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Diffstat (limited to 'src/Core/regularisers_CPU/FGP_TV_core.c')
-rw-r--r--src/Core/regularisers_CPU/FGP_TV_core.c76
1 files changed, 23 insertions, 53 deletions
diff --git a/src/Core/regularisers_CPU/FGP_TV_core.c b/src/Core/regularisers_CPU/FGP_TV_core.c
index a16a2e5..ff67af2 100644
--- a/src/Core/regularisers_CPU/FGP_TV_core.c
+++ b/src/Core/regularisers_CPU/FGP_TV_core.c
@@ -46,12 +46,12 @@ float TV_FGP_CPU_main(float *Input, float *Output, float *infovector, float lamb
float tk = 1.0f;
float tkp1 =1.0f;
int count = 0;
-
+
if (dimZ <= 1) {
/*2D case */
float *Output_prev=NULL, *P1=NULL, *P2=NULL, *P1_prev=NULL, *P2_prev=NULL, *R1=NULL, *R2=NULL;
DimTotal = (long)(dimX*dimY);
-
+
if (epsil != 0.0f) Output_prev = calloc(DimTotal, sizeof(float));
P1 = calloc(DimTotal, sizeof(float));
P2 = calloc(DimTotal, sizeof(float));
@@ -59,32 +59,32 @@ float TV_FGP_CPU_main(float *Input, float *Output, float *infovector, float lamb
P2_prev = calloc(DimTotal, sizeof(float));
R1 = calloc(DimTotal, sizeof(float));
R2 = calloc(DimTotal, sizeof(float));
-
+
/* begin iterations */
for(ll=0; ll<iterationsNumb; ll++) {
-
+
if ((epsil != 0.0f) && (ll % 5 == 0)) copyIm(Output, Output_prev, (long)(dimX), (long)(dimY), 1l);
/* computing the gradient of the objective function */
Obj_func2D(Input, Output, R1, R2, lambdaPar, (long)(dimX), (long)(dimY));
-
+
/* apply nonnegativity */
if (nonneg == 1) for(j=0; j<DimTotal; j++) {if (Output[j] < 0.0f) Output[j] = 0.0f;}
-
+
/*Taking a step towards minus of the gradient*/
Grad_func2D(P1, P2, Output, R1, R2, lambdaPar, (long)(dimX), (long)(dimY));
-
+
/* projection step */
Proj_func2D(P1, P2, methodTV, DimTotal);
-
+
/*updating R and t*/
tkp1 = (1.0f + sqrtf(1.0f + 4.0f*tk*tk))*0.5f;
Rupd_func2D(P1, P1_prev, P2, P2_prev, R1, R2, tkp1, tk, DimTotal);
-
+
/*storing old values*/
copyIm(P1, P1_prev, (long)(dimX), (long)(dimY), 1l);
copyIm(P2, P2_prev, (long)(dimX), (long)(dimY), 1l);
tk = tkp1;
-
+
/* check early stopping criteria */
if ((epsil != 0.0f) && (ll % 5 == 0)) {
re = 0.0f; re1 = 0.0f;
@@ -105,7 +105,7 @@ float TV_FGP_CPU_main(float *Input, float *Output, float *infovector, float lamb
/*3D case*/
float *Output_prev=NULL, *P1=NULL, *P2=NULL, *P3=NULL, *P1_prev=NULL, *P2_prev=NULL, *P3_prev=NULL, *R1=NULL, *R2=NULL, *R3=NULL;
DimTotal = (long)(dimX*dimY*dimZ);
-
+
if (epsil != 0.0f) Output_prev = calloc(DimTotal, sizeof(float));
P1 = calloc(DimTotal, sizeof(float));
P2 = calloc(DimTotal, sizeof(float));
@@ -116,28 +116,28 @@ float TV_FGP_CPU_main(float *Input, float *Output, float *infovector, float lamb
R1 = calloc(DimTotal, sizeof(float));
R2 = calloc(DimTotal, sizeof(float));
