public double AddThresh(Vp8LHistogram b, Vp8LStreaks stats, Vp8LBitEntropy bitsEntropy, double costThreshold)
{
double costInitial = -this.BitCost;
this.GetCombinedHistogramEntropy(b, stats, bitsEntropy, costThreshold, costInitial, out double cost);
return(cost);
}
private static int HistogramCopyAndAnalyze(List <Vp8LHistogram> origHistograms, List <Vp8LHistogram> histograms, ushort[] histogramSymbols)
{
var stats = new Vp8LStreaks();
var bitsEntropy = new Vp8LBitEntropy();
for (int clusterId = 0, i = 0; i < origHistograms.Count; i++)
{
Vp8LHistogram origHistogram = origHistograms[i];
origHistogram.UpdateHistogramCost(stats, bitsEntropy);
// Skip the histogram if it is completely empty, which can happen for tiles with no information (when they are skipped because of LZ77).
if (!origHistogram.IsUsed[0] && !origHistogram.IsUsed[1] && !origHistogram.IsUsed[2] && !origHistogram.IsUsed[3] && !origHistogram.IsUsed[4])
{
origHistograms[i] = null;
histograms[i] = null;
histogramSymbols[i] = InvalidHistogramSymbol;
}
else
{
histograms[i] = (Vp8LHistogram)origHistogram.DeepClone();
histogramSymbols[i] = (ushort)clusterId++;
}
}
int numUsed = histogramSymbols.Count(h => h != InvalidHistogramSymbol);
return(numUsed);
}
/// <summary>
/// Update the cost diff and combo of a pair of histograms. This needs to be called when the the histograms have been merged with a third one.
/// </summary>
private static void HistoListUpdatePair(Vp8LHistogram h1, Vp8LHistogram h2, Vp8LStreaks stats, Vp8LBitEntropy bitsEntropy, double threshold, HistogramPair pair)
{
double sumCost = h1.BitCost + h2.BitCost;
pair.CostCombo = 0.0d;
h1.GetCombinedHistogramEntropy(h2, stats, bitsEntropy, sumCost + threshold, costInitial: pair.CostCombo, out double cost);
pair.CostCombo = cost;
pair.CostDiff = pair.CostCombo - sumCost;
}
/// <summary>
/// Estimate how many bits the combined entropy of literals and distance approximately maps to.
/// </summary>
/// <returns>Estimated bits.</returns>
public double EstimateBits(Vp8LStreaks stats, Vp8LBitEntropy bitsEntropy)
{
uint notUsed = 0;
return
(PopulationCost(this.Literal, this.NumCodes(), ref notUsed, ref this.IsUsed[0], stats, bitsEntropy)
+ PopulationCost(this.Red, WebpConstants.NumLiteralCodes, ref notUsed, ref this.IsUsed[1], stats, bitsEntropy)
+ PopulationCost(this.Blue, WebpConstants.NumLiteralCodes, ref notUsed, ref this.IsUsed[2], stats, bitsEntropy)
+ PopulationCost(this.Alpha, WebpConstants.NumLiteralCodes, ref notUsed, ref this.IsUsed[3], stats, bitsEntropy)
+ PopulationCost(this.Distance, WebpConstants.NumDistanceCodes, ref notUsed, ref this.IsUsed[4], stats, bitsEntropy)
+ ExtraCost(this.Literal.AsSpan(WebpConstants.NumLiteralCodes), WebpConstants.NumLengthCodes)
+ ExtraCost(this.Distance, WebpConstants.NumDistanceCodes));
}
/// <summary>
/// Performs output = a + b, computing the cost C(a+b) - C(a) - C(b) while comparing
/// to the threshold value 'costThreshold'. 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 'costThreshold', we only need to compare
/// the partial cost against 'costThreshold + C(a) + C(b)' to possibly bail-out early.
