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/*=========================================================================
Program: Insight Segmentation & Registration Toolkit
Module: $RCSfile: itkRecursiveGaussianImageFiltersOnTensorsTest.cxx,v $
Language: C++
Date: $Date: 2006-03-09 03:37:16 $
Version: $Revision: 1.2 $
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.
=========================================================================*/
#include "itkImageRegionIteratorWithIndex.h"
#include "itkImageFileReader.h"
#include "itkImageFileWriter.h"
#include "itkImageLinearConstIteratorWithIndex.h"
#include "itkImageLinearIteratorWithIndex.h"
#include "itkRecursiveGaussianImageFilter.h"
#include "itkSymmetricSecondRankTensor.h"
#include "vnl/vnl_math.h"
int itkRecursiveGaussianImageFiltersOnTensorsTest(int, char* [] )
{
// In this test, we will create a 9x9 image of tensors with pixels (4,4)
// and (1,6) set to 'tensor1'. We will filter it using
// RecursiveGaussianImageFilter and compare a few filtered pixels.
//
const unsigned int Dimension = 2;
const double sigma = 1;
const double tolerance = 0.001;
//Create ON and OFF tensors.
typedef itk::SymmetricSecondRankTensor<double,3> Double3DTensorType;
Double3DTensorType tensor0(0.0);
Double3DTensorType tensor1;
tensor1(0,0) = 1.0;
tensor1(0,1) = 0.0;
tensor1(0,2) = 0.0;
tensor1(1,0) = 0.0; // overrides (0,1)
tensor1(1,1) = 3.0;
tensor1(1,2) = 0.0;
tensor1(2,0) = 0.0; // overrides (0,2)
tensor1(2,1) = 0.0; // overrides (1,2)
tensor1(2,2) = 1.0;
typedef Double3DTensorType PixelType;
typedef itk::Image< PixelType, Dimension > ImageType;
typedef itk::ImageLinearIteratorWithIndex< ImageType > IteratorType;
typedef itk::ImageLinearConstIteratorWithIndex< ImageType > ConstIteratorType;
//Create the 9x9 input image
ImageType::SizeType size;
size.Fill( 9 );
ImageType::IndexType index;
index.Fill( 0 );
ImageType::RegionType region;
region.SetSize( size );
region.SetIndex( index );
ImageType::Pointer inputImage = ImageType::New();
inputImage->SetLargestPossibleRegion( region );
inputImage->SetBufferedRegion( region );
inputImage->SetRequestedRegion( region );
inputImage->Allocate();
inputImage->FillBuffer( tensor0);
std::cout
<< "Apply RecursiveGaussianImageFilter with a 9x9 image, pixels (4,4) "
<< "and (1,6) set to ON."
<< std::endl;
/* Set pixel (4,4) with the value 1
* and pixel (1,6) with the value 2
*/
index[0] = 4;
index[1] = 4;
inputImage->SetPixel( index, tensor1);
index[0] = 1;
index[1] = 6;
inputImage->SetPixel( index, tensor1);
//Gaussian filter this image now. Each component of the tensor
// is filtered independently.
//
typedef itk::RecursiveGaussianImageFilter<
ImageType, ImageType > FilterType;
FilterType::Pointer filterX = FilterType::New();
FilterType::Pointer filterY = FilterType::New();
filterX->SetDirection( 0 ); // 0 --> X direction
filterY->SetDirection( 1 ); // 1 --> Y direction
filterX->SetOrder( FilterType::ZeroOrder );
filterY->SetOrder( FilterType::ZeroOrder );
filterX->SetNormalizeAcrossScale( false );
filterY->SetNormalizeAcrossScale( false );
filterX->SetInput( inputImage );
filterY->SetInput( filterX->GetOutput() );
filterX->SetSigma( sigma );
filterY->SetSigma( sigma );
try
{
filterY->Update();
}
catch ( itk::ExceptionObject &err)
{
std::cout << "ExceptionObject caught a !" << std::endl;
std::cout << err << std::endl;
return -1;
}
//Test a few pixels of the fitlered image
//
ImageType::Pointer filteredImage = filterY->GetOutput();
ConstIteratorType cit( filteredImage, filteredImage->GetRequestedRegion() );
cit.SetDirection(0);
/* Print out all Tensor values.
for ( cit.GoToBegin(); ! cit.IsAtEnd(); cit.NextLine())
{
cit.GoToBeginOfLine();
while ( ! cit.IsAtEndOfLine() )
{
std::cout << "Tensor at index: " << cit.GetIndex() << " is " <<
cit.Get() << std::endl;
++cit;
}
}
*/
index[0] = 4;
index[1] = 4;
cit.SetIndex(index);
if( vnl_math_abs(cit.Get()(0,0) - 0.160313) > tolerance )
{
std::cout << "[FAILED] Tensor(0,0) at index (4,4) must be 0.1603 but is "
<< cit.Get()(0,0) << std::endl;
return EXIT_FAILURE;
}
index[0]=6;
index[1]=6;
cit.SetIndex(index);
if( vnl_math_abs(cit.Get()(3,3) -0.0026944) > tolerance )
{
std::cout << "[FAILED] Tensor(3,3) at index (6,6) must be 0.0026944 but is "
<< cit.Get()(3,3) << std::endl;
return EXIT_FAILURE;
}
std::cout << "[PASSED]" << std::endl;
return EXIT_SUCCESS;
}
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