vigra - smooth.cxx

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smooth.cxx |

Smooth an image using Recursive convolution functions functions: smooth.cxx
Usage: `example_smooth infile outfile`

/************************************************************************/
/* */
/* Copyright 1998-2002 by Ullrich Koethe */
/* */
/* This file is part of the VIGRA computer vision library. */
/* The VIGRA Website is */
/* http://hci.iwr.uni-heidelberg.de/vigra/ */
/* Please direct questions, bug reports, and contributions to */
/* ullrich.koethe@iwr.uni-heidelberg.de or */
/* vigra@informatik.uni-hamburg.de */
/* */
/* Permission is hereby granted, free of charge, to any person */
/* obtaining a copy of this software and associated documentation */
/* files (the "Software"), to deal in the Software without */
/* restriction, including without limitation the rights to use, */
/* copy, modify, merge, publish, distribute, sublicense, and/or */
/* sell copies of the Software, and to permit persons to whom the */
/* Software is furnished to do so, subject to the following */
/* conditions: */
/* */
/* The above copyright notice and this permission notice shall be */
/* included in all copies or substantial portions of the */
/* Software. */
/* */
/* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND */
/* EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES */
/* OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND */
/* NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT */
/* HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, */
/* WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING */
/* FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR */
/* OTHER DEALINGS IN THE SOFTWARE. */
/* */
/************************************************************************/
#include <iostream>
#include <vigra/multi_array.hxx>
#include <vigra/convolution.hxx>
#include <vigra/nonlineardiffusion.hxx>
#include <vigra/impex.hxx>
using namespace vigra;
int main(int argc, char ** argv)
{
if(argc != 3)
{
std::cout << "Usage: " << argv[0] << " infile outfile" << std::endl;
std::cout << "(supported formats: " << impexListFormats() << ")" << std::endl;
return 1;
}
// Type of smoothing:
int type;
std::cout << "Type of smoothing (1 = Gauss, 2 = Exponential, 3 = nonlinear) ? ";
std::cin >> type;
// input width of smoothing filter
double scale;
std::cout << "Amount of smoothing (operator scale) ? ";
std::cin >> scale;
double edge_threshold;
if(type == 3)
{
std::cout << "Edge threshold ? ";
std::cin >> edge_threshold;
}
try
{
ImageImportInfo info(argv[1]);
if(info. isGrayscale())
{
MultiArray<2, UInt8> in(info. width(), info. height());
MultiArray<2, float> out(info.width(), info.height());
importImage(info, destImage(in));
switch(type)
{
case 2:
{
// apply recursive filter (exponential filter) to gray image
recursiveSmoothX(in, out, scale);
recursiveSmoothY(out, out, scale);
break;
}
case 3:
{
// apply nonlinear diffusion to gray image
nonlinearDiffusion(in, out,
DiffusivityFunctor<float>(edge_threshold), scale);
break;
}
default:
{
gaussianSmoothing(in, out, scale);
}
}
exportImage(out, ImageExportInfo(argv[2]));
}
else
{
MultiArray<2, RGBValue<UInt8> > in(info. shape());
MultiArray<2, RGBValue<float> > out(info.shape());
importImage(info, in);
switch(type)
{
case 2:
{
// apply recursive filter (exponential filter) to color image
recursiveSmoothX(in, out, scale);
recursiveSmoothY(out, out, scale);
break;
}
case 3:
{
// apply nonlinear diffusion to color image, one band at a time
for(int band = 0; band<3; ++band)
{
nonlinearDiffusion(in.bindElementChannel(band), out.bindElementChannel(band),
DiffusivityFunctor<float>(edge_threshold), scale);
}
break;
}
default:
{
gaussianSmoothing(in, out, scale);
}
}
exportImage(out, ImageExportInfo(argv[2]));
}
}
catch (std::exception & e)
{
std::cout << e.what() << std::endl;
return 1;
}
return 0;
}

© Ullrich Köthe (ullrich.koethe@iwr.uni-heidelberg.de) Heidelberg Collaboratory for Image Processing, University of Heidelberg, Germany | html generated using doxygen and Python vigra 1.11.0 (Fri May 19 2017)