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synced 2024-11-20 04:18:26 +01:00
Refactor code for HistogramCombine.
Refactor code for HistogramCombine and optimize the code by calculating the combined entropy and avoid un-necessary Histogram merges. This speeds up lossless encoding by 1-2% and almost no impact on compression density. Change-Id: Iedfcf4c1f3e88077bc77fc7b8c780c4cd5d6362b
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ca1bfff53f
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@ -436,7 +436,8 @@ static int CostModelBuild(CostModel* const m, int xsize, int ysize,
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}
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VP8LHistogramCreate(&histo, &refs, cache_bits);
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ConvertPopulationCountTableToBitEstimates(
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VP8LHistogramNumCodes(&histo), histo.literal_, m->literal_);
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VP8LHistogramNumCodes(histo.palette_code_bits_),
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histo.literal_, m->literal_);
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ConvertPopulationCountTableToBitEstimates(
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VALUES_IN_BYTE, histo.red_, m->red_);
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ConvertPopulationCountTableToBitEstimates(
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@ -98,25 +98,9 @@ void VP8LHistogramAddSinglePixOrCopy(VP8LHistogram* const histo,
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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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static WEBP_INLINE double BitsEntropyRefine(int nonzeros, int sum, int max_val,
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double retval) {
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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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@ -147,42 +131,108 @@ static double BitsEntropy(const int* const array, int n) {
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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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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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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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return BitsEntropyRefine(nonzeros, sum, max_val, retval);
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}
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static double BitsEntropyCombined(const int* const X, const int* const Y,
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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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for (i = 0; i < n; ++i) {
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const int xy = X[i] + Y[i];
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if (xy != 0) {
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sum += xy;
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++nonzeros;
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retval -= VP8LFastSLog2(xy);
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if (max_val < xy) {
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max_val = xy;
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}
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}
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}
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retval += VP8LFastSLog2(sum);
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return BitsEntropyRefine(nonzeros, sum, max_val, retval);
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}
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static WEBP_INLINE double InitialHuffmanCost(void) {
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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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return kHuffmanCodeOfHuffmanCodeSize - kSmallBias;
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}
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static WEBP_INLINE double HuffmanCostRefine(int streak, int val) {
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double retval;
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if (streak > 3) {
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if (val == 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 (val == 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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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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int streak = 0;
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int i = 0;
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double retval = InitialHuffmanCost();
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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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retval += HuffmanCostRefine(streak, population[i]);
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streak = 0;
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}
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if (i == length - 1) {
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retval += HuffmanCostRefine(++streak, population[i]);
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return retval;
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}
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static double HuffmanCostCombined(const int* const X, const int* const Y,
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int length) {
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int streak = 0;
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int i = 0;
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double retval = InitialHuffmanCost();
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for (; i < length - 1; ++i) {
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const int xy = X[i] + Y[i];
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const int xy_next = X[i + 1] + Y[i + 1];
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++streak;
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goto last_streak_hack;
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if (xy == xy_next) {
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continue;
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}
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retval += HuffmanCostRefine(streak, xy);
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streak = 0;
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}
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retval += HuffmanCostRefine(++streak, X[i] + Y[i]);
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return retval;
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}
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@ -190,6 +240,12 @@ 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 GetCombinedEntropy(const int* const X, const int* const Y,
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int length) {
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return BitsEntropyCombined(X, Y, length) + HuffmanCostCombined(X, Y, 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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@ -197,9 +253,21 @@ static double ExtraCost(const int* const population, int length) {
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return cost;
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}
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static double ExtraCostCombined(const int* const X, const int* const Y,
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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) {
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const int xy = X[i + 2] + Y[i + 2];
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cost += (i >> 1) * xy;
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}
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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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return
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PopulationCost(p->literal_, VP8LHistogramNumCodes(p->palette_code_bits_))
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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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@ -209,7 +277,8 @@ double VP8LHistogramEstimateBits(const VP8LHistogram* const p) {
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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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return
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BitsEntropy(p->literal_, VP8LHistogramNumCodes(p->palette_code_bits_))
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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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@ -238,6 +307,35 @@ static void HistogramAdd(const VP8LHistogram* const in,
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}
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}
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static int GetCombinedHistogramEntropy(const VP8LHistogram* const a,
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const VP8LHistogram* const b,
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double cost_threshold,
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double* cost) {
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const int 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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*cost += GetCombinedEntropy(a->literal_, b->literal_,
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VP8LHistogramNumCodes(palette_code_bits));
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*cost += ExtraCostCombined(a->literal_ + 256, b->literal_ + 256,
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NUM_LENGTH_CODES);
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if (*cost > cost_threshold) return 0;
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*cost += GetCombinedEntropy(a->red_, b->red_, 256);
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if (*cost > cost_threshold) return 0;
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*cost += GetCombinedEntropy(a->blue_, b->blue_, 256);
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if (*cost > cost_threshold) return 0;
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*cost += GetCombinedEntropy(a->distance_, b->distance_, NUM_DISTANCE_CODES);
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*cost += ExtraCostCombined(a->distance_, b->distance_, NUM_DISTANCE_CODES);
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if (*cost > cost_threshold) return 0;
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*cost += GetCombinedEntropy(a->alpha_, b->alpha_, 256);
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if (*cost > cost_threshold) return 0;
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return 1;
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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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@ -251,40 +349,25 @@ static double HistogramAddEval(const VP8LHistogram* const a,
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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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if (GetCombinedHistogramEntropy(a, b, cost_threshold, &cost)) {
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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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for (i = 0; i < 256; ++i) {
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out->red_[i] = a->red_[i] + b->red_[i];
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out->blue_[i] = a->blue_[i] + b->blue_[i];
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out->alpha_[i] = a->alpha_[i] + b->alpha_[i];
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}
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out->palette_code_bits_ = (a->palette_code_bits_ > b->palette_code_bits_) ?
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a->palette_code_bits_ : b->palette_code_bits_;
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out->bit_cost_ = cost;
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}
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return cost - sum_cost;
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}
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@ -294,37 +377,8 @@ static double HistogramAddEval(const VP8LHistogram* const a,
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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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GetCombinedHistogramEntropy(a, b, cost_threshold, &cost);
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return cost;
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}
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@ -82,9 +82,9 @@ double VP8LHistogramEstimateBits(const VP8LHistogram* const p);
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// represent the entropy code itself.
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double VP8LHistogramEstimateBitsBulk(const VP8LHistogram* const p);
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static WEBP_INLINE int VP8LHistogramNumCodes(const VP8LHistogram* const p) {
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static WEBP_INLINE int VP8LHistogramNumCodes(int palette_code_bits) {
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return 256 + NUM_LENGTH_CODES +
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((p->palette_code_bits_ > 0) ? (1 << p->palette_code_bits_) : 0);
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((palette_code_bits > 0) ? (1 << palette_code_bits) : 0);
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}
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// Builds the histogram image.
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@ -186,9 +186,9 @@ static int GetHuffBitLengthsAndCodes(
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const VP8LHistogram* const histo = histogram_image->histograms[i];
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HuffmanTreeCode* const codes = &huffman_codes[5 * i];
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for (k = 0; k < 5; ++k) {
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const int num_symbols = (k == 0) ? VP8LHistogramNumCodes(histo)
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: (k == 4) ? NUM_DISTANCE_CODES
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: 256;
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const int num_symbols =
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(k == 0) ? VP8LHistogramNumCodes(histo->palette_code_bits_) :
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(k == 4) ? NUM_DISTANCE_CODES : 256;
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codes[k].num_symbols = num_symbols;
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total_length_size += num_symbols;
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}
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