📄 nlmeans.cpp
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/*----------------------------------------------------------------------------------------- File : nlmeans.cpp Description : Example for the CImg plugin: non-local means filter test: (cpu: intel pentium 4 2.60GHz) 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 Copyright : Jerome Boulanger - http://www.irisa.fr/vista/Equipe/People/Jerome.Boulanger.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;// The undef below is necessary when using a non-standard compiler.#ifdef cimg_use_visualcpp6#define std#endifint 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",(char*)NULL,"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.dimx()*zoom),(int)(img.dimy()*zoom),(int)(img.dimz()*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 //--------------------- long tic = cimg::time(); CImg<> dest; dest = img.get_nlmeans(patch_size,lambda,alpha,sigma,sampling); long 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.f+128.0f).display("Original + Restored + Estimated Noise"); else { CImgList<>(original,img,dest,(dest-img)*2.f+128.0f,(dest-original)*2.f+128.0f).display("Original + Noisy + Restored + Estimated Noise + Original Noise"); } } return 0;}
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