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fixing 2-stage MLT, part 2

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Wenzel Jakob 2012-10-25 02:25:28 -04:00
parent 93d8953c90
commit 75cf06e8b2
2 changed files with 13 additions and 11 deletions
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setpath.sh Normal file → Executable file
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24
src/libbidir/pathsampler.cpp
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@ -580,7 +580,9 @@ Float PathSampler::computeAverageLuminance(size_t sampleCount) {
} }
static void seedCallback(std::vector<PathSeed> &output, const Bitmap *importanceMap, static void seedCallback(std::vector<PathSeed> &output, const Bitmap *importanceMap,
int s, int t, Float weight, Path &path) { Float &accum, int s, int t, Float weight, Path &path) {
accum += weight;
if (importanceMap) { if (importanceMap) {
const Float *luminanceValues = importanceMap->getFloatData(); const Float *luminanceValues = importanceMap->getFloatData();
Vector2i size = importanceMap->getSize(); Vector2i size = importanceMap->getSize();
@ -608,40 +610,40 @@ Float PathSampler::generateSeeds(size_t sampleCount, size_t seedCount,
tempSeeds.reserve(sampleCount); tempSeeds.reserve(sampleCount);
SplatList splatList; SplatList splatList;
Float luminance;
PathCallback callback = boost::bind(&seedCallback, PathCallback callback = boost::bind(&seedCallback,
boost::ref(tempSeeds), importanceMap, _1, _2, _3, _4); boost::ref(tempSeeds), importanceMap, boost::ref(luminance),
_1, _2, _3, _4);
Float mean = 0.0f, variance = 0.0f; Float mean = 0.0f, variance = 0.0f;
for (size_t i=0; i<sampleCount; ++i) { for (size_t i=0; i<sampleCount; ++i) {
size_t seedIndex = tempSeeds.size(); size_t seedIndex = tempSeeds.size();
size_t sampleIndex = m_sensorSampler->getSampleIndex(); size_t sampleIndex = m_sensorSampler->getSampleIndex();
Float lum = 0.0f; luminance = 0.0f;
if (fineGrained) { if (fineGrained) {
samplePaths(Point2i(-1), callback); samplePaths(Point2i(-1), callback);
/* Fine seed granularity (e.g. for Veach-MLT). /* Fine seed granularity (e.g. for Veach-MLT).
Set the correct the sample index value */ Set the correct the sample index value */
for (size_t j = seedIndex; j<tempSeeds.size(); ++j) { for (size_t j = seedIndex; j<tempSeeds.size(); ++j)
tempSeeds[j].sampleIndex = sampleIndex; tempSeeds[j].sampleIndex = sampleIndex;
lum += tempSeeds[j].luminance;
}
} else { } else {
/* Run the path sampling strategy */ /* Run the path sampling strategy */
sampleSplats(Point2i(-1), splatList); sampleSplats(Point2i(-1), splatList);
luminance = splatList.luminance;
splatList.normalize(importanceMap); splatList.normalize(importanceMap);
lum = splatList.luminance;
/* Coarse seed granularity (e.g. for PSSMLT) */ /* Coarse seed granularity (e.g. for PSSMLT) */
if (lum != 0) if (luminance != 0)
tempSeeds.push_back(PathSeed(sampleIndex, lum)); tempSeeds.push_back(PathSeed(sampleIndex, luminance));
} }
/* Numerically robust online variance estimation using an /* Numerically robust online variance estimation using an
algorithm proposed by Donald Knuth (TAOCP vol.2, 3rd ed., p.232) */ algorithm proposed by Donald Knuth (TAOCP vol.2, 3rd ed., p.232) */
Float delta = lum - mean; Float delta = luminance - mean;
mean += delta / (Float) (i+1); mean += delta / (Float) (i+1);
variance += delta * (lum - mean); variance += delta * (luminance - mean);
} }
BDAssert(m_pool.unused()); BDAssert(m_pool.unused());
Float stddev = std::sqrt(variance / (sampleCount-1)); Float stddev = std::sqrt(variance / (sampleCount-1));