbols and hence the
merge) because the symbol is encode as Golomb.

This constant cost is useless and can be removed.

Change-Id: I6271e8c0e4111cdeff544cbdb7dec3c67be5309c
2025-03-28 15:00:41 +01:00

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// 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 <string.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"
// 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
// Return the size of the histogram for a given cache_bits.
static int GetHistogramSize(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;
}
static void HistogramClear(VP8LHistogram* const p) {
uint32_t* const literal = p->literal_;
const int cache_bits = p->palette_code_bits_;
const int histo_size = GetHistogramSize(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 = GetHistogramSize(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_));
}
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 = GetHistogramSize(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 = GetHistogramSize(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 = GetHistogramSize(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 uint64_t BitsEntropyRefine(const VP8LBitEntropy* entropy) {
uint64_t 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 DivRound(99 * ((uint64_t)entropy->sum << LOG_2_PRECISION_BITS) +
entropy->entropy,
100);
}
// 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 = 950;
} else {
mix = 700; // nonzeros == 4.
}
} else {
mix = 627;
}
{
uint64_t min_limit = (uint64_t)(2 * entropy->sum - entropy->max_val)
<< LOG_2_PRECISION_BITS;
min_limit =
DivRound(mix * min_limit + (1000 - mix) * entropy->entropy, 1000);
return (entropy->entropy < min_limit) ? min_limit : entropy->entropy;
}
}
uint64_t VP8LBitsEntropy(const uint32_t* const array, int n) {
VP8LBitEntropy entropy;
VP8LBitsEntropyUnrefined(array, n, &entropy);
return BitsEntropyRefine(&entropy);
}
static uint64_t InitialHuffmanCost(void) {
// Small bias because Huffman code length is typically not stored in
// full length.
static const uint64_t kHuffmanCodeOfHuffmanCodeSize = CODE_LENGTH_CODES * 3;
// Subtract a bias of 9.1.
return (kHuffmanCodeOfHuffmanCodeSize << LOG_2_PRECISION_BITS) -
DivRound(91ll << LOG_2_PRECISION_BITS, 10);
}
// Finalize the Huffman cost based on streak numbers and length type (<3 or >=3)
static uint64_t FinalHuffmanCost(const VP8LStreaks* const stats) {
// The constants in this function are empirical and got rounded from
// their original values in 1/8 when switched to 1/1024.
uint64_t retval = InitialHuffmanCost();
// Second coefficient: Many zeros in the histogram are covered efficiently
// by a run-length encode. Originally 2/8.
uint32_t retval_extra = stats->counts[0] * 1600 + 240 * stats->streaks[0][1];
// Second coefficient: Constant values are encoded less efficiently, but still
// RLE'ed. Originally 6/8.
retval_extra += stats->counts[1] * 2640 + 720 * stats->streaks[1][1];
// 0s are usually encoded more efficiently than non-0s.
// Originally 15/8.
retval_extra += 1840 * stats->streaks[0][0];
// Originally 26/8.
retval_extra += 3360 * stats->streaks[1][0];
return retval + ((uint64_t)retval_extra << (LOG_2_PRECISION_BITS - 10));
}
// Get the symbol entropy for the distribution 'population'.
// Set 'trivial_sym', if there's only one symbol present in the distribution.
static uint64_t 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 uint64_t 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.
uint64_t 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]) +
((uint64_t)(VP8LExtraCost(p->literal_ + NUM_LITERAL_CODES,
NUM_LENGTH_CODES) +
VP8LExtraCost(p->distance_, NUM_DISTANCE_CODES))
<< LOG_2_PRECISION_BITS);
}
// -----------------------------------------------------------------------------
// Various histogram combine/cost-eval functions
// Set a + b in b, saturating at WEBP_INT64_MAX.
static WEBP_INLINE void SaturateAdd(uint64_t a, int64_t* b) {
if (*b < 0 || (int64_t)a <= WEBP_INT64_MAX - *b) {
*b += (int64_t)a;
} else {
*b = WEBP_INT64_MAX;
}
}
// Returns 1 if the cost of the combined histogram is less than the threshold.
// Otherwise returns 0 and the cost is invalid due to early bail-out.
WEBP_NODISCARD static int GetCombinedHistogramEntropy(
const VP8LHistogram* const a, const VP8LHistogram* const b,
int64_t cost_threshold_in, uint64_t* cost) {
const int palette_code_bits = a->palette_code_bits_;
int trivial_at_end = 0;
const uint64_t cost_threshold = (uint64_t)cost_threshold_in;
assert(a->palette_code_bits_ == b->palette_code_bits_);
if (cost_threshold_in <= 0) return 0;
*cost = GetCombinedEntropy(a->literal_, b->literal_,
VP8LHistogramNumCodes(palette_code_bits),
a->is_used_[0], b->is_used_[0], 0);
// No need to add the extra cost as it is a constant that does not influence
// the histograms.
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);
// No need to add the extra cost as it is a constant that does not influence
// the histograms.
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.
// Returns 1 if the cost is less than the threshold.
// Otherwise returns 0 and the cost is invalid due to early bail-out.
WEBP_NODISCARD static int HistogramAddEval(const VP8LHistogram* const a,
const VP8LHistogram* const b,
VP8LHistogram* const out,
int64_t cost_threshold) {
uint64_t cost;
const uint64_t sum_cost = a->bit_cost_ + b->bit_cost_;
SaturateAdd(sum_cost, &cost_threshold);
if (!GetCombinedHistogramEntropy(a, b, cost_threshold, &cost)) return 0;
