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fix-variance-estimation

LT1AB
Minyan Zhong 2021-01-05 02:21:55 -08:00 committed by Lijun Zhu
parent e8da2d947a
commit 19ee850211
3 changed files with 21 additions and 20 deletions
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22
contrib/PyCuAmpcor/src/cuAmpcorChunk.cu
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@ -65,29 +65,31 @@ void cuAmpcorChunk::run(int idxDown_, int idxAcross_)
// 41 x 41, if halfsearchrange=20
cuArraysMaxloc2D(r_corrBatchRaw, offsetInit, r_maxval, stream);
// Estimation of statistics
// Extraction of correlation surface around the peak
// estimate variance
cuEstimateVariance(r_referenceBatchRaw->size, r_corrBatchRaw, offsetInit, r_maxval, r_covValue, stream);
// estimate SNR
// step1: extraction of correlation surface around the peak
cuArraysCopyExtractCorr(r_corrBatchRaw, r_corrBatchRawZoomIn, i_corrBatchZoomInValid, offsetInit, stream);
// Summation of correlation and data point values
// step2: summation of correlation and data point values
cuArraysSumCorr(r_corrBatchRawZoomIn, i_corrBatchZoomInValid, r_corrBatchSum, i_corrBatchValidCount, stream);
#ifdef CUAMPCOR_DEBUG
r_maxval->outputToFile("r_maxval", stream);
r_corrBatchRawZoomIn->outputToFile("r_corrBatchRawStatZoomIn", stream);
i_corrBatchZoomInValid->outputToFile("i_corrBatchZoomInValid", stream);
r_corrBatchSum->outputToFile("r_corrBatchSum", stream);
i_corrBatchValidCount->outputToFile("i_corrBatchValidCount", stream);
#endif
// SNR
// step3: divide the peak value by the mean of surrounding values
cuEstimateSnr(r_corrBatchSum, i_corrBatchValidCount, r_maxval, r_snrValue, stream);
// Variance
cuEstimateVariance(r_corrBatchRaw, offsetInit, r_maxval, r_covValue, stream);
#ifdef CUAMPCOR_DEBUG
offsetInit->outputToFile("i_offsetInit", stream);
r_maxval->outputToFile("r_maxval", stream);
r_corrBatchRawZoomIn->outputToFile("r_corrBatchRawStatZoomIn", stream);
i_corrBatchZoomInValid->outputToFile("i_corrBatchStatZoomInValid", stream);
r_snrValue->outputToFile("r_snrValue", stream);
r_covValue->outputToFile("r_covValue", stream);
#endif
// Using the approximate estimation to adjust secondary image (half search window size becomes only 4 pixels)

2
contrib/PyCuAmpcor/src/cuAmpcorUtil.h
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@ -91,7 +91,7 @@ void cuArraysSumCorr(cuArrays<float> *images, cuArrays<int> *imagesValid, cuArra
void cuEstimateSnr(cuArrays<float> *corrSum, cuArrays<int> *corrValidCount, cuArrays<float> *maxval, cuArrays<float> *snrValue, cudaStream_t stream);
// implemented in cuEstimateStats.cu
void cuEstimateVariance(cuArrays<float> *corrBatchRaw, cuArrays<int2> *maxloc, cuArrays<float> *maxval, cuArrays<float3> *covValue, cudaStream_t stream);
void cuEstimateVariance(int winSize, cuArrays<float> *corrBatchRaw, cuArrays<int2> *maxloc, cuArrays<float> *maxval, cuArrays<float3> *covValue, cudaStream_t stream);
#endif

15
contrib/PyCuAmpcor/src/cuEstimateStats.cu
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@ -46,7 +46,7 @@ void cuEstimateSnr(cuArrays<float> *corrSum, cuArrays<int> *corrValidCount, cuAr
}
// cuda kernel for cuEstimateVariance
__global__ void cudaKernel_estimateVar(const float* corrBatchRaw, const int NX, const int NY,
__global__ void cudaKernel_estimateVar(const int winSize, const float* corrBatchRaw, const int NX, const int NY,
const int2* maxloc, const float* maxval, float3* covValue, const int size)
{
@ -78,14 +78,12 @@ __global__ void cudaKernel_estimateVar(const float* corrBatchRaw, const int NX,
int idx21 = offset + (px + 1) * NY + py ;
int idx22 = offset + (px + 1) * NY + py + 1;
float dxx = - ( corrBatchRaw[idx21] + corrBatchRaw[idx01] - 2*corrBatchRaw[idx11] ) * 0.5;
float dyy = - ( corrBatchRaw[idx12] + corrBatchRaw[idx10] - 2*corrBatchRaw[idx11] ) * 0.5;
float dxy = - ( corrBatchRaw[idx22] + corrBatchRaw[idx00] - corrBatchRaw[idx20] - corrBatchRaw[idx02] ) *0.25;
float dxx = - ( corrBatchRaw[idx21] + corrBatchRaw[idx01] - 2*corrBatchRaw[idx11] ) * 1.0;
float dyy = - ( corrBatchRaw[idx12] + corrBatchRaw[idx10] - 2*corrBatchRaw[idx11] ) * 1.0;
float dxy = ( corrBatchRaw[idx22] + corrBatchRaw[idx00] - corrBatchRaw[idx20] - corrBatchRaw[idx02] ) *0.25;
float n2 = fmaxf(1 - peak, 0.0);
int winSize = NX*NY;
dxx = dxx * winSize;
dyy = dyy * winSize;
dxy = dxy * winSize;
@ -113,18 +111,19 @@ __global__ void cudaKernel_estimateVar(const float* corrBatchRaw, const int NX,
/**
* Estimate the variance of the correlation surface
* @param[in] winSize size of reference chip
* @param[in] corrBatchRaw correlation surface
* @param[in] maxloc maximum location
* @param[in] maxval maximum value
* @param[out] covValue variance value
* @param[in] stream cuda stream
*/
void cuEstimateVariance(cuArrays<float> *corrBatchRaw, cuArrays<int2> *maxloc, cuArrays<float> *maxval, cuArrays<float3> *covValue, cudaStream_t stream)
void cuEstimateVariance(int winSize, cuArrays<float> *corrBatchRaw, cuArrays<int2> *maxloc, cuArrays<float> *maxval, cuArrays<float3> *covValue, cudaStream_t stream)
{
int size = corrBatchRaw->count;
// One dimensional launching parameters to loop over every correlation surface.
cudaKernel_estimateVar<<< IDIVUP(size, NTHREADS), NTHREADS, 0, stream>>>
(corrBatchRaw->devData, corrBatchRaw->height, corrBatchRaw->width, maxloc->devData, maxval->devData, covValue->devData, size);
(winSize, corrBatchRaw->devData, corrBatchRaw->height, corrBatchRaw->width, maxloc->devData, maxval->devData, covValue->devData, size);
getLastCudaError("cudaKernel_estimateVar error\n");
}
//end of file