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/*=========================================================================
Program: Insight Segmentation & Registration Toolkit
Module: GradientRecursiveGaussianImageFilter.cxx
Language: C++
Date: $Date$
Version: $Revision$
Copyright (c) Insight Software Consortium. All rights reserved.
See ITKCopyright.txt or http://www.itk.org/HTML/Copyright.htm for details.
This software is distributed WITHOUT ANY WARRANTY; without even
the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
PURPOSE. See the above copyright notices for more information.
=========================================================================*/
#if defined(_MSC_VER)
#pragma warning ( disable : 4786 )
#endif
#ifdef __BORLANDC__
#define ITK_LEAN_AND_MEAN
#endif
// Software Guide : BeginLatex
//
// This example illustrates the use of the \doxygen{GradientRecursiveGaussianImageFilter}.
//
// \index{itk::Gradient\-Recursive\-Gaussian\-Image\-Filter}
//
// Software Guide : EndLatex
#include "itkImage.h"
#include "itkImageFileReader.h"
#include "itkImageFileWriter.h"
// Software Guide : BeginLatex
//
// The first step required to use this filter is to include its header
// file.
//
// \index{itk::Gradient\-Recursive\-Gaussian\-Image\-Filter!header}
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
#include "itkGradientRecursiveGaussianImageFilter.h"
// Software Guide : EndCodeSnippet
int main( int argc, char * argv[] )
{
if( argc < 4 )
{
std::cerr << "Usage: " << std::endl;
std::cerr << argv[0] << " inputImageFile outputVectorImageFile sigma" << std::endl;
return EXIT_FAILURE;
}
// Software Guide : BeginLatex
//
// Types should be instantiated based on the pixels of the input and
// output images.
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
const unsigned int Dimension = 3;
typedef float InputPixelType;
typedef float OutputComponentPixelType;
typedef itk::CovariantVector<
OutputComponentPixelType, Dimension > OutputPixelType;
// Software Guide : EndCodeSnippet
// Software Guide : BeginLatex
//
// With them, the input and output image types can be instantiated.
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
typedef itk::Image< InputPixelType, Dimension > InputImageType;
typedef itk::Image< OutputPixelType, Dimension > OutputImageType;
// Software Guide : EndCodeSnippet
typedef itk::ImageFileReader< InputImageType > ReaderType;
// Software Guide : BeginLatex
//
// The filter type is now instantiated using both the input image and the
// output image types.
//
// \index{itk::Gradient\-Recursive\-Gaussian\-Image\-Filter!Instantiation}
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
typedef itk::GradientRecursiveGaussianImageFilter<
InputImageType, OutputImageType > FilterType;
// Software Guide : EndCodeSnippet
ReaderType::Pointer reader = ReaderType::New();
reader->SetFileName( argv[1] );
// Software Guide : BeginLatex
//
// A filter object is created by invoking the \code{New()} method and
// assigning the result to a \doxygen{SmartPointer}.
//
// \index{itk::Gradient\-Recursive\-Gaussian\-Image\-Filter!New()}
// \index{itk::Gradient\-Recursive\-Gaussian\-Image\-Filter!Pointer}
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
FilterType::Pointer filter = FilterType::New();
// Software Guide : EndCodeSnippet
// Software Guide : BeginLatex
//
// The input image can be obtained from the output of another filter. Here,
// an image reader is used as source.
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
filter->SetInput( reader->GetOutput() );
// Software Guide : EndCodeSnippet
// Software Guide : BeginLatex
//
// The standard deviation of the Gaussian smoothing kernel is now set.
//
// \index{itk::Gradient\-Recursive\-Gaussian\-Image\-Filter!SetSigma()}
// \index{SetSigma()!itk::Gradient\-Recursive\-Gaussian\-Image\-Filter}
//
// Software Guide : EndLatex
const double sigma = atof( argv[3] );
// Software Guide : BeginCodeSnippet
filter->SetSigma( sigma );
// Software Guide : EndCodeSnippet
// Software Guide : BeginLatex
//
// Finally the filter is executed by invoking the \code{Update()} method.
//
// \index{itk::Gradient\-Recursive\-Gaussian\-Image\-Filter!Update()}
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
filter->Update();
// Software Guide : EndCodeSnippet
// Software Guide : BeginLatex
//
// If connected to other filters in a pipeline, this filter will
// automatically update when any downstream filters are updated. For
// example, we may connect this gradient magnitude filter to an image file
// writer and then update the writer.
//
// Software Guide : EndLatex
typedef itk::ImageFileWriter< OutputImageType > WriterType;
WriterType::Pointer writer = WriterType::New();
writer->SetFileName( argv[2] );
// Software Guide : BeginCodeSnippet
writer->SetInput( filter->GetOutput() );
writer->Update();
// Software Guide : EndCodeSnippet
// Software Guide : BeginLatex
//
//
//
// Software Guide : EndLatex
return EXIT_SUCCESS;
}
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