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Switch the histogram_enc.h API to fixed point

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Speedups: 4% with '-lossless', 8% with '-lossless -q 100 -m6'

Change-Id: I8f1c244b290d48132c1edc6a1c9fc3f79fef68ec
This commit is contained in:
Vincent Rabaud 2024-07-02 14:33:37 +02:00
parent ac1e410ded
commit 66408c2c7c
6 changed files with 148 additions and 139 deletions
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3
src/dsp/lossless_common.h
View File

@ -111,6 +111,9 @@ static WEBP_INLINE int64_t DivRound(int64_t a, int64_t b) {
return ((a < 0) == (b < 0)) ? ((a + b / 2) / b) : ((a - b / 2) / b);
}
#define WEBP_INT64_MAX ((int64_t)((1ull << 63) - 1))
#define WEBP_UINT64_MAX (~0ull)
// -----------------------------------------------------------------------------
// PrefixEncode()

4
src/enc/backward_references_cost_enc.c
View File

@ -320,9 +320,7 @@ static int CostManagerInit(CostManager* const manager,
}
// Set the initial costs_ to INT64_MAX for every pixel as we will keep the
// minimum.
for (i = 0; i < pix_count; ++i) {
manager->costs_[i] = (int64_t)((1ull << 63) - 1);
}
for (i = 0; i < pix_count; ++i) manager->costs_[i] = WEBP_INT64_MAX;
return 1;
}

14
src/enc/backward_references_enc.c
View File

@ -13,8 +13,6 @@
#include "src/enc/backward_references_enc.h"
#include <assert.h>
#include <float.h>
#include <math.h>
#include "src/dsp/dsp.h"
#include "src/dsp/lossless.h"
@ -27,8 +25,6 @@
#define MIN_BLOCK_SIZE 256 // minimum block size for backward references
#define MAX_ENTROPY (1e30f)
// 1M window (4M bytes) minus 120 special codes for short distances.
#define WINDOW_SIZE ((1 << WINDOW_SIZE_BITS) - 120)
@ -758,7 +754,7 @@ static int CalculateBestCacheSize(const uint32_t* argb, int quality,
int* const best_cache_bits) {
int i;
const int cache_bits_max = (quality <= 25) ? 0 : *best_cache_bits;
float entropy_min = MAX_ENTROPY;
uint64_t entropy_min = WEBP_UINT64_MAX;
int cc_init[MAX_COLOR_CACHE_BITS + 1] = { 0 };
VP8LColorCache hashers[MAX_COLOR_CACHE_BITS + 1];
VP8LRefsCursor c = VP8LRefsCursorInit(refs);
@ -843,7 +839,7 @@ static int CalculateBestCacheSize(const uint32_t* argb, int quality,
}
for (i = 0; i <= cache_bits_max; ++i) {
const float entropy = VP8LHistogramEstimateBits(histos[i]);
const uint64_t entropy = VP8LHistogramEstimateBits(histos[i]);
if (i == 0 || entropy < entropy_min) {
entropy_min = entropy;
*best_cache_bits = i;
@ -920,7 +916,7 @@ static int GetBackwardReferences(int width, int height,
int i, lz77_type;
// Index 0 is for a color cache, index 1 for no cache (if needed).
int lz77_types_best[2] = {0, 0};
float bit_costs_best[2] = {FLT_MAX, FLT_MAX};
uint64_t bit_costs_best[2] = {WEBP_UINT64_MAX, WEBP_UINT64_MAX};
VP8LHashChain hash_chain_box;
VP8LBackwardRefs* const refs_tmp = &refs[do_no_cache ? 2 : 1];
int status = 0;
@ -932,7 +928,7 @@ static int GetBackwardReferences(int width, int height,
for (lz77_type = 1; lz77_types_to_try;
lz77_types_to_try &= ~lz77_type, lz77_type <<= 1) {
int res = 0;
float bit_cost = 0.f;
uint64_t bit_cost = 0u;
if ((lz77_types_to_try & lz77_type) == 0) continue;
switch (lz77_type) {
case kLZ77RLE:
@ -1006,7 +1002,7 @@ static int GetBackwardReferences(int width, int height,
const VP8LHashChain* const hash_chain_tmp =
(lz77_types_best[i] == kLZ77Standard) ? hash_chain : &hash_chain_box;
const int cache_bits = (i == 1) ? 0 : *cache_bits_best;
float bit_cost_trace;
uint64_t bit_cost_trace;
if (!VP8LBackwardReferencesTraceBackwards(width, height, argb, cache_bits,
hash_chain_tmp, &refs[i],
refs_tmp)) {