/// </summary>
public double AddEval(Vp8LHistogram b, Vp8LStreaks stats, Vp8LBitEntropy bitsEntropy, double costThreshold, Vp8LHistogram output)
{
double sumCost = this.BitCost + b.BitCost;
costThreshold += sumCost;
if (this.GetCombinedHistogramEntropy(b, stats, bitsEntropy, costThreshold, costInitial: 0, out double cost))
{
this.Add(b, output);
output.BitCost = cost;
output.PaletteCodeBits = this.PaletteCodeBits;
}
return(cost - sumCost);
}
public void GetEntropyUnrefined(uint[] x, int length, Vp8LStreaks stats)
{
int i;
int iPrev = 0;
uint xPrev = x[0];
this.Init();
for (i = 1; i < length; i++)
{
uint xi = x[i];
if (xi != xPrev)
{
this.GetEntropyUnrefined(xi, i, ref xPrev, ref iPrev, stats);
}
}
this.GetEntropyUnrefined(0, i, ref xPrev, ref iPrev, stats);
this.Entropy += LosslessUtils.FastSLog2(this.Sum);
}
public void UpdateHistogramCost(Vp8LStreaks stats, Vp8LBitEntropy bitsEntropy)
{
uint alphaSym = 0, redSym = 0, blueSym = 0;
uint notUsed = 0;
double alphaCost = PopulationCost(this.Alpha, WebpConstants.NumLiteralCodes, ref alphaSym, ref this.IsUsed[3], stats, bitsEntropy);
double distanceCost = PopulationCost(this.Distance, WebpConstants.NumDistanceCodes, ref notUsed, ref this.IsUsed[4], stats, bitsEntropy) + ExtraCost(this.Distance, WebpConstants.NumDistanceCodes);
int numCodes = this.NumCodes();
this.LiteralCost = PopulationCost(this.Literal, numCodes, ref notUsed, ref this.IsUsed[0], stats, bitsEntropy) + ExtraCost(this.Literal.AsSpan(WebpConstants.NumLiteralCodes), WebpConstants.NumLengthCodes);
this.RedCost = PopulationCost(this.Red, WebpConstants.NumLiteralCodes, ref redSym, ref this.IsUsed[1], stats, bitsEntropy);
this.BlueCost = PopulationCost(this.Blue, WebpConstants.NumLiteralCodes, ref blueSym, ref this.IsUsed[2], stats, bitsEntropy);
this.BitCost = this.LiteralCost + this.RedCost + this.BlueCost + alphaCost + distanceCost;
if ((alphaSym | redSym | blueSym) == NonTrivialSym)
{
this.TrivialSymbol = NonTrivialSym;
}
else
{
this.TrivialSymbol = (alphaSym << 24) | (redSym << 16) | (blueSym << 0);
}
}
/// <summary>
/// Evaluates best possible backward references for specified quality. The input cacheBits to 'GetBackwardReferences'
/// sets the maximum cache bits to use (passing 0 implies disabling the local color cache).
/// The optimal cache bits is evaluated and set for the cacheBits parameter.
/// The return value is the pointer to the best of the two backward refs viz, refs[0] or refs[1].
/// </summary>
public static Vp8LBackwardRefs GetBackwardReferences(
int width,
int height,
ReadOnlySpan <uint> bgra,
int quality,
int lz77TypesToTry,
ref int cacheBits,
MemoryAllocator memoryAllocator,
Vp8LHashChain hashChain,
Vp8LBackwardRefs best,
Vp8LBackwardRefs worst)
{
int lz77TypeBest = 0;
double bitCostBest = -1;
int cacheBitsInitial = cacheBits;
Vp8LHashChain hashChainBox = null;
var stats = new Vp8LStreaks();
var bitsEntropy = new Vp8LBitEntropy();
for (int lz77Type = 1; lz77TypesToTry > 0; lz77TypesToTry &= ~lz77Type, lz77Type <<= 1)
{
int cacheBitsTmp = cacheBitsInitial;
if ((lz77TypesToTry & lz77Type) == 0)
{
continue;
}
switch ((Vp8LLz77Type)lz77Type)
{
case Vp8LLz77Type.Lz77Rle:
BackwardReferencesRle(width, height, bgra, 0, worst);
break;
case Vp8LLz77Type.Lz77Standard:
// Compute LZ77 with no cache (0 bits), as the ideal LZ77 with a color cache is not that different in practice.
