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fd198f7370
libwebp/src/enc/histogram_enc.c
Vincent Rabaud 485ff86fbb Fix pair update in stochastic entropy merging. 
The old code simply did not make sense.
The effect is that the pair would be popped from the
queue no matter what; as the queue is small, it does
not matter that much on the results.
But it will matter for a later CL.

Change-Id: If50c9fa9d7f3ac3c48bb7336d81479287d4944c4
2018-11-07 00:33:14 +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 <math.h>
#include "src/enc/backward_references_enc.h"
#include "src/enc/histogram_enc.h"
#include "src/dsp/lossless.h"
#include "src/dsp/lossless_common.h"
#include "src/utils/utils.h"
#define MAX_COST 1.e38
// Number of partitions for the three dominant (literal, red and blue) symbol
// costs.
#define NUM_PARTITIONS 4
// The size of the bin-hash corresponding to the three dominant costs.
#define BIN_SIZE (NUM_PARTITIONS * NUM_PARTITIONS * NUM_PARTITIONS)
// Maximum number of histograms allowed in greedy combining algorithm.
#define MAX_HISTO_GREEDY 100
static void HistogramClear(VP8LHistogram* const p) {
uint32_t* const literal = p->literal_;
const int cache_bits = p->palette_code_bits_;
const int histo_size = VP8LGetHistogramSize(cache_bits);
memset(p, 0, histo_size);
p->palette_code_bits_ = cache_bits;
p->literal_ = literal;
}
// Swap two histogram pointers.
static void HistogramSwap(VP8LHistogram** const A, VP8LHistogram** const B) {
VP8LHistogram* const tmp = *A;
*A = *B;
*B = tmp;
}
static void HistogramCopy(const VP8LHistogram* const src,
VP8LHistogram* const dst) {
uint32_t* const dst_literal = dst->literal_;
const int dst_cache_bits = dst->palette_code_bits_;
const int 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->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;
}
}
// -----------------------------------------------------------------------------
void VP8LHistogramAddSinglePixOrCopy(VP8LHistogram* const histo,
const PixOrCopy* const v,
int (*const distance_modifier)(int, int),
int distance_modifier_arg0) {
if (PixOrCopyIsLiteral(v)) {
++histo->alpha_[PixOrCopyLiteral(v, 3)];
++histo->red_[PixOrCopyLiteral(v, 2)];
++histo->literal_[PixOrCopyLiteral(v, 1)];
++histo->blue_[PixOrCopyLiteral(v, 0)];
} else if (PixOrCopyIsCacheIdx(v)) {
const int literal_ix =
NUM_LITERAL_CODES + NUM_LENGTH_CODES + PixOrCopyCacheIdx(v);
++histo->literal_[literal_ix];
} else {
int code, extra_bits;
VP8LPrefixEncodeBits(PixOrCopyLength(v), &code, &extra_bits);
++histo->literal_[NUM_LITERAL_CODES + code];
if (distance_modifier == NULL) {
VP8LPrefixEncodeBits(PixOrCopyDistance(v), &code, &extra_bits);
} else {
VP8LPrefixEncodeBits(
distance_modifier(distance_modifier_arg0, PixOrCopyDistance(v)),
&code, &extra_bits);
}
++histo->distance_[code];
}
}
// -----------------------------------------------------------------------------
// Entropy-related functions.
static WEBP_INLINE double BitsEntropyRefine(const VP8LBitEntropy* entropy) {
double mix;
if (entropy->nonzeros < 5) {
if (entropy->nonzeros <= 1) {
return 0;
}
// Two symbols, they will be 0 and 1 in a Huffman code.
// Let's mix in a bit of entropy to favor good clustering when
// distributions of these are combined.
if (entropy->nonzeros == 2) {
return 0.99 * entropy->sum + 0.01 * entropy->entropy;
}
// No matter what the entropy says, we cannot be better than min_limit
// with Huffman coding. I am mixing a bit of entropy into the
// min_limit since it produces much better (~0.5 %) compression results
// perhaps because of better entropy clustering.
if (entropy->nonzeros == 3) {
mix = 0.95;
} else {
mix = 0.7; // nonzeros == 4.
