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authorDaniil Kazantsev <dkazanc@hotmail.com>2019-03-16 23:39:29 +0000
committerDaniil Kazantsev <dkazanc@hotmail.com>2019-03-16 23:39:29 +0000
commit9633c5d701c164c3ff8f4d870624f87744d186bd (patch)
tree23fd9a110436318aa55cbb46a6f86824940b5478 /src
parent1740fb91c1842dc174492857fad88c03420f74eb (diff)
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matlab demos updated
Diffstat (limited to 'src')
-rw-r--r--src/Matlab/mex_compile/regularisers_CPU/TGV.c44
1 files changed, 22 insertions, 22 deletions
diff --git a/src/Matlab/mex_compile/regularisers_CPU/TGV.c b/src/Matlab/mex_compile/regularisers_CPU/TGV.c
index 2c0fcbd..9e32ae4 100644
--- a/src/Matlab/mex_compile/regularisers_CPU/TGV.c
+++ b/src/Matlab/mex_compile/regularisers_CPU/TGV.c
@@ -20,7 +20,7 @@ limitations under the License.
#include "mex.h"
#include "TGV_core.h"
-/* C-OMP implementation of Primal-Dual denoising method for
+/* C-OMP implementation of Primal-Dual denoising method for
* Total Generilized Variation (TGV)-L2 model [1] (2D/3D)
*
* Input Parameters:
@@ -33,7 +33,7 @@ limitations under the License.
* 7. eplsilon - tolerance constant [OPTIONAL parameter]
*
* Output:
- * [1] Regularized image/volume
+ * [1] Regularized image/volume
* [2] Information vector which contains [iteration no., reached tolerance]
*
*
@@ -44,51 +44,51 @@ limitations under the License.
void mexFunction(
int nlhs, mxArray *plhs[],
int nrhs, const mxArray *prhs[])
-
+
{
int number_of_dims, iter;
mwSize dimX, dimY, dimZ;
const mwSize *dim_array;
-
+
float *Input, *Output=NULL, lambda, alpha0, alpha1, L2, epsil;
float *infovec=NULL;
-
+
number_of_dims = mxGetNumberOfDimensions(prhs[0]);
dim_array = mxGetDimensions(prhs[0]);
-
+
/*Handling Matlab input data*/
- if ((nrhs < 2) || (nrhs > 7)) mexErrMsgTxt("At least 2 parameters is required, all parameters are: Image(2D), Regularisation parameter, alpha0, alpha1, iterations number, Lipshitz Constant");
-
+ if ((nrhs < 2) || (nrhs > 7)) mexErrMsgTxt("At least 2 parameters is required, all parameters are: Image(2D), Regularisation parameter, alpha0, alpha1, iterations number, Lipshitz Constant, tolerance");
+
Input = (float *) mxGetData(prhs[0]); /*noisy image/volume */
lambda = (float) mxGetScalar(prhs[1]); /* regularisation parameter */
- alpha1 = 1.0f; /* parameter to control the first-order term */
+ alpha1 = 1.0f; /* parameter to control the first-order term */
alpha0 = 2.0f; /* parameter to control the second-order term */
- iter = 500; /* Iterations number */
+ iter = 500; /* Iterations number */
L2 = 12.0f; /* Lipshitz constant */
epsil = 1.0e-06; /*tolerance parameter*/
-
- if (mxGetClassID(prhs[0]) != mxSINGLE_CLASS) {mexErrMsgTxt("The input image must be in a single precision"); }
- if ((nrhs == 3) || (nrhs == 4) || (nrhs == 5) || (nrhs == 6) || (nrhs == 7)) alpha1 = (float) mxGetScalar(prhs[2]); /* parameter to control the first-order term */
+
+ if (mxGetClassID(prhs[0]) != mxSINGLE_CLASS) {mexErrMsgTxt("The input image must be in a single precision"); }
+ if ((nrhs == 3) || (nrhs == 4) || (nrhs == 5) || (nrhs == 6) || (nrhs == 7)) alpha1 = (float) mxGetScalar(prhs[2]); /* parameter to control the first-order term */
if ((nrhs == 4) || (nrhs == 5) || (nrhs == 6) || (nrhs == 7)) alpha0 = (float) mxGetScalar(prhs[3]); /* parameter to control the second-order term */
- if ((nrhs == 5) || (nrhs == 6) || (nrhs == 7)) iter = (int) mxGetScalar(prhs[4]); /* Iterations number */
+ if ((nrhs == 5) || (nrhs == 6) || (nrhs == 7)) iter = (int) mxGetScalar(prhs[4]); /* Iterations number */
if ((nrhs == 6) || (nrhs == 7)) L2 = (float) mxGetScalar(prhs[5]); /* Lipshitz constant */
if (nrhs == 7) epsil = (float) mxGetScalar(prhs[6]); /* epsilon */
-
+
/*Handling Matlab output data*/
dimX = dim_array[0]; dimY = dim_array[1]; dimZ = dim_array[2];
-
+
if (number_of_dims == 2) {
dimZ = 1; /*2D case*/
- Output = (float*)mxGetPr(plhs[0] = mxCreateNumericArray(2, dim_array, mxSINGLE_CLASS, mxREAL));
+ Output = (float*)mxGetPr(plhs[0] = mxCreateNumericArray(2, dim_array, mxSINGLE_CLASS, mxREAL));
}
if (number_of_dims == 3) {
Output = (float*)mxGetPr(plhs[0] = mxCreateNumericArray(3, dim_array, mxSINGLE_CLASS, mxREAL));
- }
-
+ }
+
mwSize vecdim[1];
vecdim[0] = 2;
- infovec = (float*)mxGetPr(plhs[1] = mxCreateNumericArray(1, vecdim, mxSINGLE_CLASS, mxREAL));
-
+ infovec = (float*)mxGetPr(plhs[1] = mxCreateNumericArray(1, vecdim, mxSINGLE_CLASS, mxREAL));
+
/* running the function */
- TGV_main(Input, Output, infovec, lambda, alpha1, alpha0, iter, L2, epsil, dimX, dimY, dimZ);
+ TGV_main(Input, Output, infovec, lambda, alpha1, alpha0, iter, L2, epsil, dimX, dimY, dimZ);
}