BackwardReferencesLz77(width, height, bgra, 0, hashChain, worst);
break;
case Vp8LLz77Type.Lz77Box:
hashChainBox = new Vp8LHashChain(memoryAllocator, width * height);
BackwardReferencesLz77Box(width, height, bgra, 0, hashChain, hashChainBox, worst);
break;
}
// Next, try with a color cache and update the references.
cacheBitsTmp = CalculateBestCacheSize(bgra, quality, worst, cacheBitsTmp);
if (cacheBitsTmp > 0)
{
BackwardRefsWithLocalCache(bgra, cacheBitsTmp, worst);
}
// Keep the best backward references.
var histo = new Vp8LHistogram(worst, cacheBitsTmp);
double bitCost = histo.EstimateBits(stats, bitsEntropy);
if (lz77TypeBest == 0 || bitCost < bitCostBest)
{
Vp8LBackwardRefs tmp = worst;
worst = best;
best = tmp;
bitCostBest = bitCost;
cacheBits = cacheBitsTmp;
lz77TypeBest = lz77Type;
}
}
// Improve on simple LZ77 but only for high quality (TraceBackwards is costly).
if ((lz77TypeBest == (int)Vp8LLz77Type.Lz77Standard || lz77TypeBest == (int)Vp8LLz77Type.Lz77Box) && quality >= 25)
{
Vp8LHashChain hashChainTmp = lz77TypeBest == (int)Vp8LLz77Type.Lz77Standard ? hashChain : hashChainBox;
BackwardReferencesTraceBackwards(width, height, memoryAllocator, bgra, cacheBits, hashChainTmp, best, worst);
var histo = new Vp8LHistogram(worst, cacheBits);
double bitCostTrace = histo.EstimateBits(stats, bitsEntropy);
if (bitCostTrace < bitCostBest)
{
best = worst;
}
}
BackwardReferences2DLocality(width, best);
hashChainBox?.Dispose();
return(best);
}
/// <summary>
/// Evaluate optimal cache bits for the local color cache.
/// The input bestCacheBits sets the maximum cache bits to use (passing 0 implies disabling the local color cache).
/// The local color cache is also disabled for the lower (smaller then 25) quality.
/// </summary>
/// <returns>Best cache size.</returns>
private static int CalculateBestCacheSize(ReadOnlySpan <uint> bgra, int quality, Vp8LBackwardRefs refs, int bestCacheBits)
{
int cacheBitsMax = quality <= 25 ? 0 : bestCacheBits;
if (cacheBitsMax == 0)
{
// Local color cache is disabled.
return(0);
}
double entropyMin = MaxEntropy;
int pos = 0;
var colorCache = new ColorCache[WebpConstants.MaxColorCacheBits + 1];
var histos = new Vp8LHistogram[WebpConstants.MaxColorCacheBits + 1];
for (int i = 0; i <= WebpConstants.MaxColorCacheBits; i++)
{
histos[i] = new Vp8LHistogram(paletteCodeBits: i);
colorCache[i] = new ColorCache();
colorCache[i].Init(i);
}
// Find the cacheBits giving the lowest entropy.
for (int idx = 0; idx < refs.Refs.Count; idx++)
{
PixOrCopy v = refs.Refs[idx];
if (v.IsLiteral())
{
uint pix = bgra[pos++];
uint a = (pix >> 24) & 0xff;
uint r = (pix >> 16) & 0xff;
uint g = (pix >> 8) & 0xff;
uint b = (pix >> 0) & 0xff;
// The keys of the caches can be derived from the longest one.
int key = ColorCache.HashPix(pix, 32 - cacheBitsMax);
// Do not use the color cache for cacheBits = 0.