}
} else {
mix = 0.627;
}
{
double min_limit = 2 * entropy->sum - entropy->max_val;
min_limit = mix * min_limit + (1.0 - mix) * entropy->entropy;
return (entropy->entropy < min_limit) ? min_limit : entropy->entropy;
}
}
double VP8LBitsEntropy(const uint32_t* const array, int n) {
VP8LBitEntropy entropy;
VP8LBitsEntropyUnrefined(array, n, &entropy);
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,
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 double 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.
double 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,
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),
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 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,
&h->is_used_[3]);
const double 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(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);
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 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;
image_histo->size = 0;
for (i = 0; i < histo_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]) {
continue;
}
// Copy histograms from orig_histo[] to image_histo[].
HistogramCopy(histo, histograms[image_histo->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) {
UpdateDominantCostRange(histograms[i], &cost_range);
}
// bin-hash histograms on three of the dominant (literal, red and blue)
// symbol costs and store the resulting bin_id for each histogram.
for (i = 0; i < histo_size; ++i) {
bin_map[i] = GetHistoBinIndex(histograms[i], &cost_range, low_effort);
}
}
// Compact image_histo[] by merging some histograms with same bin_id together if
// it's advantageous.
static void HistogramCombineEntropyBin(VP8LHistogramSet* const image_histo,
VP8LHistogram* cur_combo,
const uint16_t* const bin_map,
int bin_map_size, int num_bins,
double combine_cost_factor,
int low_effort) {
VP8LHistogram** const histograms = image_histo->histograms;
int idx;
// Work in-place: processed histograms are put at the beginning of
// image_histo[]. At the end, we just have to truncate the array.
int size = 0;
struct {
int16_t first; // position of the histogram that accumulates all
// histograms with the same bin_id
uint16_t num_combine_failures; // number of combine failures per bin_id
} bin_info[BIN_SIZE];
assert(num_bins <= BIN_SIZE);
for (idx = 0; idx < num_bins; ++idx) {
bin_info[idx].first = -1;
bin_info[idx].num_combine_failures = 0;
}
for (idx = 0; idx < bin_map_size; ++idx) {
const int bin_id = bin_map[idx];
const int first = bin_info[bin_id].first;
assert(size <= idx);
if (first == -1) {
// just move histogram #idx to its final position
histograms[size] = histograms[idx];
bin_info[bin_id].first = size++;
} else if (low_effort) {
HistogramAdd(histograms[idx], histograms[first], histograms[first]);
} else {
// try to merge #idx into #first (both share the same bin_id)
const double bit_cost = histograms[idx]->bit_cost_;
const double bit_cost_thresh = -bit_cost * combine_cost_factor;
const double curr_cost_diff =
HistogramAddEval(histograms[first], histograms[idx],
cur_combo, bit_cost_thresh);
if (curr_cost_diff < bit_cost_thresh) {
// Try to merge two histograms only if the combo is a trivial one or
// the two candidate histograms are already non-trivial.
// For some images, 'try_combine' turns out to be false for a lot of
// histogram pairs. In that case, we fallback to combining
// histograms as usual to avoid increasing the header size.
const int try_combine =
(cur_combo->trivial_symbol_ != VP8L_NON_TRIVIAL_SYM) ||
((histograms[idx]->trivial_symbol_ == VP8L_NON_TRIVIAL_SYM) &&
(histograms[first]->trivial_symbol_ == VP8L_NON_TRIVIAL_SYM));
const int max_combine_failures = 32;
if (try_combine ||
bin_info[bin_id].num_combine_failures >= max_combine_failures) {
// move the (better) merged histogram to its final slot
HistogramSwap(&cur_combo, &histograms[first]);
} else {
histograms[size++] = histograms[idx];
++bin_info[bin_id].num_combine_failures;
}
} else {
histograms[size++] = histograms[idx];
}
}
}
image_histo->size = size;
if (low_effort) {
// for low_effort case, update the final cost when everything is merged
for (idx = 0; idx < size; ++idx) {
UpdateHistogramCost(histograms[idx]);
}
}
}
// Implement a Lehmer random number generator with a multiplicative constant of
// 48271 and a modulo constant of 2^31 - 1.
static uint32_t MyRand(uint32_t* const seed) {
*seed = (uint32_t)(((uint64_t)(*seed) * 48271u) % 2147483647u);
assert(*seed > 0);
return *seed;
}
// -----------------------------------------------------------------------------
// Histogram pairs priority queue
// Pair of histograms. Negative idx1 value means that pair is out-of-date.