236
src/enc/histogram_enc.c
View File

@ -13,8 +13,7 @@
#include "src/webp/config.h"
#endif
#include <float.h>
#include <math.h>
#include <string.h>
#include "src/dsp/lossless.h"
#include "src/dsp/lossless_common.h"
@ -23,8 +22,6 @@
#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
@ -102,10 +99,10 @@ void VP8LHistogramInit(VP8LHistogram* const p, int palette_code_bits,
HistogramClear(p);
} else {
p->trivial_symbol_ = 0;
p->bit_cost_ = 0.;
p->literal_cost_ = 0.;
p->red_cost_ = 0.;
p->blue_cost_ = 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_));
}
}
@ -230,8 +227,10 @@ void VP8LHistogramAddSinglePixOrCopy(VP8LHistogram* const histo,
// -----------------------------------------------------------------------------
// Entropy-related functions.
static WEBP_INLINE float BitsEntropyRefine(const VP8LBitEntropy* entropy) {
float mix;
static WEBP_INLINE uint64_t BitsEntropyRefine(const VP8LBitEntropy* entropy) {
uint64_t mix;
const uint64_t fixed_point_entropy =
(uint64_t)(entropy->entropy * (1ll << LOG_2_PRECISION_BITS) + .5);
if (entropy->nonzeros < 5) {
if (entropy->nonzeros <= 1) {
return 0;
@ -240,67 +239,72 @@ static WEBP_INLINE float BitsEntropyRefine(const VP8LBitEntropy* entropy) {
// 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;
return DivRound(99 * ((uint64_t)entropy->sum << LOG_2_PRECISION_BITS) +
fixed_point_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 = 0.95f;
mix = 950;
} else {
mix = 0.7f; // nonzeros == 4.
mix = 700; // nonzeros == 4.
}
} else {
mix = 0.627f;
mix = 627;
}
{
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;
uint64_t min_limit = (uint64_t)(2 * entropy->sum - entropy->max_val)
<< LOG_2_PRECISION_BITS;
min_limit =
DivRound(mix * min_limit + (1000 - mix) * fixed_point_entropy, 1000);
return (fixed_point_entropy < min_limit) ? min_limit : fixed_point_entropy;
}
}
float VP8LBitsEntropy(const uint32_t* const array, int n) {
uint64_t VP8LBitsEntropy(const uint32_t* const array, int n) {
VP8LBitEntropy entropy;
VP8LBitsEntropyUnrefined(array, n, &entropy);
return BitsEntropyRefine(&entropy);
}
static float InitialHuffmanCost(void) {
static uint64_t 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;
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 float FinalHuffmanCost(const VP8LStreaks* const stats) {
// The constants in this function are experimental and got rounded from
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.
float retval = InitialHuffmanCost();
uint64_t 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];
uint64_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 += stats->counts[1] * 2.578125f + 0.703125f * stats->streaks[1][1];
retval_extra += stats->counts[1] * 2640 + 720 * stats->streaks[1][1];
// 0s are usually encoded more efficiently than non-0s.
// Originally 15/8.
retval += 1.796875f * stats->streaks[0][0];
retval_extra += 1840 * stats->streaks[0][0];
// Originally 26/8.
retval += 3.28125f * stats->streaks[1][0];
return retval;
retval_extra += 3360 * stats->streaks[1][0];
return retval + (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 float PopulationCost(const uint32_t* const population, int length,
uint32_t* const trivial_sym,
uint8_t* const is_used) {
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);
@ -316,10 +320,11 @@ static float PopulationCost(const uint32_t* const population, int length,
// 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) {
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
@ -357,7 +362,7 @@ static WEBP_INLINE float GetCombinedEntropy(const uint32_t* const X,
}
// Estimates the Entropy + Huffman + other block overhead size cost.
float VP8LHistogramEstimateBits(VP8LHistogram* const p) {
uint64_t VP8LHistogramEstimateBits(VP8LHistogram* const p) {
return PopulationCost(p->literal_,
VP8LHistogramNumCodes(p->palette_code_bits_), NULL,
&p->is_used_[0]) +
@ -366,9 +371,10 @@ float VP8LHistogramEstimateBits(VP8LHistogram* const p) {
PopulationCost(p->alpha_, NUM_LITERAL_CODES, NULL, &p->is_used_[3]) +
PopulationCost(p->distance_, NUM_DISTANCE_CODES, NULL,
&p->is_used_[4]) +
(float)VP8LExtraCost(p->literal_ + NUM_LITERAL_CODES,