++histos[0].Blue[b];
++histos[0].Literal[g];
++histos[0].Red[r];
++histos[0].Alpha[a];
// Deal with cacheBits > 0.
for (int i = cacheBitsMax; i >= 1; --i, key >>= 1)
{
if (colorCache[i].Lookup(key) == pix)
{
++histos[i].Literal[WebpConstants.NumLiteralCodes + WebpConstants.NumLengthCodes + key];
}
else
{
colorCache[i].Set((uint)key, pix);
++histos[i].Blue[b];
++histos[i].Literal[g];
++histos[i].Red[r];
++histos[i].Alpha[a];
}
}
}
else
{
// We should compute the contribution of the (distance, length)
// histograms but those are the same independently from the cache size.
// As those constant contributions are in the end added to the other
// histogram contributions, we can ignore them, except for the length
// prefix that is part of the literal_ histogram.
int len = v.Len;
uint bgraPrev = bgra[pos] ^ 0xffffffffu;
int extraBits = 0, extraBitsValue = 0;
int code = LosslessUtils.PrefixEncode(len, ref extraBits, ref extraBitsValue);
for (int i = 0; i <= cacheBitsMax; i++)
{
++histos[i].Literal[WebpConstants.NumLiteralCodes + code];
}
// Update the color caches.
do
{
if (bgra[pos] != bgraPrev)
{
// Efficiency: insert only if the color changes.
int key = ColorCache.HashPix(bgra[pos], 32 - cacheBitsMax);
for (int i = cacheBitsMax; i >= 1; --i, key >>= 1)
{
colorCache[i].Colors[key] = bgra[pos];
}
bgraPrev = bgra[pos];
}
pos++;
}while (--len != 0);
}
}
var stats = new Vp8LStreaks();
var bitsEntropy = new Vp8LBitEntropy();
for (int i = 0; i <= cacheBitsMax; i++)
{
double entropy = histos[i].EstimateBits(stats, bitsEntropy);
if (i == 0 || entropy < entropyMin)
{
entropyMin = entropy;
bestCacheBits = i;
}
}
return(bestCacheBits);
}
private static void HistogramRemap(List <Vp8LHistogram> input, List <Vp8LHistogram> output, ushort[] symbols)
{
int inSize = input.Count;
int outSize = output.Count;
var stats = new Vp8LStreaks();
var bitsEntropy = new Vp8LBitEntropy();
if (outSize > 1)
{
for (int i = 0; i < inSize; i++)
{
if (input[i] == null)
{
// Arbitrarily set to the previous value if unused to help future LZ77.
symbols[i] = symbols[i - 1];
continue;
}
int bestOut = 0;
double bestBits = double.MaxValue;
for (int k = 0; k < outSize; k++)
{
double curBits = output[k].AddThresh(input[i], stats, bitsEntropy, bestBits);
if (k == 0 || curBits < bestBits)
{
bestBits = curBits;
bestOut = k;
}
}
symbols[i] = (ushort)bestOut;
}
}
else
{
for (int i = 0; i < inSize; i++)
{
symbols[i] = 0;
}
}
// Recompute each output.
int paletteCodeBits = output.First().PaletteCodeBits;
output.Clear();
for (int i = 0; i < outSize; i++)
{
output.Add(new Vp8LHistogram(paletteCodeBits));
}
for (int i = 0; i < inSize; i++)
{
if (input[i] == null)
{
continue;
}
int idx = symbols[i];
input[i].Add(output[idx], output[idx]);
}
}
/// <summary>
/// Create a pair from indices "idx1" and "idx2" provided its cost is inferior to "threshold", a negative entropy.
