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