NUM_LENGTH_CODES) +
(float)VP8LExtraCost(p->distance_, NUM_DISTANCE_CODES);
((uint64_t)(VP8LExtraCost(p->literal_ + NUM_LITERAL_CODES,
NUM_LENGTH_CODES) +
VP8LExtraCost(p->distance_, NUM_DISTANCE_CODES))
<< LOG_2_PRECISION_BITS);
}
// -----------------------------------------------------------------------------
@ -376,16 +382,17 @@ float VP8LHistogramEstimateBits(VP8LHistogram* const p) {
static int GetCombinedHistogramEntropy(const VP8LHistogram* const a,
const VP8LHistogram* const b,
float cost_threshold, float* cost) {
int64_t cost_threshold, int64_t* 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 += (float)VP8LExtraCostCombined(a->literal_ + NUM_LITERAL_CODES,
b->literal_ + NUM_LITERAL_CODES,
NUM_LENGTH_CODES);
*cost += (int64_t)VP8LExtraCostCombined(a->literal_ + NUM_LITERAL_CODES,
b->literal_ + NUM_LITERAL_CODES,
NUM_LENGTH_CODES)
<< LOG_2_PRECISION_BITS;
if (*cost > cost_threshold) return 0;
if (a->trivial_symbol_ != VP8L_NON_TRIVIAL_SYM &&
@ -419,8 +426,9 @@ static int GetCombinedHistogramEntropy(const VP8LHistogram* const a,
*cost +=
GetCombinedEntropy(a->distance_, b->distance_, NUM_DISTANCE_CODES,
a->is_used_[4], b->is_used_[4], 0);
*cost += (float)VP8LExtraCostCombined(a->distance_, b->distance_,
NUM_DISTANCE_CODES);
*cost += (int64_t)VP8LExtraCostCombined(a->distance_, b->distance_,
NUM_DISTANCE_CODES)
<< LOG_2_PRECISION_BITS;
if (*cost > cost_threshold) return 0;
return 1;
@ -441,11 +449,12 @@ static WEBP_INLINE void HistogramAdd(const VP8LHistogram* const a,
// 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_;
static int64_t HistogramAddEval(const VP8LHistogram* const a,
const VP8LHistogram* const b,
VP8LHistogram* const out,
int64_t cost_threshold) {
int64_t cost = 0;
const int64_t sum_cost = a->bit_cost_ + b->bit_cost_;
cost_threshold += sum_cost;
if (GetCombinedHistogramEntropy(a, b, cost_threshold, &cost)) {
@ -460,10 +469,10 @@ static float HistogramAddEval(const VP8LHistogram* const a,
// 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;
static int64_t HistogramAddThresh(const VP8LHistogram* const a,
const VP8LHistogram* const b,
int64_t cost_threshold) {
int64_t cost;
assert(a != NULL && b != NULL);
cost = -a->bit_cost_;
GetCombinedHistogramEntropy(a, b, cost_threshold, &cost);
@ -475,21 +484,21 @@ static float HistogramAddThresh(const VP8LHistogram* const a,
// 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_;
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_ = MAX_BIT_COST;
c->red_max_ = 0.;
c->red_min_ = MAX_BIT_COST;
c->blue_max_ = 0.;
c->blue_min_ = MAX_BIT_COST;
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(
@ -504,15 +513,18 @@ static void UpdateDominantCostRange(
static void UpdateHistogramCost(VP8LHistogram* const h) {
uint32_t alpha_sym, red_sym, blue_sym;
const float alpha_cost =
const uint64_t alpha_cost =
PopulationCost(h->alpha_, NUM_LITERAL_CODES, &alpha_sym, &h->is_used_[3]);
const float distance_cost =
const uint64_t distance_cost =
PopulationCost(h->distance_, NUM_DISTANCE_CODES, NULL, &h->is_used_[4]) +
(float)VP8LExtraCost(h->distance_, NUM_DISTANCE_CODES);
((uint64_t)VP8LExtraCost(h->distance_, NUM_DISTANCE_CODES)
<< LOG_2_PRECISION_BITS);
const int num_codes = VP8LHistogramNumCodes(h->palette_code_bits_);
h->literal_cost_ =
PopulationCost(h->literal_, num_codes, NULL, &h->is_used_[0]) +
(float)VP8LExtraCost(h->literal_ + NUM_LITERAL_CODES, NUM_LENGTH_CODES);
((uint64_t)VP8LExtraCost(h->literal_ + NUM_LITERAL_CODES,
NUM_LENGTH_CODES)
<< LOG_2_PRECISION_BITS);
h->red_cost_ =
PopulationCost(h->red_, NUM_LITERAL_CODES, &red_sym, &h->is_used_[1]);
h->blue_cost_ =
@ -527,10 +539,10 @@ static void UpdateHistogramCost(VP8LHistogram* const h) {
}
}
static int GetBinIdForEntropy(float min, float max, float val) {
const float range = max - min;
if (range > 0.) {
const float delta = val - min;
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;
@ -639,11 +651,12 @@ static void HistogramAnalyzeEntropyBin(VP8LHistogramSet* const image_histo,
// 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 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) {
