515 lines
17 KiB
C
515 lines
17 KiB
C
// Copyright 2012 Google Inc. All Rights Reserved.
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//
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// Use of this source code is governed by a BSD-style license
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// that can be found in the COPYING file in the root of the source
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// tree. An additional intellectual property rights grant can be found
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// in the file PATENTS. All contributing project authors may
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// be found in the AUTHORS file in the root of the source tree.
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// -----------------------------------------------------------------------------
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//
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// Author: Jyrki Alakuijala (jyrki@google.com)
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//
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#ifdef HAVE_CONFIG_H
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#include "config.h"
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#endif
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#include <math.h>
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#include <stdio.h>
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#include "./backward_references.h"
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#include "./histogram.h"
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#include "../dsp/lossless.h"
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#include "../utils/utils.h"
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static void HistogramClear(VP8LHistogram* const p) {
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memset(p->literal_, 0, sizeof(p->literal_));
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memset(p->red_, 0, sizeof(p->red_));
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memset(p->blue_, 0, sizeof(p->blue_));
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memset(p->alpha_, 0, sizeof(p->alpha_));
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memset(p->distance_, 0, sizeof(p->distance_));
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p->bit_cost_ = 0;
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}
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void VP8LHistogramStoreRefs(const VP8LBackwardRefs* const refs,
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VP8LHistogram* const histo) {
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int i;
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for (i = 0; i < refs->size; ++i) {
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VP8LHistogramAddSinglePixOrCopy(histo, &refs->refs[i]);
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}
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}
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void VP8LHistogramCreate(VP8LHistogram* const p,
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const VP8LBackwardRefs* const refs,
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int palette_code_bits) {
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if (palette_code_bits >= 0) {
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p->palette_code_bits_ = palette_code_bits;
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}
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HistogramClear(p);
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VP8LHistogramStoreRefs(refs, p);
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}
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void VP8LHistogramInit(VP8LHistogram* const p, int palette_code_bits) {
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p->palette_code_bits_ = palette_code_bits;
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HistogramClear(p);
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}
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VP8LHistogramSet* VP8LAllocateHistogramSet(int size, int cache_bits) {
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int i;
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VP8LHistogramSet* set;
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VP8LHistogram* bulk;
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const uint64_t total_size = sizeof(*set)
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+ (uint64_t)size * sizeof(*set->histograms)
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+ (uint64_t)size * sizeof(**set->histograms);
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uint8_t* memory = (uint8_t*)WebPSafeMalloc(total_size, sizeof(*memory));
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if (memory == NULL) return NULL;
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set = (VP8LHistogramSet*)memory;
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memory += sizeof(*set);
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set->histograms = (VP8LHistogram**)memory;
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memory += size * sizeof(*set->histograms);
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bulk = (VP8LHistogram*)memory;
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set->max_size = size;
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set->size = size;
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for (i = 0; i < size; ++i) {
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set->histograms[i] = bulk + i;
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VP8LHistogramInit(set->histograms[i], cache_bits);
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}
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return set;
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}
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// -----------------------------------------------------------------------------
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void VP8LHistogramAddSinglePixOrCopy(VP8LHistogram* const histo,
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const PixOrCopy* const v) {
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if (PixOrCopyIsLiteral(v)) {
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++histo->alpha_[PixOrCopyLiteral(v, 3)];
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++histo->red_[PixOrCopyLiteral(v, 2)];
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++histo->literal_[PixOrCopyLiteral(v, 1)];
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++histo->blue_[PixOrCopyLiteral(v, 0)];
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} else if (PixOrCopyIsCacheIdx(v)) {
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int literal_ix = 256 + NUM_LENGTH_CODES + PixOrCopyCacheIdx(v);
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++histo->literal_[literal_ix];
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} else {
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int code, extra_bits_count, extra_bits_value;
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PrefixEncode(PixOrCopyLength(v),
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&code, &extra_bits_count, &extra_bits_value);
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++histo->literal_[256 + code];
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PrefixEncode(PixOrCopyDistance(v),
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&code, &extra_bits_count, &extra_bits_value);
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++histo->distance_[code];
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}
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}
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static double BitsEntropy(const int* const array, int n) {
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double retval = 0.;
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int sum = 0;
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int nonzeros = 0;
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int max_val = 0;
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int i;
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double mix;
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for (i = 0; i < n; ++i) {
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if (array[i] != 0) {
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sum += array[i];
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++nonzeros;
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retval -= VP8LFastSLog2(array[i]);
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if (max_val < array[i]) {
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max_val = array[i];
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}
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}
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}
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retval += VP8LFastSLog2(sum);
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if (nonzeros < 5) {
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if (nonzeros <= 1) {
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return 0;
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}
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// Two symbols, they will be 0 and 1 in a Huffman code.