R3 = calloc(DimTotal, sizeof(float));
-
+
/* begin iterations */
for(ll=0; ll<iterationsNumb; ll++) {
-
+
if ((epsil != 0.0f) && (ll % 5 == 0)) copyIm(Output, Output_prev, (long)(dimX), (long)(dimY), (long)(dimZ));
-
+
/* computing the gradient of the objective function */
Obj_func3D(Input, Output, R1, R2, R3, lambdaPar, (long)(dimX), (long)(dimY), (long)(dimZ));
-
+
/* apply nonnegativity */
if (nonneg == 1) for(j=0; j<DimTotal; j++) {if (Output[j] < 0.0f) Output[j] = 0.0f;}
-
+
/*Taking a step towards minus of the gradient*/
Grad_func3D(P1, P2, P3, Output, R1, R2, R3, lambdaPar, (long)(dimX), (long)(dimY), (long)(dimZ));
-
+
/* projection step */
Proj_func3D(P1, P2, P3, methodTV, DimTotal);
-
+
/*updating R and t*/
tkp1 = (1.0f + sqrtf(1.0f + 4.0f*tk*tk))*0.5f;
Rupd_func3D(P1, P1_prev, P2, P2_prev, P3, P3_prev, R1, R2, R3, tkp1, tk, DimTotal);
-
+
/* calculate norm - stopping rules*/
if ((epsil != 0.0f) && (ll % 5 == 0)) {
re = 0.0f; re1 = 0.0f;
@@ -151,22 +151,22 @@ float TV_FGP_CPU_main(float *Input, float *Output, float *infovector, float lamb
if (re < epsil) count++;
if (count > 3) break;
}
-
+
/*storing old values*/
copyIm(P1, P1_prev, (long)(dimX), (long)(dimY), (long)(dimZ));
copyIm(P2, P2_prev, (long)(dimX), (long)(dimY), (long)(dimZ));
copyIm(P3, P3_prev, (long)(dimX), (long)(dimY), (long)(dimZ));
tk = tkp1;
}
-
+
if (epsil != 0.0f) free(Output_prev);
free(P1); free(P2); free(P3); free(P1_prev); free(P2_prev); free(P3_prev); free(R1); free(R2); free(R3);
}
-
+
/*adding info into info_vector */
infovector[0] = (float)(ll); /*iterations number (if stopped earlier based on tolerance)*/
infovector[1] = re; /* reached tolerance */
-
+
return 0;
}
@@ -202,36 +202,6 @@ float Grad_func2D(float *P1, float *P2, float *D, float *R1, float *R2, float la
}}
return 1;
}
-float Proj_func2D(float *P1, float *P2, int methTV, long DimTotal)
-{
- float val1, val2, denom, sq_denom;
- long i;
- if (methTV == 0) {
- /* isotropic TV*/
-#pragma omp parallel for shared(P1,P2) private(i,denom,sq_denom)
- for(i=0; i<DimTotal; i++) {
- denom = powf(P1[i],2) + powf(P2[i],2);
- if (denom > 1.0f) {
- sq_denom = 1.0f/sqrtf(denom);
- P1[i] = P1[i]*sq_denom;
- P2[i] = P2[i]*sq_denom;
- }
- }
- }
- else {
- /* anisotropic TV*/
-#pragma omp parallel for shared(P1,P2) private(i,val1,val2)
- for(i=0; i<DimTotal; i++) {
- val1 = fabs(P1[i]);
- val2 = fabs(P2[i]);
- if (val1 < 1.0f) {val1 = 1.0f;}
- if (val2 < 1.0f) {val2 = 1.0f;}
- P1[i] = P1[i]/val1;
- P2[i] = P2[i]/val2;
- }
- }
- return 1;
-}
float Rupd_func2D(float *P1, float *P1_old, float *P2, float *P2_old, float *R1, float *R2, float tkp1, float tk, long DimTotal)
{
long i;
generated by cgit v1.2.1 (git 2.18.0) at 2024-05-28 19:15:16 +0000