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/*
#
# 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;
}
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