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-rw-r--r--Core/regularisers_CPU/LLT_ROF_core.c6
-rw-r--r--Core/regularisers_CPU/ROF_TV_core.c14
-rw-r--r--Core/regularisers_GPU/LLT_ROF_GPU_core.cu6
-rwxr-xr-xCore/regularisers_GPU/TV_ROF_GPU_core.cu28
-rw-r--r--Readme.md5
5 files changed, 30 insertions, 29 deletions
diff --git a/Core/regularisers_CPU/LLT_ROF_core.c b/Core/regularisers_CPU/LLT_ROF_core.c
index 6dcf018..1584a29 100644
--- a/Core/regularisers_CPU/LLT_ROF_core.c
+++ b/Core/regularisers_CPU/LLT_ROF_core.c
@@ -19,7 +19,7 @@ limitations under the License.
#include "LLT_ROF_core.h"
#define EPS_LLT 0.01
-#define EPS_ROF 1.0e-5
+#define EPS_ROF 1.0e-12
#define MAX(x, y) (((x) > (y)) ? (x) : (y))
#define MIN(x, y) (((x) < (y)) ? (x) : (y))
@@ -363,7 +363,7 @@ float Update2D_LLT_ROF(float *U0, float *U, float *D1_LLT, float *D2_LLT, float
div = dv1 + dv2; /*build Divirgent*/
/*combine all into one cost function to minimise */
- U[index] += tau*(lambdaROF*(div) - lambdaLLT*(laplc) - (U[index] - U0[index]));
+ U[index] += tau*(2.0f*lambdaROF*(div) - lambdaLLT*(laplc) - (U[index] - U0[index]));
}
}
return *U;
@@ -400,7 +400,7 @@ float Update3D_LLT_ROF(float *U0, float *U, float *D1_LLT, float *D2_LLT, float
div = dv1 + dv2 + dv3; /*build Divirgent*/
/*combine all into one cost function to minimise */
- U[index] += tau*(lambdaROF*(div) - lambdaLLT*(laplc) - (U[index] - U0[index]));
+ U[index] += tau*(2.0f*lambdaROF*(div) - lambdaLLT*(laplc) - (U[index] - U0[index]));
}
}
}
diff --git a/Core/regularisers_CPU/ROF_TV_core.c b/Core/regularisers_CPU/ROF_TV_core.c
index e89774f..fb3bc7c 100644
--- a/Core/regularisers_CPU/ROF_TV_core.c
+++ b/Core/regularisers_CPU/ROF_TV_core.c
@@ -19,7 +19,7 @@
#include "ROF_TV_core.h"
-#define EPS 1.0e-5
+#define EPS 1.0e-12
#define MAX(x, y) (((x) > (y)) ? (x) : (y))
#define MIN(x, y) (((x) < (y)) ? (x) : (y))
@@ -148,7 +148,7 @@ float D2_func(float *A, float *D2, int dimX, int dimY, int dimZ)
for(j=0; j<dimY; j++) {
for(i=0; i<dimX; i++) {
for(k=0; k<dimZ; k++) {
- index = (dimX*dimY)*k + j*dimX+i;
+ index = (dimX*dimY)*k + j*dimX+i;
/* symmetric boundary conditions (Neuman) */
i1 = i + 1; if (i1 >= dimX) i1 = i-1;
i2 = i - 1; if (i2 < 0) i2 = i+1;
@@ -179,7 +179,7 @@ float D2_func(float *A, float *D2, int dimX, int dimY, int dimZ)
#pragma omp parallel for shared (A, D2, dimX, dimY) private(i, j, i1, j1, i2, j2, NOMx_1,NOMy_1,NOMx_0,denom1,denom2,T2,index)
for(j=0; j<dimY; j++) {
for(i=0; i<dimX; i++) {
- index = j*dimX+i;
+ index = j*dimX+i;
/* symmetric boundary conditions (Neuman) */
i1 = i + 1; if (i1 >= dimX) i1 = i-1;
i2 = i - 1; if (i2 < 0) i2 = i+1;
@@ -265,8 +265,8 @@ float TV_kernel(float *D1, float *D2, float *D3, float *B, float *A, float lambd
dv2 = D2[index] - D2[(dimX*dimY)*k + j*dimX+i2];
dv3 = D3[index] - D3[(dimX*dimY)*k2 + j*dimX+i];
- B[index] = B[index] + tau*(lambda*(dv1 + dv2 + dv3) - (B[index] - A[index]));
- }}}
+ B[index] += tau*(2.0f*lambda*(dv1 + dv2 + dv3) - (B[index] - A[index]));
+ }}}
}
else {
#pragma omp parallel for shared (D1, D2, B, dimX, dimY) private(index, i, j, i1, j1, i2, j2,dv1,dv2)
@@ -281,9 +281,9 @@ float TV_kernel(float *D1, float *D2, float *D3, float *B, float *A, float lambd
/* divergence components */
dv1 = D1[index] - D1[j2*dimX + i];
- dv2 = D2[index] - D2[j*dimX + i2];
+ dv2 = D2[index] - D2[j*dimX + i2];
- B[index] = B[index] + tau*(lambda*(dv1 + dv2) - (B[index] - A[index]));
+ B[index] += tau*(2.0f*lambda*(dv1 + dv2) - (B[index] - A[index]));
}}
}
return *B;
diff --git a/Core/regularisers_GPU/LLT_ROF_GPU_core.cu b/Core/regularisers_GPU/LLT_ROF_GPU_core.cu
index 70c9295..0228bf0 100644
--- a/Core/regularisers_GPU/LLT_ROF_GPU_core.cu
+++ b/Core/regularisers_GPU/LLT_ROF_GPU_core.cu
@@ -61,7 +61,7 @@ limitations under the License.