int32_t combine_cost_factor, int low_effort) {
VP8LHistogram** const histograms = image_histo->histograms;
int idx;
struct {
@ -673,9 +686,10 @@ static void HistogramCombineEntropyBin(
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(
const int64_t bit_cost = histograms[idx]->bit_cost_;
const int64_t bit_cost_thresh =
-DivRound(bit_cost * combine_cost_factor, 100);
const int64_t 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
@ -724,8 +738,8 @@ static uint32_t MyRand(uint32_t* const seed) {
typedef struct {
int idx1;
int idx2;
float cost_diff;
float cost_combo;
int64_t cost_diff;
int64_t cost_combo;
} HistogramPair;
typedef struct {
@ -765,7 +779,7 @@ static void HistoQueuePopPair(HistoQueue* const histo_queue,
// 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->cost_diff < 0);
assert(pair >= histo_queue->queue &&
pair < (histo_queue->queue + histo_queue->size));
assert(histo_queue->size > 0);
@ -778,29 +792,29 @@ static void HistoQueueUpdateHead(HistoQueue* const histo_queue,
}
// 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.
// called when 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.;
const VP8LHistogram* const h2,
int64_t threshold, HistogramPair* const pair) {
const int64_t 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) {
// 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 (histo_queue->size == histo_queue->max_size) return 0;
assert(threshold <= 0);
if (idx1 > idx2) {
const int tmp = idx2;
idx2 = idx1;
@ -814,7 +828,7 @@ static float HistoQueuePush(HistoQueue* const histo_queue,
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.;
if (pair.cost_diff >= threshold) return 0;
histo_queue->queue[histo_queue->size++] = pair;
HistoQueueUpdateHead(histo_queue, &histo_queue->queue[histo_queue->size - 1]);
@ -851,7 +865,7 @@ static int HistogramCombineGreedy(VP8LHistogramSet* const image_histo,
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.);
HistoQueuePush(&histo_queue, histograms, i, j, 0);
}
}
@ -879,7 +893,7 @@ static int HistogramCombineGreedy(VP8LHistogramSet* const image_histo,
// 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.);
HistoQueuePush(&histo_queue, image_histo->histograms, idx1, i, 0);
}
}
@ -937,8 +951,8 @@ static int HistogramCombineStochastic(VP8LHistogramSet* const image_histo,
++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;
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
@ -947,7 +961,7 @@ static int HistogramCombineStochastic(VP8LHistogramSet* const image_histo,
// Pick random samples.
for (j = 0; *num_used >= 2 && j < num_tries; ++j) {
float curr_cost;
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);
@ -1012,8 +1026,8 @@ static int HistogramCombineStochastic(VP8LHistogramSet* const image_histo,
}
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.) {
HistoQueueUpdatePair(histograms[p->idx1], histograms[p->idx2], 0, p);
if (p->cost_diff >= 0) {
HistoQueuePopPair(&histo_queue, p);
continue;
}
@ -1049,7 +1063,7 @@ static void HistogramRemap(const VP8LHistogramSet* const in,
if (out_size > 1) {
for (i = 0; i < in_size; ++i) {
int best_out = 0;
float best_bits = MAX_BIT_COST;
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.
@ -1057,7 +1071,7 @@ static void HistogramRemap(const VP8LHistogramSet* const in,
continue;
}
for (k = 0; k < out_size; ++k) {
float cur_bits;
int64_t cur_bits;
cur_bits = HistogramAddThresh(out_histo[k], in_histo[i], best_bits);
if (k == 0 || cur_bits < best_bits) {
best_bits = cur_bits;
@ -1085,13 +1099,13 @@ static void HistogramRemap(const VP8LHistogramSet* const in,
}
}
static float GetCombineCostFactor(int histo_size, int quality) {
float combine_cost_factor = 0.16f;
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.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;
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;
}
@ -1201,7 +1215,7 @@ int VP8LGetHistoImageSymbols(int xsize, int ysize,
if (entropy_combine) {
uint16_t* const bin_map = map_tmp;
const float combine_cost_factor =
const int32_t combine_cost_factor =
GetCombineCostFactor(image_histo_raw_size, quality);
const uint32_t num_clusters = num_used;