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// Let's mix in a bit of entropy to favor good clustering when
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// distributions of these are combined.
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if (nonzeros == 2) {
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return 0.99 * sum + 0.01 * retval;
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}
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// No matter what the entropy says, we cannot be better than min_limit
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// with Huffman coding. I am mixing a bit of entropy into the
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// min_limit since it produces much better (~0.5 %) compression results
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// perhaps because of better entropy clustering.
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if (nonzeros == 3) {
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mix = 0.95;
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} else {
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mix = 0.7; // nonzeros == 4.
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}
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} else {
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mix = 0.627;
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}
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{
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double min_limit = 2 * sum - max_val;
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min_limit = mix * min_limit + (1.0 - mix) * retval;
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return (retval < min_limit) ? min_limit : retval;
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}
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}
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// Returns the cost encode the rle-encoded entropy code.
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// The constants in this function are experimental.
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static double HuffmanCost(const int* const population, int length) {
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// Small bias because Huffman code length is typically not stored in
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// full length.
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static const int kHuffmanCodeOfHuffmanCodeSize = CODE_LENGTH_CODES * 3;
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static const double kSmallBias = 9.1;
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double retval = kHuffmanCodeOfHuffmanCodeSize - kSmallBias;
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int streak = 0;
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int i = 0;
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for (; i < length - 1; ++i) {
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++streak;
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if (population[i] == population[i + 1]) {
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continue;
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}
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last_streak_hack:
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// population[i] points now to the symbol in the streak of same values.
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if (streak > 3) {
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if (population[i] == 0) {
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retval += 1.5625 + 0.234375 * streak;
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} else {
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retval += 2.578125 + 0.703125 * streak;
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}
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} else {
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if (population[i] == 0) {
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retval += 1.796875 * streak;
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} else {
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retval += 3.28125 * streak;
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}
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}
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streak = 0;
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}
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if (i == length - 1) {
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++streak;
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goto last_streak_hack;
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}
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return retval;
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}
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static double PopulationCost(const int* const population, int length) {
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return BitsEntropy(population, length) + HuffmanCost(population, length);
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}
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static double ExtraCost(const int* const population, int length) {
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int i;
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double cost = 0.;
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for (i = 2; i < length - 2; ++i) cost += (i >> 1) * population[i + 2];
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return cost;
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}
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// Estimates the Entropy + Huffman + other block overhead size cost.