HistogramAdd(a, b, out);
out->bit_cost_ = cost;
out->palette_code_bits_ = a->palette_code_bits_;
return 1;
}
// 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.
// Returns 1 if the cost is less than the threshold.
// Otherwise returns 0 and the cost is invalid due to early bail-out.
WEBP_NODISCARD static int HistogramAddThresh(const VP8LHistogram* const a,
const VP8LHistogram* const b,
int64_t cost_threshold,
int64_t* cost_out) {
uint64_t cost;
assert(a != NULL && b != NULL);
SaturateAdd(a->bit_cost_, &cost_threshold);
if (!GetCombinedHistogramEntropy(a, b, cost_threshold, &cost)) return 0;
*cost_out = (int64_t)cost - (int64_t)a->bit_cost_;
return 1;
}
// -----------------------------------------------------------------------------
// The structure to keep track of cost range for the three dominant entropy
// symbols.
typedef struct {
uint64_t literal_max_;
uint64_t literal_min_;
uint64_t red_max_;
uint64_t red_min_;
uint64_t blue_max_;
uint64_t blue_min_;
} DominantCostRange;
static void DominantCostRangeInit(DominantCostRange* const c) {
c->literal_max_ = 0;
c->literal_min_ = WEBP_UINT64_MAX;
c->red_max_ = 0;
c->red_min_ = WEBP_UINT64_MAX;
c->blue_max_ = 0;
c->blue_min_ = WEBP_UINT64_MAX;
}
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 uint64_t alpha_cost =
PopulationCost(h->alpha_, NUM_LITERAL_CODES, &alpha_sym, &h->is_used_[3]);
// No need to add the extra cost as it is a constant that does not influence
// the histograms.
const uint64_t distance_cost =
PopulationCost(h->distance_, NUM_DISTANCE_CODES, NULL, &h->is_used_[4]);
const int num_codes = VP8LHistogramNumCodes(h->palette_code_bits_);
h->literal_cost_ =
PopulationCost(h->literal_, num_codes, NULL, &h->is_used_[0]);
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(uint64_t min, uint64_t max, uint64_t val) {
const uint64_t range = max - min;
if (range > 0) {
const uint64_t 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 uint32_t kInvalidHistogramSymbol = (uint32_t)(-1);
static void HistogramCopyAndAnalyze(VP8LHistogramSet* const orig_histo,
VP8LHistogramSet* const image_histo,
int* const num_used,
uint32_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.
// 'combine_cost_factor' has to be divided by 100.
static void HistogramCombineEntropyBin(
VP8LHistogramSet* const image_histo, int* num_used,
const uint32_t* const clusters, uint16_t* const cluster_mappings,
VP8LHistogram* cur_combo, const uint16_t* const bin_map, int num_bins,
int32_t 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 uint64_t bit_cost = histograms[idx]->bit_cost_;
const int64_t bit_cost_thresh =
-DivRound((int64_t)bit_cost * combine_cost_factor, 100);
if (HistogramAddEval(histograms[first], histograms[idx], cur_combo,
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;
int64_t cost_diff;
uint64_t 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 histograms have been merged with a third one.
// Returns 1 if the cost diff is less than the threshold.
// Otherwise returns 0 and the cost is invalid due to early bail-out.
WEBP_NODISCARD static int HistoQueueUpdatePair(const VP8LHistogram* const h1,
const VP8LHistogram* const h2,
int64_t cost_threshold,
HistogramPair* const pair) {
const int64_t sum_cost = h1->bit_cost_ + h2->bit_cost_;
SaturateAdd(sum_cost, &cost_threshold);
if (!GetCombinedHistogramEntropy(h1, h2, cost_threshold, &pair->cost_combo)) {
return 0;
}
pair->cost_diff = (int64_t)pair->cost_combo - sum_cost;
return 1;
}
// 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 int64_t HistoQueuePush(HistoQueue* const histo_queue,
VP8LHistogram** const histograms, int idx1,
int idx2, int64_t 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];
// Do not even consider the pair if it does not improve the entropy.
if (!HistoQueueUpdatePair(h1, h2, threshold, &pair)) 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;
int64_t best_cost =
(histo_queue.size == 0) ? 0 : 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) {
int64_t 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.
if (!HistoQueueUpdatePair(histograms[p->idx1], histograms[p->idx2], 0,
p)) {
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,
uint32_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;
int64_t best_bits = WEBP_INT64_MAX;
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) {
int64_t cur_bits;
if (HistogramAddThresh(out_histo[k], in_histo[i], best_bits,
&cur_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 int32_t GetCombineCostFactor(int histo_size, int quality) {
int32_t combine_cost_factor = 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;
}
// 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,
uint32_t num_clusters,
uint16_t* const cluster_mappings_tmp,
uint32_t* const symbols) {
uint32_t 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 < (uint32_t)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 < (uint32_t)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,
uint32_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 =
(uint16_t*)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 int32_t 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) {
// cubic ramp between 1 and MAX_HISTO_GREEDY:
const int threshold_size =
(int)(1 + DivRound(quality * quality * quality * (MAX_HISTO_GREEDY - 1),
100 * 100 * 100));
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);
}
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