generic-library/opencv
1
0
Fork 0
Code Issues Pull Requests Releases Wiki Activity

update libwebp up to 0.3.0

Browse Source
This commit is contained in:
AoD314
2013-04-02 15:22:10 +04:00
parent db45e04d58
commit 740941c8b8
64 changed files with 5394 additions and 2773 deletions
Download Patch File Download Diff File Expand all files Collapse all files

234
3rdparty/libwebp/enc/histogram.c vendored
View File

@@ -98,8 +98,6 @@ void VP8LHistogramAddSinglePixOrCopy(VP8LHistogram* const histo,
}
}
static double BitsEntropy(const int* const array, int n) {
double retval = 0.;
int sum = 0;
@@ -149,25 +147,6 @@ static double BitsEntropy(const int* const array, int n) {
}
}
double VP8LHistogramEstimateBitsBulk(const VP8LHistogram* const p) {
double retval = BitsEntropy(&p->literal_[0], VP8LHistogramNumCodes(p))
+ BitsEntropy(&p->red_[0], 256)
+ BitsEntropy(&p->blue_[0], 256)
+ BitsEntropy(&p->alpha_[0], 256)
+ BitsEntropy(&p->distance_[0], NUM_DISTANCE_CODES);
// Compute the extra bits cost.
int i;
for (i = 2; i < NUM_LENGTH_CODES - 2; ++i) {
retval +=
(i >> 1) * p->literal_[256 + i + 2];
}
for (i = 2; i < NUM_DISTANCE_CODES - 2; ++i) {
retval += (i >> 1) * p->distance_[i + 2];
}
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) {
@@ -207,19 +186,150 @@ static double HuffmanCost(const int* const population, int length) {
return retval;
}
// Estimates the Huffman dictionary + other block overhead size.
static double HistogramEstimateBitsHeader(const VP8LHistogram* const p) {
return HuffmanCost(&p->alpha_[0], 256) +
HuffmanCost(&p->red_[0], 256) +
HuffmanCost(&p->literal_[0], VP8LHistogramNumCodes(p)) +
HuffmanCost(&p->blue_[0], 256) +
HuffmanCost(&p->distance_[0], NUM_DISTANCE_CODES);
static double PopulationCost(const int* const population, int length) {
return BitsEntropy(population, length) + HuffmanCost(population, length);
}
double VP8LHistogramEstimateBits(const VP8LHistogram* const p) {
return HistogramEstimateBitsHeader(p) + VP8LHistogramEstimateBitsBulk(p);
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) {
@@ -249,14 +359,15 @@ static uint32_t MyRand(uint32_t *seed) {
}
static int HistogramCombine(const VP8LHistogramSet* const in,
VP8LHistogramSet* const out, int num_pairs) {
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;
const int min_cluster_size = 2;
int out_size = in->size;
const int outer_iters = in->size * 3;
const int outer_iters = in->size * iter_mult;
const int min_cluster_size = 2;
VP8LHistogram* const histos = (VP8LHistogram*)malloc(2 * sizeof(*histos));
VP8LHistogram* cur_combo = histos + 0; // trial merged histogram
VP8LHistogram* best_combo = histos + 1; // best merged histogram so far
@@ -271,29 +382,26 @@ static int HistogramCombine(const VP8LHistogramSet* const in,
// Collapse similar histograms in 'out'.
for (iter = 0; iter < outer_iters && out_size >= min_cluster_size; ++iter) {
// We pick the best pair to be combined out of 'inner_iters' pairs.
double best_cost_diff = 0.;
int best_idx1 = 0, best_idx2 = 1;
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_pairs; ++j) {
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) % (out_size - 1);
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;
}
*cur_combo = *out->histograms[idx1];
VP8LHistogramAdd(cur_combo, out->histograms[idx2]);
cur_combo->bit_cost_ = VP8LHistogramEstimateBits(cur_combo);
// Calculate cost reduction on combining.
curr_cost_diff = cur_combo->bit_cost_
- out->histograms[idx1]->bit_cost_
- out->histograms[idx2]->bit_cost_;
if (best_cost_diff > curr_cost_diff) { // found a better pair?
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;
@@ -305,7 +413,7 @@ static int HistogramCombine(const VP8LHistogramSet* const in,
}
}
if (best_cost_diff < 0.0) {
if (best_idx1 >= 0) {
*out->histograms[best_idx1] = *best_combo;
// swap best_idx2 slot with last one (which is now unused)
--out_size;
@@ -315,7 +423,7 @@ static int HistogramCombine(const VP8LHistogramSet* const in,
}
tries_with_no_success = 0;
}
if (++tries_with_no_success >= 50) {
if (++tries_with_no_success >= num_tries_no_success) {
break;
}
}
@@ -330,20 +438,11 @@ static int HistogramCombine(const VP8LHistogramSet* const in,
// -----------------------------------------------------------------------------
// Histogram refinement
// What is the bit cost of moving square_histogram from
// cur_symbol to candidate_symbol.
// TODO(skal): we don't really need to copy the histogram and Add(). Instead
// we just need VP8LDualHistogramEstimateBits(A, B) estimation function.
// 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) {
const double previous_bit_cost = candidate->bit_cost_;
double new_bit_cost;
VP8LHistogram modified_histo;
modified_histo = *candidate;
VP8LHistogramAdd(&modified_histo, square_histogram);
new_bit_cost = VP8LHistogramEstimateBits(&modified_histo);
return new_bit_cost - previous_bit_cost;
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.
@@ -354,11 +453,12 @@ static void HistogramRemap(const VP8LHistogramSet* const in,
int i;
for (i = 0; i < in->size; ++i) {
int best_out = 0;
double best_bits = HistogramDistance(in->histograms[i], out->histograms[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]);
HistogramDistance(in->histograms[i], out->histograms[k], best_bits);
if (cur_bits < best_bits) {
best_bits = cur_bits;
best_out = k;
@@ -372,7 +472,7 @@ static void HistogramRemap(const VP8LHistogramSet* const in,
HistogramClear(out->histograms[i]);
}
for (i = 0; i < in->size; ++i) {
VP8LHistogramAdd(out->histograms[symbols[i]], in->histograms[i]);
HistogramAdd(in->histograms[i], out->histograms[symbols[i]]);
}
}
@@ -384,8 +484,13 @@ int VP8LGetHistoImageSymbols(int xsize, int ysize,
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 num_histo_pairs = 10 + quality / 2; // For HistogramCombine().
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;
@@ -393,7 +498,8 @@ int VP8LGetHistoImageSymbols(int xsize, int ysize,
// Build histogram image.
HistogramBuildImage(xsize, histo_bits, refs, image_out);
// Collapse similar histograms.
if (!HistogramCombine(image_out, image_in, num_histo_pairs)) {
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.