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transient tuning pt. 1

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This commit is contained in:
Christian R. Helmrich
2020-04-08 01:00:06 +02:00
parent 69e1d998a2
commit 83f3dc2f88
2 changed files with 41 additions and 9 deletions
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38
src/lib/bitAllocation.cpp
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@ -165,7 +165,7 @@ unsigned BitAllocator::initSfbStepSizes (const SfbGroupData* const groupData[USA
const uint32_t* rms = grpData.sfbRmsValues;
uint32_t* stepSizes = &sfbStepSizes[ch * numSwbShort * NUM_WINDOW_GROUPS];
// --- apply INTRA-channel simultaneous masking, equal-loudness weighting, and thresholding to SFB RMS data
uint32_t maskingSlope = 0, b, elw = 58254; // 8/9
uint32_t maskingSlope = 0, gr, b, elw = 58254; // 8/9
uint32_t rmsEqualLoud = 0;
uint32_t sumStepSizes = 0;
@ -185,7 +185,7 @@ unsigned BitAllocator::initSfbStepSizes (const SfbGroupData* const groupData[USA
}
if ((ch == lfeChannelIndex) || (grpData.numWindowGroups != 1)) // LFE, SHORT windows: no masking or ELW
{
for (unsigned gr = 0; gr < grpData.numWindowGroups; gr++)
for (gr = 0; gr < grpData.numWindowGroups; gr++)
{
const uint32_t* gRms = &rms[numSwbShort * gr];
uint32_t* gStepSizes = &stepSizes[numSwbShort * gr];
@ -207,11 +207,43 @@ unsigned BitAllocator::initSfbStepSizes (const SfbGroupData* const groupData[USA
{
// --- SHORT windows: apply perceptual just noticeable difference (JND) model and local band-peak smoothing
nMeans++;
for (b = maxSfbInCh - 1; b > 0; b--) // gentle temporal band-peak smoothing; a spectral one follows
{
uint32_t maxGrpStep = stepSizes[b], stepSizeM1 = BA_EPS;
for (gr = 1; gr < grpData.numWindowGroups; gr++)
{
const uint32_t curGrpStep = stepSizes[b + numSwbShort * gr];
if (curGrpStep > maxGrpStep) maxGrpStep = curGrpStep;
}
for (gr = 0; gr + 1 < grpData.numWindowGroups; gr++)
{
const uint32_t newGrpStep = __max (stepSizeM1, stepSizes[b + numSwbShort * (gr + 1)]);
stepSizeM1 = stepSizes[b + numSwbShort * gr];
if ((stepSizeM1 == maxGrpStep) && (maxGrpStep > newGrpStep))
{
sumStepSizes -= unsigned (0.5 + sqrt ((double) maxGrpStep));
stepSizes[b + numSwbShort * gr] = newGrpStep;
sumStepSizes += unsigned (0.5 + sqrt ((double) newGrpStep));
}
}
if ((stepSizes[b + numSwbShort * gr] == maxGrpStep) && (maxGrpStep > stepSizeM1))
{
sumStepSizes -= unsigned (0.5 + sqrt ((double) maxGrpStep));
stepSizes[b + numSwbShort * gr] = stepSizeM1;
sumStepSizes += unsigned (0.5 + sqrt ((double) stepSizeM1));
}
} // for b
m_avgStepSize[ch] = __min (USHRT_MAX, uint32_t ((sumStepSizes + (nBandsInCh >> 1)) / nBandsInCh));
sumMeans += m_avgStepSize[ch];
m_avgStepSize[ch] *= m_avgStepSize[ch];
for (unsigned gr = 0; gr < grpData.numWindowGroups; gr++) // separate peak smoothing for each group
for (gr = 0; gr < grpData.numWindowGroups; gr++) // separate spectral peak smoothing for each group
{
jndPowerLawAndPeakSmoothing (&stepSizes[numSwbShort * gr], maxSfbInCh, m_avgStepSize[ch], m_avgSpecFlat[ch], 0);
}