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
This commit is contained in:
Vikas Arora 2014-03-03 13:49:54 -08:00
parent ca1bfff53f
commit b33e8a05ee
4 changed files with 157 additions and 102 deletions

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@ -436,7 +436,8 @@ static int CostModelBuild(CostModel* const m, int xsize, int ysize,
} }
VP8LHistogramCreate(&histo, &refs, cache_bits); VP8LHistogramCreate(&histo, &refs, cache_bits);
ConvertPopulationCountTableToBitEstimates( ConvertPopulationCountTableToBitEstimates(
VP8LHistogramNumCodes(&histo), histo.literal_, m->literal_); VP8LHistogramNumCodes(histo.palette_code_bits_),
histo.literal_, m->literal_);
ConvertPopulationCountTableToBitEstimates( ConvertPopulationCountTableToBitEstimates(
VALUES_IN_BYTE, histo.red_, m->red_); VALUES_IN_BYTE, histo.red_, m->red_);
ConvertPopulationCountTableToBitEstimates( ConvertPopulationCountTableToBitEstimates(

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@ -98,25 +98,9 @@ void VP8LHistogramAddSinglePixOrCopy(VP8LHistogram* const histo,
} }
} }
static double BitsEntropy(const int* const array, int n) { static WEBP_INLINE double BitsEntropyRefine(int nonzeros, int sum, int max_val,
double retval = 0.; double retval) {
int sum = 0;
int nonzeros = 0;
int max_val = 0;
int i;
double mix; 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 < 5) {
if (nonzeros <= 1) { if (nonzeros <= 1) {
return 0; return 0;
@ -147,42 +131,108 @@ static double BitsEntropy(const int* const array, int n) {
} }
} }
// Returns the cost encode the rle-encoded entropy code. static double BitsEntropy(const int* const array, int n) {
// The constants in this function are experimental. double retval = 0.;
static double HuffmanCost(const int* const population, int length) { int sum = 0;
int nonzeros = 0;
int max_val = 0;
int i;
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);
return BitsEntropyRefine(nonzeros, sum, max_val, retval);
}
static double BitsEntropyCombined(const int* const X, const int* const Y,
int n) {
double retval = 0.;
int sum = 0;
int nonzeros = 0;
int max_val = 0;
int i;
for (i = 0; i < n; ++i) {
const int xy = X[i] + Y[i];
if (xy != 0) {
sum += xy;
++nonzeros;
retval -= VP8LFastSLog2(xy);
if (max_val < xy) {
max_val = xy;
}
}
}
retval += VP8LFastSLog2(sum);
return BitsEntropyRefine(nonzeros, sum, max_val, retval);
}
static WEBP_INLINE double InitialHuffmanCost(void) {
// Small bias because Huffman code length is typically not stored in // Small bias because Huffman code length is typically not stored in
// full length. // full length.
static const int kHuffmanCodeOfHuffmanCodeSize = CODE_LENGTH_CODES * 3; static const int kHuffmanCodeOfHuffmanCodeSize = CODE_LENGTH_CODES * 3;
static const double kSmallBias = 9.1; static const double kSmallBias = 9.1;
double retval = kHuffmanCodeOfHuffmanCodeSize - kSmallBias; return kHuffmanCodeOfHuffmanCodeSize - kSmallBias;
}
static WEBP_INLINE double HuffmanCostRefine(int streak, int val) {
double retval;
if (streak > 3) {
if (val == 0) {
retval = 1.5625 + 0.234375 * streak;
} else {
retval = 2.578125 + 0.703125 * streak;
}
} else {
if (val == 0) {
retval = 1.796875 * streak;
} else {
retval = 3.28125 * streak;
}
}
return 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) {
int streak = 0; int streak = 0;
int i = 0; int i = 0;
double retval = InitialHuffmanCost();
for (; i < length - 1; ++i) { for (; i < length - 1; ++i) {
++streak; ++streak;
if (population[i] == population[i + 1]) { if (population[i] == population[i + 1]) {
continue; continue;
} }
last_streak_hack: retval += HuffmanCostRefine(streak, population[i]);
// 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; streak = 0;
} }
if (i == length - 1) { retval += HuffmanCostRefine(++streak, population[i]);
return retval;
}