12
src/enc/histogram_enc.h
View File

@ -40,10 +40,10 @@ typedef struct {
int palette_code_bits_;
uint32_t trivial_symbol_; // True, if histograms for Red, Blue & Alpha
// literal symbols are single valued.
float bit_cost_; // cached value of bit cost.
float literal_cost_; // Cached values of dominant entropy costs:
float red_cost_; // literal, red & blue.
float blue_cost_;
int64_t bit_cost_; // cached value of bit cost.
uint64_t literal_cost_; // Cached values of dominant entropy costs:
uint64_t red_cost_; // literal, red & blue.
uint64_t blue_cost_;
uint8_t is_used_[5]; // 5 for literal, red, blue, alpha, distance
} VP8LHistogram;
@ -117,11 +117,11 @@ int VP8LGetHistoImageSymbols(int xsize, int ysize,
int* const percent);
// Returns the entropy for the symbols in the input array.
float VP8LBitsEntropy(const uint32_t* const array, int n);
uint64_t VP8LBitsEntropy(const uint32_t* const array, int n);
// Estimate how many bits the combined entropy of literals and distance
// approximately maps to.
float VP8LHistogramEstimateBits(VP8LHistogram* const p);
uint64_t VP8LHistogramEstimateBits(VP8LHistogram* const p);
#ifdef __cplusplus
}

18
src/enc/vp8l_enc.c
View File

@ -141,8 +141,8 @@ static int AnalyzeEntropy(const uint32_t* argb,
curr_row += argb_stride;
}
{
float entropy_comp[kHistoTotal];
float entropy[kNumEntropyIx];
uint64_t entropy_comp[kHistoTotal];
uint64_t entropy[kNumEntropyIx];
int k;
int last_mode_to_analyze = use_palette ? kPalette : kSpatialSubGreen;
int j;
@ -180,21 +180,19 @@ static int AnalyzeEntropy(const uint32_t* argb,
// When including transforms, there is an overhead in bits from
// storing them. This overhead is small but matters for small images.
// For spatial, there are 14 transformations.
entropy[kSpatial] += RightShiftRound(
(uint64_t)VP8LSubSampleSize(width, transform_bits) *
VP8LSubSampleSize(height, transform_bits) * VP8LFastLog2(14),
LOG_2_PRECISION_BITS);
entropy[kSpatial] += (uint64_t)VP8LSubSampleSize(width, transform_bits) *
VP8LSubSampleSize(height, transform_bits) *
VP8LFastLog2(14);
// For color transforms: 24 as only 3 channels are considered in a
// ColorTransformElement.
entropy[kSpatialSubGreen] += RightShiftRound(
entropy[kSpatialSubGreen] +=
(uint64_t)VP8LSubSampleSize(width, transform_bits) *
VP8LSubSampleSize(height, transform_bits) * VP8LFastLog2(24),
LOG_2_PRECISION_BITS);
VP8LSubSampleSize(height, transform_bits) * VP8LFastLog2(24);
// For palettes, add the cost of storing the palette.
// We empirically estimate the cost of a compressed entry as 8 bits.
// The palette is differential-coded when compressed hence a much
// lower cost than sizeof(uint32_t)*8.
entropy[kPalette] += palette_size * 8;
entropy[kPalette] += (palette_size * 8ull) << LOG_2_PRECISION_BITS;
*min_entropy_ix = kDirect;
for (k = kDirect + 1; k <= last_mode_to_analyze; ++k) {