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/*=========================================================================
Program: Insight Segmentation & Registration Toolkit
Module: itkDiscreteGaussianDerivativeImageFilterTest.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.
=========================================================================*/
// Author : Ivn Maca (imacia@vicomtech.org)
// Date : 02/01/2009
// VICOMTech, Spain
// http://www.vicomtech.org
// Description : calculates the gaussian derivatives at non-zero
// points of a gaussian input image. For derivative calculation the class
// itkDiscreteGaussianDerivativeImageFilter is used. This example operates on 2D images.
#include "itkImage.h"
#include "itkImageFileReader.h"
#include "itkImageFileWriter.h"
#include "itkRescaleIntensityImageFilter.h"
#include "itkDiscreteGaussianDerivativeImageFilter.h"
#include "itkSimpleFilterWatcher.h"
int itkDiscreteGaussianDerivativeImageFilterTest( int argc, char* argv[] )
{
// Verify the number of parameters in the command line
if( argc < 6 )
{
std::cerr << "Usage: " << std::endl;
std::cerr << argv[0] << " inputFileName outputFileName orderX orderY sigma (maximum_error) (maximum_kernel_width)" << std::endl;
return EXIT_FAILURE;
}
const unsigned int Dimension = 2;
//const unsigned int Dimension = 3;
typedef float PixelType;
typedef unsigned short OutputPixelType;
typedef itk::Image<PixelType, Dimension> ImageType;
typedef itk::Image<OutputPixelType, Dimension> OutputImageType;
typedef itk::ImageFileReader< ImageType > ReaderType;
ReaderType::Pointer reader = ReaderType::New();
reader->SetFileName( argv[1] );
try
{
reader->Update();
}
catch ( itk::ExceptionObject &err)
{
std::cout << "ExceptionObject caught !" << std::endl;
std::cout << err << std::endl;
return EXIT_FAILURE;
}
typedef itk::DiscreteGaussianDerivativeImageFilter< ImageType, ImageType > DerivativeFilterType;
DerivativeFilterType::Pointer derivativeFilter = DerivativeFilterType::New();
derivativeFilter->SetInput( reader->GetOutput() );
// Now proceed to apply the gaussian derivative filter in both directions
double maxError = 0.001;
unsigned int maxKernelWidth = 100;
if( argc >= 7 )
{
maxError = atof( argv[6] );
}
else if( argc >= 8 )
{
maxError = atof( argv[6] );
maxKernelWidth = atoi( argv[7] );
}
DerivativeFilterType::OrderArrayType order;
order[0] = atoi( argv[3] );
order[1] = atoi( argv[4] );
double variance = atof( argv[5] );
variance *= variance;
derivativeFilter->SetMaximumError( maxError );
derivativeFilter->SetMaximumKernelWidth( maxKernelWidth );
derivativeFilter->SetVariance( variance );
derivativeFilter->SetOrder( order );
itk::SimpleFilterWatcher watcher(derivativeFilter, "derivativeFilter");
typedef itk::RescaleIntensityImageFilter< ImageType, OutputImageType >
RescaleFilterType;
RescaleFilterType::Pointer rescaler = RescaleFilterType::New();
rescaler->SetOutputMinimum( itk::NumericTraits<OutputPixelType>::min() );
rescaler->SetOutputMaximum( itk::NumericTraits<OutputPixelType>::max() );
rescaler->SetInput( derivativeFilter->GetOutput() );
typedef itk::ImageFileWriter< OutputImageType > WriterType;
WriterType::Pointer writer = WriterType::New();
writer->SetFileName( argv[2] );
writer->SetInput( rescaler->GetOutput() );
try
{
writer->Update();
}
catch ( itk::ExceptionObject &err)
{
std::cout << "ExceptionObject caught !" << std::endl;
std::cout << err << std::endl;
return EXIT_FAILURE;
}
return EXIT_SUCCESS;
}
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