KJ135
/
ISCE_INSAR
mirror of http://172.16.0.12:5000/WBJY/ISCE_INSAR.git
4
0
Fork 0
Code Issues Packages Projects Releases Wiki Activity

update

LT1AB
Minyan Zhong 2021-01-11 02:15:22 -08:00 committed by Lijun Zhu
parent 19ee850211
commit d5e5067acd
3 changed files with 12 additions and 12 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

2
contrib/PyCuAmpcor/src/cuAmpcorChunk.cu
View File

@ -66,7 +66,7 @@ void cuAmpcorChunk::run(int idxDown_, int idxAcross_)
cuArraysMaxloc2D(r_corrBatchRaw, offsetInit, r_maxval, stream);
// estimate variance
cuEstimateVariance(r_referenceBatchRaw->size, r_corrBatchRaw, offsetInit, r_maxval, r_covValue, stream);
cuEstimateVariance(r_corrBatchRaw, offsetInit, r_maxval, r_referenceBatchRaw->size, r_covValue, stream);
// estimate SNR
// step1: extraction of correlation surface around the peak

2
contrib/PyCuAmpcor/src/cuAmpcorUtil.h
View File

@ -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(int winSize, cuArrays<float> *corrBatchRaw, cuArrays<int2> *maxloc, cuArrays<float> *maxval, cuArrays<float3> *covValue, cudaStream_t stream);
void cuEstimateVariance(cuArrays<float> *corrBatchRaw, cuArrays<int2> *maxloc, cuArrays<float> *maxval, int templateSize, cuArrays<float3> *covValue, cudaStream_t stream);
#endif

20
contrib/PyCuAmpcor/src/cuEstimateStats.cu
View File

@ -46,8 +46,8 @@ void cuEstimateSnr(cuArrays<float> *corrSum, cuArrays<int> *corrValidCount, cuAr
}
// cuda kernel for cuEstimateVariance
__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)
__global__ void cudaKernel_estimateVar(const float* corrBatchRaw, const int NX, const int NY, const int2* maxloc,
const float* maxval, const int templateSize, float3* covValue, const int size)
{
// Find image id.
@ -63,7 +63,7 @@ __global__ void cudaKernel_estimateVar(const int winSize, const float* corrBatch
// Check if maxval is on the margin.
if (px-1 < 0 || py-1 <0 || px + 1 >=NX || py+1 >=NY) {
covValue[idxImage] = make_float3(99.0, 99.0, 99.0);
covValue[idxImage] = make_float3(99.0, 99.0, 0.0);
}
else {
@ -84,13 +84,13 @@ __global__ void cudaKernel_estimateVar(const int winSize, const float* corrBatch
float n2 = fmaxf(1 - peak, 0.0);
dxx = dxx * winSize;
dyy = dyy * winSize;
dxy = dxy * winSize;
dxx = dxx * templateSize;
dyy = dyy * templateSize;
dxy = dxy * templateSize;
float n4 = n2*n2;
n2 = n2 * 2;
n4 = n4 * 0.5 * winSize;
n4 = n4 * 0.5 * templateSize;
float u = dxy * dxy - dxx * dyy;
float u2 = u*u;
@ -111,19 +111,19 @@ __global__ void cudaKernel_estimateVar(const int winSize, const float* corrBatch
/**
* Estimate the variance of the correlation surface
* @param[in] winSize size of reference chip
* @param[in] templateSize 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(int winSize, cuArrays<float> *corrBatchRaw, cuArrays<int2> *maxloc, cuArrays<float> *maxval, cuArrays<float3> *covValue, cudaStream_t stream)
void cuEstimateVariance(cuArrays<float> *corrBatchRaw, cuArrays<int2> *maxloc, cuArrays<float> *maxval, int templateSize, 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>>>
(winSize, corrBatchRaw->devData, corrBatchRaw->height, corrBatchRaw->width, maxloc->devData, maxval->devData, covValue->devData, size);
(corrBatchRaw->devData, corrBatchRaw->height, corrBatchRaw->width, maxloc->devData, maxval->devData, templateSize, covValue->devData, size);
getLastCudaError("cudaKernel_estimateVar error\n");
}
//end of file