/// </summary>
/// <returns>The cost of the pair, or 0 if it superior to threshold.</returns>
private static double HistoPriorityListPush(List <HistogramPair> histoList, int maxSize, List <Vp8LHistogram> histograms, int idx1, int idx2, double threshold, Vp8LStreaks stats, Vp8LBitEntropy bitsEntropy)
{
var pair = new HistogramPair();
if (histoList.Count == maxSize)
{
return(0.0d);
}
if (idx1 > idx2)
{
int tmp = idx2;
idx2 = idx1;
idx1 = tmp;
}
pair.Idx1 = idx1;
pair.Idx2 = idx2;
Vp8LHistogram h1 = histograms[idx1];
Vp8LHistogram h2 = histograms[idx2];
HistoListUpdatePair(h1, h2, stats, bitsEntropy, threshold, pair);
// Do not even consider the pair if it does not improve the entropy.
if (pair.CostDiff >= threshold)
{
return(0.0d);
}
histoList.Add(pair);
HistoListUpdateHead(histoList, pair);
return(pair.CostDiff);
}
/// <summary>
/// Perform histogram aggregation using a stochastic approach.
/// </summary>
/// <returns>true if a greedy approach needs to be performed afterwards, false otherwise.</returns>
private static bool HistogramCombineStochastic(List <Vp8LHistogram> histograms, int minClusterSize)
{
uint seed = 1;
int triesWithNoSuccess = 0;
int numUsed = histograms.Count(h => h != null);
int outerIters = numUsed;
int numTriesNoSuccess = outerIters / 2;
var stats = new Vp8LStreaks();
var bitsEntropy = new Vp8LBitEntropy();
if (numUsed < minClusterSize)
{
return(true);
}
// Priority list of histogram pairs. Its size impacts the quality of the compression and the speed:
// the smaller the faster but the worse for the compression.
var histoPriorityList = new List <HistogramPair>();
int maxSize = 9;
// Fill the initial mapping.
int[] mappings = new int[histograms.Count];
for (int j = 0, iter = 0; iter < histograms.Count; iter++)
{
if (histograms[iter] == null)
{
continue;
}
mappings[j++] = iter;
}
// Collapse similar histograms.
for (int iter = 0; iter < outerIters && numUsed >= minClusterSize && ++triesWithNoSuccess < numTriesNoSuccess; iter++)
{
double bestCost = histoPriorityList.Count == 0 ? 0.0d : histoPriorityList[0].CostDiff;
int numTries = numUsed / 2;
uint randRange = (uint)((numUsed - 1) * numUsed);
// Pick random samples.
for (int j = 0; numUsed >= 2 && j < numTries; j++)
{
// Choose two different histograms at random and try to combine them.
uint tmp = MyRand(ref seed) % randRange;
int idx1 = (int)(tmp / (numUsed - 1));
int idx2 = (int)(tmp % (numUsed - 1));
if (idx2 >= idx1)
{
idx2++;
}
idx1 = mappings[idx1];
idx2 = mappings[idx2];
// Calculate cost reduction on combination.
double currCost = HistoPriorityListPush(histoPriorityList, maxSize, histograms, idx1, idx2, bestCost, stats, bitsEntropy);
// Found a better pair?
if (currCost < 0)
{
bestCost = currCost;
if (histoPriorityList.Count == maxSize)
{
break;
}
}
}
if (histoPriorityList.Count == 0)
{
continue;
}
// Get the best histograms.
int bestIdx1 = histoPriorityList[0].Idx1;
int bestIdx2 = histoPriorityList[0].Idx2;
int mappingIndex = Array.IndexOf(mappings, bestIdx2);
Span <int> src = mappings.AsSpan(mappingIndex + 1, numUsed - mappingIndex - 1);
Span <int> dst = mappings.AsSpan(mappingIndex);
src.CopyTo(dst);
// Merge the histograms and remove bestIdx2 from the list.