typedef struct {
int idx1;
int idx2;
double cost_diff;
double cost_combo;
} HistogramPair;
typedef struct {
HistogramPair* queue;
int size;
int max_size;
} HistoQueue;
static int HistoQueueInit(HistoQueue* const histo_queue, const int max_index) {
histo_queue->size = 0;
// max_index^2 for the queue size is safe. If you look at
// HistogramCombineGreedy, and imagine that UpdateQueueFront always pushes
// data to the queue, you insert at most:
// - max_index*(max_index-1)/2 (the first two for loops)
// - max_index - 1 in the last for loop at the first iteration of the while
// loop, max_index - 2 at the second iteration ... therefore
// max_index*(max_index-1)/2 overall too
histo_queue->max_size = max_index * max_index;
// We allocate max_size + 1 because the last element at index "size" is
// used as temporary data (and it could be up to max_size).
histo_queue->queue = (HistogramPair*)WebPSafeMalloc(
histo_queue->max_size + 1, sizeof(*histo_queue->queue));
return histo_queue->queue != NULL;
}
static void HistoQueueClear(HistoQueue* const histo_queue) {
assert(histo_queue != NULL);
WebPSafeFree(histo_queue->queue);
histo_queue->size = 0;
histo_queue->max_size = 0;
}
// Pop a specific pair in the queue by replacing it with the last one
// and shrinking the queue.
static void HistoQueuePopPair(HistoQueue* const histo_queue,
HistogramPair* const pair) {
assert(pair >= histo_queue->queue &&
pair < (histo_queue->queue + histo_queue->size));
assert(histo_queue->size > 0);
*pair = histo_queue->queue[histo_queue->size - 1];
--histo_queue->size;
}
// Check whether a pair in the queue should be updated as head or not.
static void HistoQueueUpdateHead(HistoQueue* const histo_queue,
HistogramPair* const pair) {
assert(pair->cost_diff < 0.);
assert(pair >= histo_queue->queue &&
pair < (histo_queue->queue + histo_queue->size));
assert(histo_queue->size > 0);
if (pair->cost_diff < histo_queue->queue[0].cost_diff) {
// Replace the best pair.
const HistogramPair tmp = histo_queue->queue[0];
histo_queue->queue[0] = *pair;
*pair = tmp;
}
}
// 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,
double threshold,
HistogramPair* const pair) {
const double 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 double HistoQueuePush(HistoQueue* const histo_queue,
VP8LHistogram** const histograms, int idx1,
int idx2, double threshold) {
const VP8LHistogram* h1;
const VP8LHistogram* h2;
HistogramPair pair;
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.;
// We cannot add more elements than the capacity.
assert(histo_queue->size < histo_queue->max_size);
histo_queue->queue[histo_queue->size++] = pair;
HistoQueueUpdateHead(histo_queue, &histo_queue->queue[histo_queue->size - 1]);
return pair.cost_diff;
}
// -----------------------------------------------------------------------------
// Combines histograms by continuously choosing the one with the highest cost
// reduction.
static int HistogramCombineGreedy(VP8LHistogramSet* const image_histo) {
int ok = 0;
int image_histo_size = image_histo->size;
int i, j;
VP8LHistogram** const histograms = image_histo->histograms;
// Indexes of remaining histograms.
int* const clusters =
(int*)WebPSafeMalloc(image_histo_size, sizeof(*clusters));
// Priority queue of histogram pairs.
HistoQueue histo_queue;
if (!HistoQueueInit(&histo_queue, image_histo_size) || clusters == NULL) {
goto End;
}
for (i = 0; i < image_histo_size; ++i) {
// Initialize clusters indexes.
clusters[i] = i;
for (j = i + 1; j < image_histo_size; ++j) {
// Initialize positions array.
HistoQueuePush(&histo_queue, histograms, i, j, 0.);
}
}
while (image_histo_size > 1 && histo_queue.size > 0) {
const int idx1 = histo_queue.queue[0].idx1;
const int idx2 = histo_queue.queue[0].idx2;
HistogramAdd(histograms[idx2], histograms[idx1], histograms[idx1]);
histograms[idx1]->bit_cost_ = histo_queue.queue[0].cost_combo;
// Remove merged histogram.
for (i = 0; i + 1 < image_histo_size; ++i) {
if (clusters[i] >= idx2) {
clusters[i] = clusters[i + 1];
}
}
--image_histo_size;
// Remove pairs intersecting the just combined best pair.
for (i = 0; i < histo_queue.size;) {
HistogramPair* const p = histo_queue.queue + i;
if (p->idx1 == idx1 || p->idx2 == idx1 ||
p->idx1 == idx2 || p->idx2 == idx2) {
HistoQueuePopPair(&histo_queue, p);
} else {
HistoQueueUpdateHead(&histo_queue, p);
++i;
}
}
// Push new pairs formed with combined histogram to the queue.
for (i = 0; i < image_histo_size; ++i) {
if (clusters[i] != idx1) {
HistoQueuePush(&histo_queue, histograms, idx1, clusters[i], 0.);
}
}
}
// Move remaining histograms to the beginning of the array.
for (i = 0; i < image_histo_size; ++i) {
if (i != clusters[i]) { // swap the two histograms
HistogramSwap(&histograms[i], &histograms[clusters[i]]);
}
}
image_histo->size = image_histo_size;
ok = 1;
End:
WebPSafeFree(clusters);
HistoQueueClear(&histo_queue);
return ok;
}
// Perform histogram aggregation using a stochastic approach.
