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rewrite the bin_map clustering to use less memory

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output should bit-write the same as before, in both
low_effort and non low_effort modes.

if anything, speed is a tad faster, probably because of the
reduced memory traffic.

Change-Id: Iaa2ddcfda2aaffefe7e5b7bc89216373d1ddb194
This commit is contained in:
Pascal Massimino 2016-06-17 09:52:36 +02:00
parent 6a9c262aa8
commit 3591ba6684
1 changed files with 27 additions and 42 deletions
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69
src/enc/histogram.c
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@ -450,33 +450,23 @@ static void HistogramCopyAndAnalyze(
// Partition histograms to different entropy bins for three dominant (literal,
// red and blue) symbol costs and compute the histogram aggregate bit_cost.
static void HistogramAnalyzeEntropyBin(VP8LHistogramSet* const image_histo,
int16_t* const bin_map, int low_effort) {
uint16_t* const bin_map,
int low_effort) {
int i;
VP8LHistogram** const histograms = image_histo->histograms;
const int histo_size = image_histo->size;
const int bin_depth = histo_size + 1;
DominantCostRange cost_range;
DominantCostRangeInit(&cost_range);
// Analyze the dominant (literal, red and blue) entropy costs.
for (i = 0; i < histo_size; ++i) {
VP8LHistogram* const histo = histograms[i];
UpdateDominantCostRange(histo, &cost_range);
UpdateDominantCostRange(histograms[i], &cost_range);
}
// bin-hash histograms on three of the dominant (literal, red and blue)
// symbol costs.
// symbol costs and store the resulting bin_id for each histogram.
for (i = 0; i < histo_size; ++i) {
const VP8LHistogram* const histo = histograms[i];
const int bin_id = GetHistoBinIndex(histo, &cost_range, low_effort);
const int bin_offset = bin_id * bin_depth;
// bin_map[n][0] for every bin 'n' maintains the counter for the number of
// histograms in that bin.
// Get and increment the num_histos in that bin.
const int num_histos = ++bin_map[bin_offset];
assert(bin_offset + num_histos < bin_depth * BIN_SIZE);
// Add histogram i'th index at num_histos (last) position in the bin_map.
bin_map[bin_offset + num_histos] = i;
bin_map[i] = GetHistoBinIndex(histograms[i], &cost_range, low_effort);
}
}
@ -500,19 +490,21 @@ static void HistogramCompactBins(VP8LHistogramSet* const image_histo) {
static VP8LHistogram* HistogramCombineEntropyBin(
VP8LHistogramSet* const image_histo,
VP8LHistogram* cur_combo,
int16_t* const bin_map, int bin_depth, int num_bins,
uint16_t* const bin_map, int bin_map_size, int num_bins,
double combine_cost_factor, int low_effort) {
int bin_id;
VP8LHistogram** const histograms = image_histo->histograms;
int bin_id;
for (bin_id = 0; bin_id < num_bins; ++bin_id) {
const int bin_offset = bin_id * bin_depth;
const int num_histos = bin_map[bin_offset];
const int idx1 = bin_map[bin_offset + 1];
int num_combine_failures = 0;
int n;
for (n = 2; n <= num_histos; ++n) {
const int idx2 = bin_map[bin_offset + n];
int idx1, idx2;
for (idx1 = 0; idx1 < bin_map_size; ++idx1) {
if (bin_map[idx1] == bin_id) break;
}
if (idx1 == bin_map_size) continue; // no histo with this bin_id
for (idx2 = idx1 + 1; idx2 < bin_map_size; ++idx2) {
if (bin_map[idx2] != bin_id) continue;
// try to merge #idx2 into #idx1 (both share the same bin_id)
if (low_effort) {
// Merge all histograms with the same bin index, irrespective of cost of
// the merged histograms.
@ -870,30 +862,17 @@ int VP8LGetHistoImageSymbols(int xsize, int ysize,
const int image_histo_raw_size = histo_xsize * histo_ysize;
const int entropy_combine_num_bins = low_effort ? NUM_PARTITIONS : BIN_SIZE;
// The bin_map for every bin follows following semantics:
// bin_map[n][0] = num_histo; // The number of histograms in that bin.
// bin_map[n][1] = index of first histogram in that bin;
// bin_map[n][num_histo] = index of last histogram in that bin;
// bin_map[n][num_histo + 1] ... bin_map[n][bin_depth - 1] = unused indices.
const int bin_depth = image_histo_raw_size + 1;
int16_t* bin_map = NULL;
VP8LHistogramSet* const orig_histo =
VP8LAllocateHistogramSet(image_histo_raw_size, cache_bits);
VP8LHistogram* cur_combo;
// Don't attempt linear bin-partition heuristic for
// histograms of small sizes (as bin_map will be very sparse) and
// maximum quality q==100 (to preserve the compression gains at that level).
const int entropy_combine =
(orig_histo->size > entropy_combine_num_bins * 2) && (quality < 100);
if (orig_histo == NULL) goto Error;
// Don't attempt linear bin-partition heuristic for:
// histograms of small sizes, as bin_map will be very sparse and;
// Maximum quality (q==100), to preserve the compression gains at that level.
if (entropy_combine) {
const int bin_map_size = bin_depth * entropy_combine_num_bins;
bin_map = (int16_t*)WebPSafeCalloc(bin_map_size, sizeof(*bin_map));
if (bin_map == NULL) goto Error;
}
// Construct the histograms from backward references.
HistogramBuild(xsize, histo_bits, refs, orig_histo);
// Copies the histograms and computes its bit_cost.
@ -901,13 +880,20 @@ int VP8LGetHistoImageSymbols(int xsize, int ysize,
cur_combo = tmp_histos->histograms[1]; // pick up working slot
if (entropy_combine) {
const int bin_map_size = orig_histo->size;
const double combine_cost_factor =
GetCombineCostFactor(image_histo_raw_size, quality);
uint16_t* const bin_map =
(uint16_t*)WebPSafeCalloc(bin_map_size, sizeof(*bin_map));
if (bin_map == NULL) goto Error;
HistogramAnalyzeEntropyBin(orig_histo, bin_map, low_effort);
// Collapse histograms with similar entropy.
cur_combo = HistogramCombineEntropyBin(image_histo, cur_combo, bin_map,
bin_depth, entropy_combine_num_bins,
cur_combo = HistogramCombineEntropyBin(image_histo, cur_combo,
bin_map, bin_map_size,
entropy_combine_num_bins,
combine_cost_factor, low_effort);
WebPSafeFree(bin_map);
}
// Don't combine the histograms using stochastic and greedy heuristics for
@ -931,7 +917,6 @@ int VP8LGetHistoImageSymbols(int xsize, int ysize,
ok = 1;
Error:
WebPSafeFree(bin_map);
VP8LFreeHistogramSet(orig_histo);
return ok;
}