⭐ 欢迎来到虫虫下载站! | 📦 资源下载 📁 资源专辑 ℹ️ 关于我们
⭐ 虫虫下载站

📄 nlmeans.cpp

📁 this a image processing program
💻 CPP
字号:
/*-----------------------------------------------------------------------------------------  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;}

⌨️ 快捷键说明

复制代码 Ctrl + C
搜索代码 Ctrl + F
全屏模式 F11
切换主题 Ctrl + Shift + D
显示快捷键 ?
增大字号 Ctrl + =
减小字号 Ctrl + -