// 'do_greedy' is set to 1 if a greedy approach needs to be performed
// afterwards, 0 otherwise.
static int HistogramCombineStochastic(VP8LHistogramSet* const image_histo,
int min_cluster_size,
int* const do_greedy) {
int iter;
uint32_t seed = 1;
int tries_with_no_success = 0;
int image_histo_size = image_histo->size;
const int outer_iters = image_histo_size;
const int num_tries_no_success = outer_iters / 2;
VP8LHistogram** const histograms = image_histo->histograms;
// Priority queue of histogram pairs. Its size of "kCostHeapSizeSqrt"^2
// impacts the quality of the compression and the speed: the smaller the
// faster but the worse for the compression.
HistoQueue histo_queue;
const int kHistoQueueSizeSqrt = 3;
int ok = 0;
if (!HistoQueueInit(&histo_queue, kHistoQueueSizeSqrt)) {
goto End;
}
// Collapse similar histograms in 'image_histo'.
++min_cluster_size;
for (iter = 0; iter < outer_iters && image_histo_size >= min_cluster_size &&
++tries_with_no_success < num_tries_no_success;
++iter) {
double best_cost =
(histo_queue.size == 0) ? 0. : histo_queue.queue[0].cost_diff;
int best_idx1 = -1, best_idx2 = 1;
int j;
const uint32_t rand_range = (image_histo_size - 1) * image_histo_size;
// image_histo_size / 2 was chosen empirically. Less means faster but worse
// compression.
const int num_tries = image_histo_size / 2;
for (j = 0; j < num_tries; ++j) {
double curr_cost;
// Choose two different histograms at random and try to combine them.
const uint32_t tmp = MyRand(&seed) % rand_range;
const uint32_t idx1 = tmp / (image_histo_size - 1);
uint32_t idx2 = tmp % (image_histo_size - 1);
if (idx2 >= idx1) ++idx2;
// Calculate cost reduction on combination.
curr_cost =
HistoQueuePush(&histo_queue, histograms, idx1, idx2, best_cost);
if (curr_cost < 0) { // found a better pair?
best_cost = curr_cost;
// Empty the queue if we reached full capacity.
if (histo_queue.size == histo_queue.max_size) break;
}
}
if (histo_queue.size == 0) continue;
// Merge the two best histograms.
best_idx1 = histo_queue.queue[0].idx1;
best_idx2 = histo_queue.queue[0].idx2;
assert(best_idx1 < best_idx2);
HistogramAddEval(histograms[best_idx1], histograms[best_idx2],
histograms[best_idx1], 0);
// Swap the best_idx2 histogram with the last one (which is now unused).
--image_histo_size;
if (best_idx2 != image_histo_size) {
HistogramSwap(&histograms[image_histo_size], &histograms[best_idx2]);
}
histograms[image_histo_size] = NULL;
// Parse the queue and update each pair that deals with best_idx1,
// best_idx2 or image_histo_size.
for (j = 0; j < histo_queue.size;) {
HistogramPair* const p = histo_queue.queue + j;
const int is_idx1_best = p->idx1 == best_idx1 || p->idx1 == best_idx2;
const int is_idx2_best = p->idx2 == best_idx1 || p->idx2 == best_idx2;
int do_eval = 0;
// The front pair could have been duplicated by a random pick so
// check for it all the time nevertheless.
if (is_idx1_best && is_idx2_best) {
HistoQueuePopPair(&histo_queue, p);
continue;
}
// Any pair containing one of the two best indices should only refer to
// best_idx1. Its cost should also be updated.
if (is_idx1_best) {
p->idx1 = best_idx1;
do_eval = 1;
} else if (is_idx2_best) {
p->idx2 = best_idx1;
do_eval = 1;
}
if (p->idx2 == image_histo_size) {
// No need to re-evaluate here as it does not involve a pair
// containing best_idx1 or best_idx2.
p->idx2 = best_idx2;
}
assert(p->idx2 < image_histo_size);
// Make sure the index order is respected.
if (p->idx1 > p->idx2) {
const int tmp = p->idx2;
p->idx2 = p->idx1;
p->idx1 = tmp;
}
if (do_eval) {
// Re-evaluate the cost of an updated pair.