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double VP8LHistogramEstimateBits(const VP8LHistogram* const p) {
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return PopulationCost(p->literal_, VP8LHistogramNumCodes(p))
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+ PopulationCost(p->red_, 256)
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+ PopulationCost(p->blue_, 256)
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+ PopulationCost(p->alpha_, 256)
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+ PopulationCost(p->distance_, NUM_DISTANCE_CODES)
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+ ExtraCost(p->literal_ + 256, NUM_LENGTH_CODES)
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+ ExtraCost(p->distance_, NUM_DISTANCE_CODES);
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}
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double VP8LHistogramEstimateBitsBulk(const VP8LHistogram* const p) {
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return BitsEntropy(p->literal_, VP8LHistogramNumCodes(p))
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+ BitsEntropy(p->red_, 256)
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+ BitsEntropy(p->blue_, 256)
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+ BitsEntropy(p->alpha_, 256)
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+ BitsEntropy(p->distance_, NUM_DISTANCE_CODES)
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+ ExtraCost(p->literal_ + 256, NUM_LENGTH_CODES)
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+ ExtraCost(p->distance_, NUM_DISTANCE_CODES);
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}
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// -----------------------------------------------------------------------------
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// Various histogram combine/cost-eval functions
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// Adds 'in' histogram to 'out'
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static void HistogramAdd(const VP8LHistogram* const in,
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VP8LHistogram* const out) {
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int i;
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for (i = 0; i < PIX_OR_COPY_CODES_MAX; ++i) {
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out->literal_[i] += in->literal_[i];
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}
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for (i = 0; i < NUM_DISTANCE_CODES; ++i) {
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out->distance_[i] += in->distance_[i];
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}
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for (i = 0; i < 256; ++i) {
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out->red_[i] += in->red_[i];
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out->blue_[i] += in->blue_[i];
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out->alpha_[i] += in->alpha_[i];
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}
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}
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// Performs out = a + b, computing the cost C(a+b) - C(a) - C(b) while comparing
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// to the threshold value 'cost_threshold'. The score returned is
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// Score = C(a+b) - C(a) - C(b), where C(a) + C(b) is known and fixed.
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// Since the previous score passed is 'cost_threshold', we only need to compare
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// the partial cost against 'cost_threshold + C(a) + C(b)' to possibly bail-out
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// early.
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static double HistogramAddEval(const VP8LHistogram* const a,
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const VP8LHistogram* const b,
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VP8LHistogram* const out,
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double cost_threshold) {
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double cost = 0;
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const double sum_cost = a->bit_cost_ + b->bit_cost_;
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int i;
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cost_threshold += sum_cost;
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// palette_code_bits_ is part of the cost evaluation for literal_.
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// TODO(skal): remove/simplify this palette_code_bits_?
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out->palette_code_bits_ =
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(a->palette_code_bits_ > b->palette_code_bits_) ? a->palette_code_bits_ :
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b->palette_code_bits_;
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for (i = 0; i < PIX_OR_COPY_CODES_MAX; ++i) {
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out->literal_[i] = a->literal_[i] + b->literal_[i];
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}
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cost += PopulationCost(out->literal_, VP8LHistogramNumCodes(out));
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cost += ExtraCost(out->literal_ + 256, NUM_LENGTH_CODES);
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if (cost > cost_threshold) return cost;
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for (i = 0; i < 256; ++i) out->red_[i] = a->red_[i] + b->red_[i];
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cost += PopulationCost(out->red_, 256);
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if (cost > cost_threshold) return cost;
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for (i = 0; i < 256; ++i) out->blue_[i] = a->blue_[i] + b->blue_[i];
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cost += PopulationCost(out->blue_, 256);
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if (cost > cost_threshold) return cost;
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for (i = 0; i < NUM_DISTANCE_CODES; ++i) {
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out->distance_[i] = a->distance_[i] + b->distance_[i];
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}
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cost += PopulationCost(out->distance_, NUM_DISTANCE_CODES);
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cost += ExtraCost(out->distance_, NUM_DISTANCE_CODES);
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if (cost > cost_threshold) return cost;
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for (i = 0; i < 256; ++i) out->alpha_[i] = a->alpha_[i] + b->alpha_[i];
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cost += PopulationCost(out->alpha_, 256);
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out->bit_cost_ = cost;
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return cost - sum_cost;
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}
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// Same as HistogramAddEval(), except that the resulting histogram
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// is not stored. Only the cost C(a+b) - C(a) is evaluated. We omit
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// the term C(b) which is constant over all the evaluations.
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static double HistogramAddThresh(const VP8LHistogram* const a,
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const VP8LHistogram* const b,
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double cost_threshold) {
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int tmp[PIX_OR_COPY_CODES_MAX]; // <= max storage we'll need
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int i;
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double cost = -a->bit_cost_;
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for (i = 0; i < PIX_OR_COPY_CODES_MAX; ++i) {
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tmp[i] = a->literal_[i] + b->literal_[i];
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}
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// note that the tests are ordered so that the usually largest
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// cost shares come first.
