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