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406 lines
13 KiB
406 lines
13 KiB
// Copyright 2012 Google Inc. All Rights Reserved. |
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// |
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// This code is licensed under the same terms as WebM: |
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// Software License Agreement: http://www.webmproject.org/license/software/ |
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// Additional IP Rights Grant: http://www.webmproject.org/license/additional/ |
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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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double VP8LHistogramEstimateBitsBulk(const VP8LHistogram* const p) { |
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double retval = BitsEntropy(&p->literal_[0], VP8LHistogramNumCodes(p)) |
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+ BitsEntropy(&p->red_[0], 256) |
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+ BitsEntropy(&p->blue_[0], 256) |
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+ BitsEntropy(&p->alpha_[0], 256) |
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+ BitsEntropy(&p->distance_[0], NUM_DISTANCE_CODES); |
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// Compute the extra bits cost. |
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int i; |
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for (i = 2; i < NUM_LENGTH_CODES - 2; ++i) { |
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retval += |
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(i >> 1) * p->literal_[256 + i + 2]; |
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} |
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for (i = 2; i < NUM_DISTANCE_CODES - 2; ++i) { |
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retval += (i >> 1) * p->distance_[i + 2]; |
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} |
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return retval; |
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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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// Estimates the Huffman dictionary + other block overhead size. |
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static double HistogramEstimateBitsHeader(const VP8LHistogram* const p) { |
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return HuffmanCost(&p->alpha_[0], 256) + |
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HuffmanCost(&p->red_[0], 256) + |
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HuffmanCost(&p->literal_[0], VP8LHistogramNumCodes(p)) + |
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HuffmanCost(&p->blue_[0], 256) + |
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HuffmanCost(&p->distance_[0], NUM_DISTANCE_CODES); |
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} |
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double VP8LHistogramEstimateBits(const VP8LHistogram* const p) { |
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return HistogramEstimateBitsHeader(p) + VP8LHistogramEstimateBitsBulk(p); |
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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 num_pairs) { |
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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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const int min_cluster_size = 2; |
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int out_size = in->size; |
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const int outer_iters = in->size * 3; |
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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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// We pick the best pair to be combined out of 'inner_iters' pairs. |
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double best_cost_diff = 0.; |
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int best_idx1 = 0, best_idx2 = 1; |
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int j; |
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seed += iter; |
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for (j = 0; j < num_pairs; ++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) % (out_size - 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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*cur_combo = *out->histograms[idx1]; |
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VP8LHistogramAdd(cur_combo, out->histograms[idx2]); |
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cur_combo->bit_cost_ = VP8LHistogramEstimateBits(cur_combo); |
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// Calculate cost reduction on combining. |
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curr_cost_diff = cur_combo->bit_cost_ |
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- out->histograms[idx1]->bit_cost_ |
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- out->histograms[idx2]->bit_cost_; |
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if (best_cost_diff > curr_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_cost_diff < 0.0) { |
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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 >= 50) { |
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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 |
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// cur_symbol to candidate_symbol. |
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// TODO(skal): we don't really need to copy the histogram and Add(). Instead |
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// we just need VP8LDualHistogramEstimateBits(A, B) estimation function. |
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static double HistogramDistance(const VP8LHistogram* const square_histogram, |
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const VP8LHistogram* const candidate) { |
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const double previous_bit_cost = candidate->bit_cost_; |
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double new_bit_cost; |
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VP8LHistogram modified_histo; |
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modified_histo = *candidate; |
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VP8LHistogramAdd(&modified_histo, square_histogram); |
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new_bit_cost = VP8LHistogramEstimateBits(&modified_histo); |
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return new_bit_cost - previous_bit_cost; |
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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 = HistogramDistance(in->histograms[i], out->histograms[0]); |
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int k; |
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for (k = 1; k < out->size; ++k) { |
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const double cur_bits = |
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HistogramDistance(in->histograms[i], out->histograms[k]); |
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if (cur_bits < best_bits) { |
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best_bits = cur_bits; |
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best_out = k; |
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} |
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} |
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symbols[i] = best_out; |
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} |
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// Recompute each out based on raw and symbols. |
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for (i = 0; i < out->size; ++i) { |
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HistogramClear(out->histograms[i]); |
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} |
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for (i = 0; i < in->size; ++i) { |
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VP8LHistogramAdd(out->histograms[symbols[i]], in->histograms[i]); |
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} |
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} |
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int VP8LGetHistoImageSymbols(int xsize, int ysize, |
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const VP8LBackwardRefs* const refs, |
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int quality, int histo_bits, int cache_bits, |
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VP8LHistogramSet* const image_in, |
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uint16_t* const histogram_symbols) { |
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int ok = 0; |
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const int histo_xsize = histo_bits ? VP8LSubSampleSize(xsize, histo_bits) : 1; |
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const int histo_ysize = histo_bits ? VP8LSubSampleSize(ysize, histo_bits) : 1; |
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const int num_histo_pairs = 10 + quality / 2; // For HistogramCombine(). |
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const int histo_image_raw_size = histo_xsize * histo_ysize; |
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VP8LHistogramSet* const image_out = |
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VP8LAllocateHistogramSet(histo_image_raw_size, cache_bits); |
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if (image_out == NULL) return 0; |
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// Build histogram image. |
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HistogramBuildImage(xsize, histo_bits, refs, image_out); |
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// Collapse similar histograms. |
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if (!HistogramCombine(image_out, image_in, num_histo_pairs)) { |
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goto Error; |
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} |
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// Find the optimal map from original histograms to the final ones. |
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HistogramRemap(image_out, image_in, histogram_symbols); |
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ok = 1; |
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Error: |
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free(image_out); |
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return ok; |
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}
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