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cost += PopulationCost(tmp, VP8LHistogramNumCodes(a));
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cost += ExtraCost(tmp + 256, NUM_LENGTH_CODES);
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if (cost > cost_threshold) return cost;
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for (i = 0; i < 256; ++i) tmp[i] = a->red_[i] + b->red_[i];
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cost += PopulationCost(tmp, 256);
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if (cost > cost_threshold) return cost;
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for (i = 0; i < 256; ++i) tmp[i] = a->blue_[i] + b->blue_[i];
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cost += PopulationCost(tmp, 256);
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if (cost > cost_threshold) return cost;
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for (i = 0; i < NUM_DISTANCE_CODES; ++i) {
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tmp[i] = a->distance_[i] + b->distance_[i];
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}
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cost += PopulationCost(tmp, NUM_DISTANCE_CODES);
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cost += ExtraCost(tmp, NUM_DISTANCE_CODES);
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if (cost > cost_threshold) return cost;
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for (i = 0; i < 256; ++i) tmp[i] = a->alpha_[i] + b->alpha_[i];
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cost += PopulationCost(tmp, 256);
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return cost;
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}
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// -----------------------------------------------------------------------------
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static void HistogramBuildImage(int xsize, int histo_bits,
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const VP8LBackwardRefs* const backward_refs,
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VP8LHistogramSet* const image) {
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int i;
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int x = 0, y = 0;
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const int histo_xsize = VP8LSubSampleSize(xsize, histo_bits);
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VP8LHistogram** const histograms = image->histograms;
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assert(histo_bits > 0);
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for (i = 0; i < backward_refs->size; ++i) {
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const PixOrCopy* const v = &backward_refs->refs[i];
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const int ix = (y >> histo_bits) * histo_xsize + (x >> histo_bits);
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VP8LHistogramAddSinglePixOrCopy(histograms[ix], v);
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x += PixOrCopyLength(v);
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while (x >= xsize) {
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x -= xsize;
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++y;
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}
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}
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}
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static uint32_t MyRand(uint32_t *seed) {
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*seed *= 16807U;
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if (*seed == 0) {
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*seed = 1;
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}
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return *seed;
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}
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static int HistogramCombine(const VP8LHistogramSet* const in,
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VP8LHistogramSet* const out, int iter_mult,
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int num_pairs, int num_tries_no_success) {
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int ok = 0;
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int i, iter;
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uint32_t seed = 0;
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int tries_with_no_success = 0;
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int out_size = in->size;
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const int outer_iters = in->size * iter_mult;
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const int min_cluster_size = 2;
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VP8LHistogram* const histos = (VP8LHistogram*)malloc(2 * sizeof(*histos));
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VP8LHistogram* cur_combo = histos + 0; // trial merged histogram
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VP8LHistogram* best_combo = histos + 1; // best merged histogram so far
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if (histos == NULL) goto End;
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// Copy histograms from in[] to out[].
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assert(in->size <= out->size);
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for (i = 0; i < in->size; ++i) {
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in->histograms[i]->bit_cost_ = VP8LHistogramEstimateBits(in->histograms[i]);
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*out->histograms[i] = *in->histograms[i];
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}
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// Collapse similar histograms in 'out'.
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for (iter = 0; iter < outer_iters && out_size >= min_cluster_size; ++iter) {
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double best_cost_diff = 0.;
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int best_idx1 = -1, best_idx2 = 1;
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int j;
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const int num_tries = (num_pairs < out_size) ? num_pairs : out_size;
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seed += iter;
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for (j = 0; j < num_tries; ++j) {
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double curr_cost_diff;
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// Choose two histograms at random and try to combine them.
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const uint32_t idx1 = MyRand(&seed) % out_size;
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const uint32_t tmp = (j & 7) + 1;
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const uint32_t diff = (tmp < 3) ? tmp : MyRand(&seed) % (out_size - 1);
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const uint32_t idx2 = (idx1 + diff + 1) % out_size;
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if (idx1 == idx2) {
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continue;
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}
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// Calculate cost reduction on combining.
