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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.sourceforge.net )

  #

  #  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;

 // The lines below are necessary when using a non-standard compiler as visualcpp6.

 #ifdef cimg_use_visualcpp6

 #define std

 #endif

 #ifdef min

 #undef min

 #undef max

 #endif

 #ifndef cimg_imagepath

 #define cimg_imagepath "img/"

 #endif

 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.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)+=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;

 }