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;
}
image_histo->size = image_histo_size;
*do_greedy = (image_histo->size <= min_cluster_size);
ok = 1;
End:
HistoQueueClear(&histo_queue);
return ok;
}
// -----------------------------------------------------------------------------
// Histogram refinement
// Find the best 'out' histogram for each of the 'in' histograms.
// Note: we assume that out[]->bit_cost_ is already up-to-date.
static void HistogramRemap(const VP8LHistogramSet* const in,
const VP8LHistogramSet* const out,
uint16_t* const symbols) {
int i;
VP8LHistogram** const in_histo = in->histograms;
VP8LHistogram** const out_histo = out->histograms;
const int in_size = in->size;
const int out_size = out->size;
if (out_size > 1) {
for (i = 0; i < in_size; ++i) {
int best_out = 0;
double best_bits = MAX_COST;
int k;
for (k = 0; k < out_size; ++k) {
const double cur_bits =
HistogramAddThresh(out_histo[k], in_histo[i], best_bits);
if (k == 0 || cur_bits < best_bits) {
best_bits = cur_bits;
best_out = k;
}
}
symbols[i] = best_out;
}
} else {
assert(out_size == 1);
for (i = 0; i < in_size; ++i) {
symbols[i] = 0;
}
}
// Recompute each out based on raw and symbols.
for (i = 0; i < out_size; ++i) {
HistogramClear(out_histo[i]);
}
for (i = 0; i < in_size; ++i) {
const int idx = symbols[i];
HistogramAdd(in_histo[i], out_histo[idx], out_histo[idx]);
}
}
static double GetCombineCostFactor(int histo_size, int quality) {
double combine_cost_factor = 0.16;
if (quality < 90) {
if (histo_size > 256) combine_cost_factor /= 2.;
if (histo_size > 512) combine_cost_factor /= 2.;
if (histo_size > 1024) combine_cost_factor /= 2.;
if (quality <= 50) combine_cost_factor /= 2.;
}
return combine_cost_factor;
}
int VP8LGetHistoImageSymbols(int xsize, int ysize,
const VP8LBackwardRefs* const refs,
int quality, int low_effort,
int histo_bits, int cache_bits,
VP8LHistogramSet* const image_histo,
VP8LHistogram* const tmp_histo,
uint16_t* const histogram_symbols) {
int ok = 0;
const int histo_xsize = histo_bits ? VP8LSubSampleSize(xsize, histo_bits) : 1;
const int histo_ysize = histo_bits ? VP8LSubSampleSize(ysize, histo_bits) : 1;
const int image_histo_raw_size = histo_xsize * histo_ysize;
VP8LHistogramSet* const orig_histo =
VP8LAllocateHistogramSet(image_histo_raw_size, cache_bits);
// Don't attempt linear bin-partition heuristic for
// histograms of small sizes (as bin_map will be very sparse) and
// maximum quality q==100 (to preserve the compression gains at that level).
const int entropy_combine_num_bins = low_effort ? NUM_PARTITIONS : BIN_SIZE;
int entropy_combine;
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);
entropy_combine =
(image_histo->size > entropy_combine_num_bins * 2) && (quality < 100);
if (entropy_combine) {
const int bin_map_size = image_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(image_histo, bin_map, low_effort);
// Collapse histograms with similar entropy.
HistogramCombineEntropyBin(image_histo, tmp_histo, bin_map, bin_map_size,
entropy_combine_num_bins, combine_cost_factor,
low_effort);
}
// Don't combine the histograms using stochastic and greedy heuristics for
// low-effort compression mode.
if (!low_effort || !entropy_combine) {
const float x = quality / 100.f;
// cubic ramp between 1 and MAX_HISTO_GREEDY:
const int threshold_size = (int)(1 + (x * x * x) * (MAX_HISTO_GREEDY - 1));
int do_greedy;
if (!HistogramCombineStochastic(image_histo, threshold_size, &do_greedy)) {
goto Error;
}
if (do_greedy && !HistogramCombineGreedy(image_histo)) {
goto Error;
}
}
// TODO(vrabaud): Optimize HistogramRemap for low-effort compression mode.
// 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;
}
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