/* # # File : use_nlmeans.cpp # ( C++ source file ) # # Description : Example of use for the CImg plugin 'plugins/nlmeans.h'. # This file is a part of the CImg Library project. # ( http://cimg.eu ) # # Copyright : Jerome Boulanger # ( http://www.irisa.fr/vista/Equipe/People/Jerome.Boulanger.html ) # # Benchmark : (CPU intel pentium 4 2.60GHz) compiled with cimg_debug=0. # patch lambda* alpha T sigma PSNR # 3x3 15 9x9 3.6s 20 28.22 # 5x5 17 15x15 22.2s 20 27.91 # 7x7 42 21x21 80.0s 20 28.68 # # License : CeCILL v2.0 # ( http://www.cecill.info/licences/Licence_CeCILL_V2-en.html ) # # This software is governed by the CeCILL license under French law and # abiding by the rules of distribution of free software. You can use, # modify and/ or redistribute the software under the terms of the CeCILL # license as circulated by CEA, CNRS and INRIA at the following URL # "http://www.cecill.info". # # As a counterpart to the access to the source code and rights to copy, # modify and redistribute granted by the license, users are provided only # with a limited warranty and the software's author, the holder of the # economic rights, and the successive licensors have only limited # liability. # # In this respect, the user's attention is drawn to the risks associated # with loading, using, modifying and/or developing or reproducing the # software by the user in light of its specific status of free software, # that may mean that it is complicated to manipulate, and that also # therefore means that it is reserved for developers and experienced # professionals having in-depth computer knowledge. Users are therefore # encouraged to load and test the software's suitability as regards their # requirements in conditions enabling the security of their systems and/or # data to be ensured and, more generally, to use and operate it in the # same conditions as regards security. # # The fact that you are presently reading this means that you have had # knowledge of the CeCILL license and that you accept its terms. # */ #define cimg_plugin "plugins/nlmeans.h" #include "CImg.h" using namespace cimg_library; #ifndef cimg_imagepath #define cimg_imagepath "img/" #endif // Main procedure //---------------- int main(int argc,char **argv) { // Read command line argument s //----------------------------- cimg_usage("Non-local means denoising algorithm.\n [1] Buades, A. Coll, B. and Morel, J.: A review of image " "denoising algorithms, with a new one. Multiscale Modeling and Simulation: A SIAM Interdisciplinary " "Journal 4 (2004) 490-530 \n [2] Gasser, T. Sroka,L. Jennen Steinmetz,C. Residual variance and residual " "pattern nonlinear regression. Biometrika 73 (1986) 625-659 \n Build : "); // input/output and general options const char *file_i = cimg_option("-i",cimg_imagepath "milla.bmp","Input image"); const char *file_o = cimg_option("-o",(char*)NULL,"Output file"); const double zoom = cimg_option("-zoom",1.0,"Image magnification"); const double noiseg = cimg_option("-ng",0.0,"Add gauss noise before aplying the algorithm"); const double noiseu = cimg_option("-nu",0.0,"Add uniform noise before applying the algorithm"); const double noises = cimg_option("-ns",0.0,"Add salt&pepper noise before applying the algorithm"); const unsigned int visu = cimg_option("-visu",1,"Visualization step (0=no visualization)"); // non local means options const int patch_size = cimg_option("-p",1,"Half size of the patch (2p+1)x(2p+1)"); const float lambda = (float)cimg_option("-lambda",-1.0f,"Bandwidth as defined in [1] (-1 : automatic bandwidth)"); const double sigma = cimg_option("-sigma",-1,"Noise standard deviation (-1 : robust estimation)"); const int alpha = cimg_option("-alpha",3,"Neighborhood size (3)"); const int sampling = cimg_option("-sampling",1,"Sampling of the patch (1: slow, 2: fast)"); // Read image //------------ CImg<> img; if (file_i) { img = CImg<>(file_i); if (zoom>1) img.resize((int)(img.width()*zoom),(int)(img.height()*zoom),(int)(img.depth()*zoom),-100,3); } else throw CImgException("You need to specify at least one input image (option -i)"); CImg<> original=img; // Add some noise //----------------- img.noise(noiseg,0).noise(noiseu,1).noise(noises,2); // Apply the filter //--------------------- cimg_uint64 tic = cimg::time(); CImg<> dest; dest = img.get_nlmeans(patch_size,lambda,alpha,sigma,sampling); cimg_uint64 tac = cimg::time(); // Save result //----------------- if (file_o) dest.cut(0,255.f).save(file_o); // Display (option -visu) //----------------------- if (visu){ fprintf(stderr,"Image computed in %f s \n",(float)(tac - tic)/1000.); fprintf(stderr,"The pnsr is %f \n", 20.*std::log10(255./std::sqrt( (dest - original).pow(2).sum()/original.size() ))); if (noiseg==0 && noiseu==0 && noises==0) CImgList<>(original,dest,((dest - original)*=2)+=128).display("Original + Restored + Estimated Noise"); else { CImgList<>(original,img,dest,((dest - img)*=2)+=128,((dest - original)*=2)+=128). display("Original + Noisy + Restored + Estimated Noise + Original Noise"); } } return 0; }