static double HuffmanCostCombined(const int* const X, const int* const Y,
int length) {
int streak = 0;
int i = 0;
double retval = InitialHuffmanCost();
for (; i < length - 1; ++i) {
const int xy = X[i] + Y[i];
const int xy_next = X[i + 1] + Y[i + 1];
++streak; ++streak;
goto last_streak_hack; if (xy == xy_next) {
continue;
}
retval += HuffmanCostRefine(streak, xy);
streak = 0;
} }
retval += HuffmanCostRefine(++streak, X[i] + Y[i]);
return retval; return retval;
} }
@ -190,6 +240,12 @@ static double PopulationCost(const int* const population, int length) {
return BitsEntropy(population, length) + HuffmanCost(population, length); return BitsEntropy(population, length) + HuffmanCost(population, length);
} }
static double GetCombinedEntropy(const int* const X, const int* const Y,
int length) {
return BitsEntropyCombined(X, Y, length) + HuffmanCostCombined(X, Y, length);
}
static double ExtraCost(const int* const population, int length) { static double ExtraCost(const int* const population, int length) {
int i; int i;
double cost = 0.; double cost = 0.;
@ -197,9 +253,21 @@ static double ExtraCost(const int* const population, int length) {
return cost; return cost;
} }
static double ExtraCostCombined(const int* const X, const int* const Y,
int length) {
int i;
double cost = 0.;
for (i = 2; i < length - 2; ++i) {
const int xy = X[i + 2] + Y[i + 2];
cost += (i >> 1) * xy;
}
return cost;
}
// Estimates the Entropy + Huffman + other block overhead size cost. // Estimates the Entropy + Huffman + other block overhead size cost.
double VP8LHistogramEstimateBits(const VP8LHistogram* const p) { double VP8LHistogramEstimateBits(const VP8LHistogram* const p) {
return PopulationCost(p->literal_, VP8LHistogramNumCodes(p)) return
PopulationCost(p->literal_, VP8LHistogramNumCodes(p->palette_code_bits_))
+ PopulationCost(p->red_, 256) + PopulationCost(p->red_, 256)
+ PopulationCost(p->blue_, 256) + PopulationCost(p->blue_, 256)
+ PopulationCost(p->alpha_, 256) + PopulationCost(p->alpha_, 256)
@ -209,7 +277,8 @@ double VP8LHistogramEstimateBits(const VP8LHistogram* const p) {
} }
double VP8LHistogramEstimateBitsBulk(const VP8LHistogram* const p) { double VP8LHistogramEstimateBitsBulk(const VP8LHistogram* const p) {
return BitsEntropy(p->literal_, VP8LHistogramNumCodes(p)) return
BitsEntropy(p->literal_, VP8LHistogramNumCodes(p->palette_code_bits_))
+ BitsEntropy(p->red_, 256) + BitsEntropy(p->red_, 256)
+ BitsEntropy(p->blue_, 256) + BitsEntropy(p->blue_, 256)
+ BitsEntropy(p->alpha_, 256) + BitsEntropy(p->alpha_, 256)
@ -238,6 +307,35 @@ static void HistogramAdd(const VP8LHistogram* const in,
} }
} }
static int GetCombinedHistogramEntropy(const VP8LHistogram* const a,
const VP8LHistogram* const b,
double cost_threshold,
double* cost) {
const int palette_code_bits =
(a->palette_code_bits_ > b->palette_code_bits_) ? a->palette_code_bits_ :
b->palette_code_bits_;
*cost += GetCombinedEntropy(a->literal_, b->literal_,
VP8LHistogramNumCodes(palette_code_bits));
*cost += ExtraCostCombined(a->literal_ + 256, b->literal_ + 256,
NUM_LENGTH_CODES);
if (*cost > cost_threshold) return 0;
*cost += GetCombinedEntropy(a->red_, b->red_, 256);
if (*cost > cost_threshold) return 0;
*cost += GetCombinedEntropy(a->blue_, b->blue_, 256);
if (*cost > cost_threshold) return 0;
*cost += GetCombinedEntropy(a->distance_, b->distance_, NUM_DISTANCE_CODES);
*cost += ExtraCostCombined(a->distance_, b->distance_, NUM_DISTANCE_CODES);
if (*cost > cost_threshold) return 0;
*cost += GetCombinedEntropy(a->alpha_, b->alpha_, 256);
if (*cost > cost_threshold) return 0;
return 1;
}
// Performs out = a + b, computing the cost C(a+b) - C(a) - C(b) while comparing // 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 // 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. // Score = C(a+b) - C(a) - C(b), where C(a) + C(b) is known and fixed.
