1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
|
/*
* This work is part of the Core Imaging Library developed by
* Visual Analytics and Imaging System Group of the Science Technology
* Facilities Council, STFC
*
* Copyright 2019 Daniil Kazantsev
* Copyright 2019 Srikanth Nagella, Edoardo Pasca
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
* http://www.apache.org/licenses/LICENSE-2.0
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
#include "matrix.h"
#include "mex.h"
#include "PD_TV_core.h"
/* C-OMP implementation of Primal-Dual TV [1] by Chambolle Pock denoising/regularization model (2D/3D case)
*
* Input Parameters:
* 1. Noisy image/volume
* 2. lambdaPar - regularization parameter
* 3. Number of iterations
* 4. eplsilon: tolerance constant
* 5. TV-type: methodTV - 'iso' (0) or 'l1' (1)
* 6. nonneg: 'nonnegativity (0 is OFF by default, 1 is ON)
* 7. lipschitz_const: convergence related parameter
* Output:
* [1] TV - Filtered/regularized image/volume
* [2] Information vector which contains [iteration no., reached tolerance]
*
* [1] Antonin Chambolle, Thomas Pock. "A First-Order Primal-Dual Algorithm for Convex Problems with Applications to Imaging", 2010
*/
void mexFunction(
int nlhs, mxArray *plhs[],
int nrhs, const mxArray *prhs[])
{
int number_of_dims, iter, methTV, nonneg;
mwSize dimX, dimY, dimZ;
const mwSize *dim_array;
float *Input, *infovec=NULL, *Output=NULL, lambda, epsil, lipschitz_const;
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/3D), Regularization parameter, iterations number, tolerance, penalty type ('iso' or 'l1'), nonnegativity switch, lipschitz_const");
Input = (float *) mxGetData(prhs[0]); /*noisy image (2D/3D) */
lambda = (float) mxGetScalar(prhs[1]); /* regularization parameter */
iter = 400; /* default iterations number */
epsil = 1.0e-06; /* default tolerance constant */
methTV = 0; /* default isotropic TV penalty */
nonneg = 0; /* default nonnegativity switch, off - 0 */
lipschitz_const = 12.0; /* lipschitz_const */
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)) iter = (int) mxGetScalar(prhs[2]); /* iterations number */
if ((nrhs == 4) || (nrhs == 5) || (nrhs == 6) || (nrhs == 7)) epsil = (float) mxGetScalar(prhs[3]); /* tolerance constant */
if ((nrhs == 5) || (nrhs == 6) || (nrhs == 7)) {
char *penalty_type;
penalty_type = mxArrayToString(prhs[4]); /* choosing TV penalty: 'iso' or 'l1', 'iso' is the default */
if ((strcmp(penalty_type, "l1") != 0) && (strcmp(penalty_type, "iso") != 0)) mexErrMsgTxt("Choose TV type: 'iso' or 'l1',");
if (strcmp(penalty_type, "l1") == 0) methTV = 1; /* enable 'l1' penalty */
mxFree(penalty_type);
}
if ((nrhs == 6) || (nrhs == 7)) {
nonneg = (int) mxGetScalar(prhs[5]);
if ((nonneg != 0) && (nonneg != 1)) mexErrMsgTxt("Nonnegativity constraint can be enabled by choosing 1 or off - 0");
}
if (nrhs == 7) lipschitz_const = (float) mxGetScalar(prhs[6]);
/*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));
}
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));
/* running the function */
PDTV_CPU_main(Input, Output, infovec, lambda, iter, epsil, lipschitz_const, methTV, nonneg, dimX, dimY, dimZ);
}
|