HistogramAdd(histograms[bestIdx2], histograms[bestIdx1], histograms[bestIdx1]);
histograms.ElementAt(bestIdx1).BitCost = histoPriorityList[0].CostCombo;
histograms[bestIdx2] = null;
numUsed--;
for (int j = 0; j < histoPriorityList.Count;)
{
HistogramPair p = histoPriorityList[j];
bool isIdx1Best = p.Idx1 == bestIdx1 || p.Idx1 == bestIdx2;
bool isIdx2Best = p.Idx2 == bestIdx1 || p.Idx2 == bestIdx2;
bool doEval = false;
// The front pair could have been duplicated by a random pick so
// check for it all the time nevertheless.
if (isIdx1Best && isIdx2Best)
{
histoPriorityList[j] = histoPriorityList[histoPriorityList.Count - 1];
histoPriorityList.RemoveAt(histoPriorityList.Count - 1);
continue;
}
// Any pair containing one of the two best indices should only refer to
// bestIdx1. Its cost should also be updated.
if (isIdx1Best)
{
p.Idx1 = bestIdx1;
doEval = true;
}
else if (isIdx2Best)
{
p.Idx2 = bestIdx1;
doEval = true;
}
// Make sure the index order is respected.
if (p.Idx1 > p.Idx2)
{
int tmp = p.Idx2;
p.Idx2 = p.Idx1;
p.Idx1 = tmp;
}
if (doEval)
{
// Re-evaluate the cost of an updated pair.
HistoListUpdatePair(histograms[p.Idx1], histograms[p.Idx2], stats, bitsEntropy, 0.0d, p);
if (p.CostDiff >= 0.0d)
{
histoPriorityList[j] = histoPriorityList[histoPriorityList.Count - 1];
histoPriorityList.RemoveAt(histoPriorityList.Count - 1);
continue;
}
}
HistoListUpdateHead(histoPriorityList, p);
j++;
}
triesWithNoSuccess = 0;
}
bool doGreedy = numUsed <= minClusterSize;
return(doGreedy);
}
private static void HistogramCombineGreedy(List <Vp8LHistogram> histograms)
{
int histoSize = histograms.Count(h => h != null);
// Priority list of histogram pairs.
var histoPriorityList = new List <HistogramPair>();
int maxSize = histoSize * histoSize;
var stats = new Vp8LStreaks();
var bitsEntropy = new Vp8LBitEntropy();
for (int i = 0; i < histoSize; i++)
{
if (histograms[i] == null)
{
continue;
}
for (int j = i + 1; j < histoSize; j++)
{
if (histograms[j] == null)
{
continue;
}
HistoPriorityListPush(histoPriorityList, maxSize, histograms, i, j, 0.0d, stats, bitsEntropy);
}
}
while (histoPriorityList.Count > 0)
{
int idx1 = histoPriorityList[0].Idx1;
int idx2 = histoPriorityList[0].Idx2;
HistogramAdd(histograms[idx2], histograms[idx1], histograms[idx1]);
histograms[idx1].BitCost = histoPriorityList[0].CostCombo;
// Remove merged histogram.
histograms[idx2] = null;
// Remove pairs intersecting the just combined best pair.
for (int i = 0; i < histoPriorityList.Count;)
{
HistogramPair p = histoPriorityList.ElementAt(i);
if (p.Idx1 == idx1 || p.Idx2 == idx1 || p.Idx1 == idx2 || p.Idx2 == idx2)
{
// Replace item at pos i with the last one and shrinking the list.
histoPriorityList[i] = histoPriorityList[histoPriorityList.Count - 1];
histoPriorityList.RemoveAt(histoPriorityList.Count - 1);
}
else
{
HistoListUpdateHead(histoPriorityList, p);
i++;
}
}
// Push new pairs formed with combined histogram to the list.
for (int i = 0; i < histoSize; i++)
{
if (i == idx1 || histograms[i] == null)
{
continue;
}
HistoPriorityListPush(histoPriorityList, maxSize, histograms, idx1, i, 0.0d, stats, bitsEntropy);
}
}
}
private static void HistogramCombineEntropyBin(
List <Vp8LHistogram> histograms,
ushort[] clusters,
ushort[] clusterMappings,
Vp8LHistogram curCombo,
ushort[] binMap,
int numBins,
double combineCostFactor)
{
var binInfo = new HistogramBinInfo[BinSize];
for (int idx = 0; idx < numBins; idx++)
{
binInfo[idx].First = -1;
binInfo[idx].NumCombineFailures = 0;
}
// By default, a cluster matches itself.