@ -251,40 +349,25 @@ static double HistogramAddEval(const VP8LHistogram* const a,
double cost = 0; double cost = 0;
const double sum_cost = a->bit_cost_ + b->bit_cost_; const double sum_cost = a->bit_cost_ + b->bit_cost_;
int i; int i;
cost_threshold += sum_cost; cost_threshold += sum_cost;
// palette_code_bits_ is part of the cost evaluation for literal_. if (GetCombinedHistogramEntropy(a, b, cost_threshold, &cost)) {
// 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) { for (i = 0; i < PIX_OR_COPY_CODES_MAX; ++i) {
out->literal_[i] = a->literal_[i] + b->literal_[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) { for (i = 0; i < NUM_DISTANCE_CODES; ++i) {
out->distance_[i] = a->distance_[i] + b->distance_[i]; out->distance_[i] = a->distance_[i] + b->distance_[i];
} }
cost += PopulationCost(out->distance_, NUM_DISTANCE_CODES); for (i = 0; i < 256; ++i) {
cost += ExtraCost(out->distance_, NUM_DISTANCE_CODES); out->red_[i] = a->red_[i] + b->red_[i];
if (cost > cost_threshold) return cost; out->blue_[i] = a->blue_[i] + b->blue_[i];
out->alpha_[i] = a->alpha_[i] + b->alpha_[i];
for (i = 0; i < 256; ++i) out->alpha_[i] = a->alpha_[i] + b->alpha_[i]; }
cost += PopulationCost(out->alpha_, 256); out->palette_code_bits_ = (a->palette_code_bits_ > b->palette_code_bits_) ?
a->palette_code_bits_ : b->palette_code_bits_;
out->bit_cost_ = cost; out->bit_cost_ = cost;
}
return cost - sum_cost; return cost - sum_cost;
} }
@ -294,37 +377,8 @@ static double HistogramAddEval(const VP8LHistogram* const a,
static double HistogramAddThresh(const VP8LHistogram* const a, static double HistogramAddThresh(const VP8LHistogram* const a,
const VP8LHistogram* const b, const VP8LHistogram* const b,
double cost_threshold) { double cost_threshold) {
int tmp[PIX_OR_COPY_CODES_MAX]; // <= max storage we'll need
int i;
double cost = -a->bit_cost_; double cost = -a->bit_cost_;
GetCombinedHistogramEntropy(a, b, cost_threshold, &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; return cost;
} }

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@ -82,9 +82,9 @@ double VP8LHistogramEstimateBits(const VP8LHistogram* const p);
// represent the entropy code itself. // represent the entropy code itself.
double VP8LHistogramEstimateBitsBulk(const VP8LHistogram* const p); double VP8LHistogramEstimateBitsBulk(const VP8LHistogram* const p);
static WEBP_INLINE int VP8LHistogramNumCodes(const VP8LHistogram* const p) { static WEBP_INLINE int VP8LHistogramNumCodes(int palette_code_bits) {
return 256 + NUM_LENGTH_CODES + return 256 + NUM_LENGTH_CODES +
((p->palette_code_bits_ > 0) ? (1 << p->palette_code_bits_) : 0); ((palette_code_bits > 0) ? (1 << palette_code_bits) : 0);
} }
// Builds the histogram image. // Builds the histogram image.

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@ -186,9 +186,9 @@ static int GetHuffBitLengthsAndCodes(
const VP8LHistogram* const histo = histogram_image->histograms[i]; const VP8LHistogram* const histo = histogram_image->histograms[i];
HuffmanTreeCode* const codes = &huffman_codes[5 * i]; HuffmanTreeCode* const codes = &huffman_codes[5 * i];
for (k = 0; k < 5; ++k) { for (k = 0; k < 5; ++k) {
const int num_symbols = (k == 0) ? VP8LHistogramNumCodes(histo) const int num_symbols =
: (k == 4) ? NUM_DISTANCE_CODES (k == 0) ? VP8LHistogramNumCodes(histo->palette_code_bits_) :
: 256; (k == 4) ? NUM_DISTANCE_CODES : 256;
codes[k].num_symbols = num_symbols; codes[k].num_symbols = num_symbols;
total_length_size += num_symbols; total_length_size += num_symbols;
} }