#define EPS_LLT 0.01
-#define EPS_ROF 1.0e-5
+#define EPS_ROF 1.0e-12
#define idivup(a, b) ( ((a)%(b) != 0) ? (a)/(b)+1 : (a)/(b) )
@@ -357,7 +357,7 @@ __global__ void Update2D_LLT_ROF_kernel(float *U0, float *U, float *D1_LLT, floa
div = dv1 + dv2; /*build Divirgent*/
/*combine all into one cost function to minimise */
- U[index] += tau*(lambdaROF*(div) - lambdaLLT*(laplc) - (U[index] - U0[index]));
+ U[index] += tau*(2.0f*lambdaROF*(div) - lambdaLLT*(laplc) - (U[index] - U0[index]));
}
}
@@ -395,7 +395,7 @@ __global__ void Update3D_LLT_ROF_kernel(float *U0, float *U, float *D1_LLT, floa
div = dv1 + dv2 + dv3; /*build Divirgent*/
/*combine all into one cost function to minimise */
- U[index] += tau*(lambdaROF*(div) - lambdaLLT*(laplc) - (U[index] - U0[index]));
+ U[index] += tau*(2.0f*lambdaROF*(div) - lambdaLLT*(laplc) - (U[index] - U0[index]));
}
}
diff --git a/Core/regularisers_GPU/TV_ROF_GPU_core.cu b/Core/regularisers_GPU/TV_ROF_GPU_core.cu
index 67cdd5c..57de63d 100755
--- a/Core/regularisers_GPU/TV_ROF_GPU_core.cu
+++ b/Core/regularisers_GPU/TV_ROF_GPU_core.cu
@@ -54,7 +54,7 @@ limitations under the License.
#define BLKXSIZE2D 16
#define BLKYSIZE2D 16
-#define EPS 1.0e-5
+#define EPS 1.0e-12
#define idivup(a, b) ( ((a)%(b) != 0) ? (a)/(b)+1 : (a)/(b) )
@@ -91,10 +91,10 @@ __host__ __device__ int sign (float x)
NOMy_0 = Input[index] - Input[j*N + i2]; /* y- */
denom1 = NOMx_1*NOMx_1;
- denom2 = 0.5f*(sign((float)NOMy_1) + sign((float)NOMy_0))*(MIN(abs((float)NOMy_1),abs((float)NOMy_0)));
+ denom2 = 0.5f*(sign((float)NOMy_1) + sign((float)NOMy_0))*(MIN(abs((float)NOMy_1), abs((float)NOMy_0)));
denom2 = denom2*denom2;
T1 = sqrt(denom1 + denom2 + EPS);
- D1[index] = NOMx_1/T1;
+ D1[index] = NOMx_1/T1;
}
}
@@ -106,7 +106,7 @@ __host__ __device__ int sign (float x)
int i = blockDim.x * blockIdx.x + threadIdx.x;
int j = blockDim.y * blockIdx.y + threadIdx.y;
- int index = i + N*j;
+ int index = i + N*j;
if ((i >= 0) && (i < (N)) && (j >= 0) && (j < (M))) {
@@ -121,10 +121,10 @@ __host__ __device__ int sign (float x)
NOMx_0 = Input[index] - Input[j2*N + i]; /* x- */
denom1 = NOMy_1*NOMy_1;
- denom2 = 0.5f*(sign((float)NOMx_1) + sign((float)NOMx_0))*(MIN(abs((float)NOMx_1),abs((float)NOMx_0)));
+ denom2 = 0.5f*(sign((float)NOMx_1) + sign((float)NOMx_0))*(MIN(abs((float)NOMx_1), abs((float)NOMx_0)));
denom2 = denom2*denom2;
T2 = sqrt(denom1 + denom2 + EPS);
- D2[index] = NOMy_1/T2;
+ D2[index] = NOMy_1/T2;
}
}
@@ -139,15 +139,15 @@ __host__ __device__ int sign (float x)
if ((i >= 0) && (i < (N)) && (j >= 0) && (j < (M))) {
- /* boundary conditions (Neumann reflections) */
- i2 = i - 1; if (i2 < 0) i2 = i+1;
+ /* boundary conditions (Neumann reflections) */
+ i2 = i - 1; if (i2 < 0) i2 = i+1;
