godot/drivers/webpold/enc/histogram.c
Juan Linietsky da113fe40d -Upgraded webp to a MUCH newer version. Hoping it fixes some bugs in the process. Keeping old version just in case for now.
-Added ability to convert xml and tscn scenes to binary on export, makes loading of larger scenes faster
2015-12-04 10:18:28 -03:00

407 lines
13 KiB
C

// Copyright 2012 Google Inc. All Rights Reserved.
//
// This code is licensed under the same terms as WebM:
// Software License Agreement: http://www.webmproject.org/license/software/
// Additional IP Rights Grant: http://www.webmproject.org/license/additional/
// -----------------------------------------------------------------------------
//
// Author: Jyrki Alakuijala (jyrki@google.com)
//
#ifdef HAVE_CONFIG_H
#include "config.h"
#endif
#include <math.h>
#include <stdio.h>
#include "./backward_references.h"
#include "./histogram.h"
#include "../dsp/lossless.h"
#include "../utils/utils.h"
static void HistogramClear(VP8LHistogram* const p) {
memset(p->literal_, 0, sizeof(p->literal_));
memset(p->red_, 0, sizeof(p->red_));
memset(p->blue_, 0, sizeof(p->blue_));
memset(p->alpha_, 0, sizeof(p->alpha_));
memset(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 = (uint64_t)sizeof(*set)
+ size * sizeof(*set->histograms)
+ 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;
}
}
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) {
// 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;
}
// 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);
}
double VP8LHistogramEstimateBits(const VP8LHistogram* const p) {
return HistogramEstimateBitsHeader(p) + VP8LHistogramEstimateBitsBulk(p);
}
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;
assert(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 num_pairs) {
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;
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
if (histos == NULL) goto End;
// Copy histograms from in[] to out[].
assert(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) {
// 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 j;
seed += iter;
for (j = 0; j < num_pairs; ++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 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?
{ // 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_cost_diff < 0.0) {
*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 >= 50) {
break;
}
}
out->size = out_size;
ok = 1;
End:
free(histos);
return ok;
}
// -----------------------------------------------------------------------------
// 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.
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;
}
// 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]);
int k;
for (k = 1; k < out->size; ++k) {
const double cur_bits =
HistogramDistance(in->histograms[i], out->histograms[k]);
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) {
VP8LHistogramAdd(out->histograms[symbols[i]], in->histograms[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 num_histo_pairs = 10 + quality / 2; // For HistogramCombine().
const int histo_image_raw_size = histo_xsize * histo_ysize;
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, num_histo_pairs)) {
goto Error;
}
// Find the optimal map from original histograms to the final ones.
HistogramRemap(image_out, image_in, histogram_symbols);
ok = 1;
Error:
free(image_out);
return ok;
}