for (int idx = 0; idx < histograms.Count; idx++)
{
clusterMappings[idx] = (ushort)idx;
}
var indicesToRemove = new List <int>();
var stats = new Vp8LStreaks();
var bitsEntropy = new Vp8LBitEntropy();
for (int idx = 0; idx < histograms.Count; idx++)
{
if (histograms[idx] == null)
{
continue;
}
int binId = binMap[idx];
int first = binInfo[binId].First;
if (first == -1)
{
binInfo[binId].First = (short)idx;
}
else
{
// Try to merge #idx into #first (both share the same binId)
double bitCost = histograms[idx].BitCost;
double bitCostThresh = -bitCost * combineCostFactor;
double currCostDiff = histograms[first].AddEval(histograms[idx], stats, bitsEntropy, bitCostThresh, curCombo);
if (currCostDiff < bitCostThresh)
{
// Try to merge two histograms only if the combo is a trivial one or
// the two candidate histograms are already non-trivial.
// For some images, 'tryCombine' turns out to be false for a lot of
// histogram pairs. In that case, we fallback to combining
// histograms as usual to avoid increasing the header size.
bool tryCombine = curCombo.TrivialSymbol != NonTrivialSym || (histograms[idx].TrivialSymbol == NonTrivialSym && histograms[first].TrivialSymbol == NonTrivialSym);
int maxCombineFailures = 32;
if (tryCombine || binInfo[binId].NumCombineFailures >= maxCombineFailures)
{
// Move the (better) merged histogram to its final slot.
Vp8LHistogram tmp = curCombo;
curCombo = histograms[first];
histograms[first] = tmp;
histograms[idx] = null;
indicesToRemove.Add(idx);
clusterMappings[clusters[idx]] = clusters[first];
}
else
{
binInfo[binId].NumCombineFailures++;
}
}
}
}
foreach (int index in indicesToRemove.OrderByDescending(i => i))
{
histograms.RemoveAt(index);
}
}
private void GetEntropyUnrefined(uint val, int i, ref uint valPrev, ref int iPrev, Vp8LStreaks stats)
{
int streak = i - iPrev;
// Gather info for the bit entropy.
if (valPrev != 0)
{
this.Sum += (uint)(valPrev * streak);
this.NoneZeros += streak;
this.NoneZeroCode = (uint)iPrev;
this.Entropy -= LosslessUtils.FastSLog2(valPrev) * streak;
if (this.MaxVal < valPrev)
{
this.MaxVal = valPrev;
}
}
// Gather info for the Huffman cost.
stats.Counts[valPrev != 0 ? 1 : 0] += streak > 3 ? 1 : 0;
stats.Streaks[valPrev != 0 ? 1 : 0][streak > 3 ? 1 : 0] += streak;
valPrev = val;
iPrev = i;
}
/// <summary>
/// Get the symbol entropy for the distribution 'population'.
/// </summary>
private static double PopulationCost(uint[] population, int length, ref uint trivialSym, ref bool isUsed, Vp8LStreaks stats, Vp8LBitEntropy bitEntropy)
{
bitEntropy.Init();
stats.Clear();
bitEntropy.BitsEntropyUnrefined(population, length, stats);
trivialSym = (bitEntropy.NoneZeros == 1) ? bitEntropy.NoneZeroCode : NonTrivialSym;
// The histogram is used if there is at least one non-zero streak.
isUsed = stats.Streaks[1][0] != 0 || stats.Streaks[1][1] != 0;
return(bitEntropy.BitsEntropyRefine() + stats.FinalHuffmanCost());
}
private static double GetCombinedEntropy(uint[] x, uint[] y, int length, bool isXUsed, bool isYUsed, bool trivialAtEnd, Vp8LStreaks stats, Vp8LBitEntropy bitEntropy)
{
stats.Clear();
bitEntropy.Init();
if (trivialAtEnd)
{
// This configuration is due to palettization that transforms an indexed
// pixel into 0xff000000 | (pixel << 8) in BundleColorMap.
