diff options
author | Edoardo Pasca <edo.paskino@gmail.com> | 2017-08-02 16:51:14 +0100 |
---|---|---|
committer | Edoardo Pasca <edo.paskino@gmail.com> | 2017-10-11 15:28:35 +0100 |
commit | 33da5e128e51e5adc1f6085b4772b55b2cd76e2e (patch) | |
tree | c3629d18923f7ab752f06df0a8cd31fa508fe23f | |
parent | 6fb8f5d188ed31d7a7077cba8ab7aea17b25b8bf (diff) | |
download | regularization-33da5e128e51e5adc1f6085b4772b55b2cd76e2e.tar.gz regularization-33da5e128e51e5adc1f6085b4772b55b2cd76e2e.tar.bz2 regularization-33da5e128e51e5adc1f6085b4772b55b2cd76e2e.tar.xz regularization-33da5e128e51e5adc1f6085b4772b55b2cd76e2e.zip |
added utils
-rw-r--r-- | main_func/regularizers_CPU/FGP_TV_core.h | 30 | ||||
-rw-r--r-- | main_func/regularizers_CPU/LLT_model_core.h | 3 | ||||
-rw-r--r-- | main_func/regularizers_CPU/SplitBregman_TV_core.h | 28 | ||||
-rw-r--r-- | main_func/regularizers_CPU/TGV_PD_core.h | 3 |
4 files changed, 60 insertions, 4 deletions
diff --git a/main_func/regularizers_CPU/FGP_TV_core.h b/main_func/regularizers_CPU/FGP_TV_core.h index 697fd84..d256c9a 100644 --- a/main_func/regularizers_CPU/FGP_TV_core.h +++ b/main_func/regularizers_CPU/FGP_TV_core.h @@ -23,8 +23,36 @@ limitations under the License. #include <memory.h> #include <stdio.h> #include "omp.h" +#include "utils.h" -float copyIm(float *A, float *B, int dimX, int dimY, int dimZ); +/* C-OMP implementation of FGP-TV [1] denoising/regularization model (2D/3D case) +* +* Input Parameters: +* 1. Noisy image/volume [REQUIRED] +* 2. lambda - regularization parameter [REQUIRED] +* 3. Number of iterations [OPTIONAL parameter] +* 4. eplsilon: tolerance constant [OPTIONAL parameter] +* 5. TV-type: 'iso' or 'l1' [OPTIONAL parameter] +* +* Output: +* [1] Filtered/regularized image +* [2] last function value +* +* Example of image denoising: +* figure; +* Im = double(imread('lena_gray_256.tif'))/255; % loading image +* u0 = Im + .05*randn(size(Im)); % adding noise +* u = FGP_TV(single(u0), 0.05, 100, 1e-04); +* +* to compile with OMP support: mex FGP_TV.c CFLAGS="\$CFLAGS -fopenmp -Wall -std=c99" LDFLAGS="\$LDFLAGS -fopenmp" +* This function is based on the Matlab's code and paper by +* [1] Amir Beck and Marc Teboulle, "Fast Gradient-Based Algorithms for Constrained Total Variation Image Denoising and Deblurring Problems" +* +* D. Kazantsev, 2016-17 +* +*/ + +//float copyIm(float *A, float *B, int dimX, int dimY, int dimZ); float Obj_func2D(float *A, float *D, float *R1, float *R2, float lambda, int dimX, int dimY); float Grad_func2D(float *P1, float *P2, float *D, float *R1, float *R2, float lambda, int dimX, int dimY); float Proj_func2D(float *P1, float *P2, int methTV, int dimX, int dimY); diff --git a/main_func/regularizers_CPU/LLT_model_core.h b/main_func/regularizers_CPU/LLT_model_core.h index 10f52fe..560bb9c 100644 --- a/main_func/regularizers_CPU/LLT_model_core.h +++ b/main_func/regularizers_CPU/LLT_model_core.h @@ -23,6 +23,7 @@ limitations under the License. #include <memory.h> #include <stdio.h> #include "omp.h" +#include "utils.h" #define EPS 0.01 @@ -36,4 +37,4 @@ float div_upd3D(float *U0, float *U, float *D1, float *D2, float *D3, unsigned s float calcMap(float *U, unsigned short *Map, int dimX, int dimY, int dimZ); float cleanMap(unsigned short *Map, int dimX, int dimY, int dimZ); -float copyIm(float *A, float *U, int dimX, int dimY, int dimZ); +//float copyIm(float *A, float *U, int dimX, int dimY, int dimZ); diff --git a/main_func/regularizers_CPU/SplitBregman_TV_core.h b/main_func/regularizers_CPU/SplitBregman_TV_core.h index a7aaabb..78aef09 100644 --- a/main_func/regularizers_CPU/SplitBregman_TV_core.h +++ b/main_func/regularizers_CPU/SplitBregman_TV_core.h @@ -23,7 +23,33 @@ limitations under the License. #include <stdio.h> #include "omp.h" -float copyIm(float *A, float *B, int dimX, int dimY, int dimZ); +#include "utils.h" + +/* C-OMP implementation of Split Bregman - TV denoising-regularization model (2D/3D) +* +* Input Parameters: +* 1. Noisy image/volume +* 2. lambda - regularization parameter +* 3. Number of iterations [OPTIONAL parameter] +* 4. eplsilon - tolerance constant [OPTIONAL parameter] +* 5. TV-type: 'iso' or 'l1' [OPTIONAL parameter] +* +* Output: +* Filtered/regularized image +* +* Example: +* figure; +* Im = double(imread('lena_gray_256.tif'))/255; % loading image +* u0 = Im + .05*randn(size(Im)); u0(u0 < 0) = 0; +* u = SplitBregman_TV(single(u0), 10, 30, 1e-04); +* +* to compile with OMP support: mex SplitBregman_TV.c CFLAGS="\$CFLAGS -fopenmp -Wall -std=c99" LDFLAGS="\$LDFLAGS -fopenmp" +* References: +* The Split Bregman Method for L1 Regularized Problems, by Tom Goldstein and Stanley Osher. +* D. Kazantsev, 2016* +*/ + +//float copyIm(float *A, float *B, int dimX, int dimY, int dimZ); float gauss_seidel2D(float *U, float *A, float *Dx, float *Dy, float *Bx, float *By, int dimX, int dimY, float lambda, float mu); float updDxDy_shrinkAniso2D(float *U, float *Dx, float *Dy, float *Bx, float *By, int dimX, int dimY, float lambda); float updDxDy_shrinkIso2D(float *U, float *Dx, float *Dy, float *Bx, float *By, int dimX, int dimY, float lambda); diff --git a/main_func/regularizers_CPU/TGV_PD_core.h b/main_func/regularizers_CPU/TGV_PD_core.h index 04ba95c..cbe7ea4 100644 --- a/main_func/regularizers_CPU/TGV_PD_core.h +++ b/main_func/regularizers_CPU/TGV_PD_core.h @@ -23,6 +23,7 @@ limitations under the License. #include <memory.h> #include <stdio.h> #include "omp.h" +#include "utils.h" /* 2D functions */ float DualP_2D(float *U, float *V1, float *V2, float *P1, float *P2, int dimX, int dimY, int dimZ, float sigma); @@ -32,4 +33,4 @@ float ProjQ_2D(float *Q1, float *Q2, float *Q3, int dimX, int dimY, int dimZ, fl float DivProjP_2D(float *U, float *A, float *P1, float *P2, int dimX, int dimY, int dimZ, float lambda, float tau); float UpdV_2D(float *V1, float *V2, float *P1, float *P2, float *Q1, float *Q2, float *Q3, int dimX, int dimY, int dimZ, float tau); float newU(float *U, float *U_old, int dimX, int dimY, int dimZ); -float copyIm(float *A, float *U, int dimX, int dimY, int dimZ); +//float copyIm(float *A, float *U, int dimX, int dimY, int dimZ); |