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curr_cost_diff = HistogramAddEval(out->histograms[idx1],
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out->histograms[idx2],
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cur_combo, best_cost_diff);
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if (curr_cost_diff < best_cost_diff) { // found a better pair?
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{ // swap cur/best combo histograms
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VP8LHistogram* const tmp_histo = cur_combo;
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cur_combo = best_combo;
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best_combo = tmp_histo;
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}
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best_cost_diff = curr_cost_diff;
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best_idx1 = idx1;
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best_idx2 = idx2;
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}
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}
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if (best_idx1 >= 0) {
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*out->histograms[best_idx1] = *best_combo;
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// swap best_idx2 slot with last one (which is now unused)
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--out_size;
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if (best_idx2 != out_size) {
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out->histograms[best_idx2] = out->histograms[out_size];
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out->histograms[out_size] = NULL; // just for sanity check.
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}
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tries_with_no_success = 0;
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}
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if (++tries_with_no_success >= num_tries_no_success) {
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break;
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}
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}
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out->size = out_size;
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ok = 1;
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End:
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free(histos);
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return ok;
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}
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// -----------------------------------------------------------------------------
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// Histogram refinement
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// What is the bit cost of moving square_histogram from cur_symbol to candidate.
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static double HistogramDistance(const VP8LHistogram* const square_histogram,
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const VP8LHistogram* const candidate,
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double cost_threshold) {
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return HistogramAddThresh(candidate, square_histogram, cost_threshold);
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}
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// Find the best 'out' histogram for each of the 'in' histograms.
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// Note: we assume that out[]->bit_cost_ is already up-to-date.
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static void HistogramRemap(const VP8LHistogramSet* const in,
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const VP8LHistogramSet* const out,
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uint16_t* const symbols) {
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int i;
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for (i = 0; i < in->size; ++i) {
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int best_out = 0;
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double best_bits =
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HistogramDistance(in->histograms[i], out->histograms[0], 1.e38);
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int k;
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for (k = 1; k < out->size; ++k) {
|
|
const double cur_bits =
|
|
HistogramDistance(in->histograms[i], out->histograms[k], best_bits);
|
|
if (cur_bits < best_bits) {
|
|
best_bits = cur_bits;
|
|
best_out = k;
|
|
}
|
|
}
|
|
symbols[i] = best_out;
|
|
}
|
|
|
|
// Recompute each out based on raw and symbols.
|
|
for (i = 0; i < out->size; ++i) {
|
|
HistogramClear(out->histograms[i]);
|
|
}
|
|
for (i = 0; i < in->size; ++i) {
|
|
HistogramAdd(in->histograms[i], out->histograms[symbols[i]]);
|
|
}
|
|
}
|
|
|
|
int VP8LGetHistoImageSymbols(int xsize, int ysize,
|
|
const VP8LBackwardRefs* const refs,
|
|
int quality, int histo_bits, int cache_bits,
|
|
VP8LHistogramSet* const image_in,
|
|
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 histo_image_raw_size = histo_xsize * histo_ysize;
|
|
|
|
// Heuristic params for HistogramCombine().
|
|
const int num_tries_no_success = 8 + (quality >> 1);
|
|
const int iter_mult = (quality < 27) ? 1 : 1 + ((quality - 27) >> 4);
|
|
const int num_pairs = (quality < 25) ? 10 : (5 * quality) >> 3;
|
|
|
|
VP8LHistogramSet* const image_out =
|
|
VP8LAllocateHistogramSet(histo_image_raw_size, cache_bits);
|
|
if (image_out == NULL) return 0;
|
|
|
|
// Build histogram image.
|
|
HistogramBuildImage(xsize, histo_bits, refs, image_out);
|
|
// Collapse similar histograms.
|
|
if (!HistogramCombine(image_out, image_in, iter_mult, num_pairs,
|
|
num_tries_no_success)) {
|
|
goto Error;
|
|
}
|
|
// Find the optimal map from original histograms to the final ones.
|
|
HistogramRemap(image_out, image_in, histogram_symbols);
|
|
ok = 1;
|
|
|
|
Error:
|
|
free(image_out);
|
|
return ok;
|
|
}
|