j2 = j - 1; if (j2 < 0) j2 = j+1;
/* divergence components */
dv1 = D1[index] - D1[j2*N + i];
- dv2 = D2[index] - D2[j*N + i2];
+ dv2 = D2[index] - D2[j*N + i2];
- Update[index] = Update[index] + tau*(lambda*(dv1 + dv2) - (Update[index] - Input[index]));
+ Update[index] += tau*(2.0f*lambda*(dv1 + dv2) - (Update[index] - Input[index]));
}
}
@@ -268,7 +268,7 @@ __host__ __device__ int sign (float x)
denom3 = 0.5*(sign(NOMy_1) + sign(NOMy_0))*(MIN(abs(NOMy_1),abs(NOMy_0)));
denom3 = denom3*denom3;
T3 = sqrt(denom1 + denom2 + denom3 + EPS);
- D3[index] = NOMz_1/T3;
+ D3[index] = NOMz_1/T3;
}
}
@@ -297,7 +297,7 @@ __host__ __device__ int sign (float x)
dv2 = D2[index] - D2[(dimX*dimY)*k + j*dimX+i2];
dv3 = D3[index] - D3[(dimX*dimY)*k2 + j*dimX+i];
- Update[index] = Update[index] + tau*(lambda*(dv1 + dv2 + dv3) - (Update[index] - Input[index]));
+ Update[index] += tau*(2.0f*lambda*(dv1 + dv2 + dv3) - (Update[index] - Input[index]));
}
}
@@ -321,7 +321,7 @@ extern "C" void TV_ROF_GPU_main(float* Input, float* Output, float lambdaPar, in
CHECK(cudaMemcpy(d_update,Input,N*M*Z*sizeof(float),cudaMemcpyHostToDevice));
if (Z > 1) {
- // TV - 3D case
+ // TV - 3D case
dim3 dimBlock(BLKXSIZE,BLKYSIZE,BLKZSIZE);
dim3 dimGrid(idivup(N,BLKXSIZE), idivup(M,BLKYSIZE),idivup(Z,BLKXSIZE));
@@ -341,7 +341,7 @@ extern "C" void TV_ROF_GPU_main(float* Input, float* Output, float lambdaPar, in
CHECK(cudaDeviceSynchronize());
}
- CHECK(cudaFree(d_D3));
+ CHECK(cudaFree(d_D3));
}
else {
// TV - 2D case
diff --git a/Readme.md b/Readme.md
index 2dccaee..6f710c8 100644
--- a/Readme.md
+++ b/Readme.md
@@ -89,8 +89,9 @@ conda install ccpi-regulariser -c ccpi -c conda-forge
### Applications:
-* [Regularised FISTA-type iterative reconstruction algorithm for X-ray tomographic reconstruction with highly inaccurate measurements (MATLAB code)](https://github.com/dkazanc/FISTA-tomo)
-* [Joint image reconstruction method with correlative multi-channel prior for X-ray spectral computed tomography](https://github.com/dkazanc/multi-channel-X-ray-CT)
+* [Regularised FISTA iterative reconstruction algorithm for X-ray tomographic reconstruction with highly inaccurate measurements (MATLAB code)](https://github.com/dkazanc/FISTA-tomo)
+* [Regularised ADMM iterative reconstruction algorithm for X-ray tomographic reconstruction (MATLAB code)](https://github.com/dkazanc/ADMM-tomo)
+* [Joint image reconstruction method with correlative multi-channel prior for X-ray spectral computed tomography (MATLAB code)](https://github.com/dkazanc/multi-channel-X-ray-CT)
### License:
[Apache License, Version 2.0](http://www.apache.org/licenses/LICENSE-2.0)
generated by cgit v1.2.3 (git 2.25.1) at 2025-10-31 10:55:11 +0000