// BitsEntropyRefine is 0 for histograms with only one non-zero value.
// Only FinalHuffmanCost needs to be evaluated.
// Deal with the non-zero value at index 0 or length-1.
stats.Streaks[1][0] = 1;
// Deal with the following/previous zero streak.
stats.Counts[0] = 1;
stats.Streaks[0][1] = length - 1;
return(stats.FinalHuffmanCost());
}
if (isXUsed)
{
if (isYUsed)
{
bitEntropy.GetCombinedEntropyUnrefined(x, y, length, stats);
}
else
{
bitEntropy.GetEntropyUnrefined(x, length, stats);
}
}
else
{
if (isYUsed)
{
bitEntropy.GetEntropyUnrefined(y, length, stats);
}
else
{
stats.Counts[0] = 1;
stats.Streaks[0][length > 3 ? 1 : 0] = length;
bitEntropy.Init();
}
}
return(bitEntropy.BitsEntropyRefine() + stats.FinalHuffmanCost());
}
public bool GetCombinedHistogramEntropy(Vp8LHistogram b, Vp8LStreaks stats, Vp8LBitEntropy bitEntropy, double costThreshold, double costInitial, out double cost)
{
bool trivialAtEnd = false;
cost = costInitial;
cost += GetCombinedEntropy(this.Literal, b.Literal, this.NumCodes(), this.IsUsed[0], b.IsUsed[0], false, stats, bitEntropy);
cost += ExtraCostCombined(this.Literal.AsSpan(WebpConstants.NumLiteralCodes), b.Literal.AsSpan(WebpConstants.NumLiteralCodes), WebpConstants.NumLengthCodes);
if (cost > costThreshold)
{
return(false);
}
if (this.TrivialSymbol != NonTrivialSym && this.TrivialSymbol == b.TrivialSymbol)
{
// A, R and B are all 0 or 0xff.
uint colorA = (this.TrivialSymbol >> 24) & 0xff;
uint colorR = (this.TrivialSymbol >> 16) & 0xff;
uint colorB = (this.TrivialSymbol >> 0) & 0xff;
if ((colorA == 0 || colorA == 0xff) &&
(colorR == 0 || colorR == 0xff) &&
(colorB == 0 || colorB == 0xff))
{
trivialAtEnd = true;
}
}
cost += GetCombinedEntropy(this.Red, b.Red, WebpConstants.NumLiteralCodes, this.IsUsed[1], b.IsUsed[1], trivialAtEnd, stats, bitEntropy);
if (cost > costThreshold)
{
return(false);
}
cost += GetCombinedEntropy(this.Blue, b.Blue, WebpConstants.NumLiteralCodes, this.IsUsed[2], b.IsUsed[2], trivialAtEnd, stats, bitEntropy);
if (cost > costThreshold)
{
return(false);
}
cost += GetCombinedEntropy(this.Alpha, b.Alpha, WebpConstants.NumLiteralCodes, this.IsUsed[3], b.IsUsed[3], trivialAtEnd, stats, bitEntropy);
if (cost > costThreshold)
{
return(false);
}
cost += GetCombinedEntropy(this.Distance, b.Distance, WebpConstants.NumDistanceCodes, this.IsUsed[4], b.IsUsed[4], false, stats, bitEntropy);
if (cost > costThreshold)
{
return(false);
}
cost += ExtraCostCombined(this.Distance, b.Distance, WebpConstants.NumDistanceCodes);
if (cost > costThreshold)
{
return(false);
}
return(true);
}
