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/*=========================================================================
Program: Insight Segmentation & Registration Toolkit
Module: itkGaussianBlurImageFunctionTest.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
#include "itkGaussianBlurImageFunction.h"
#include "itkImage.h"
int itkGaussianBlurImageFunctionTest(int, char* [] )
{
const unsigned int Dimension = 2;
typedef float PixelType;
typedef itk::Image< PixelType, Dimension > ImageType;
typedef itk::GaussianBlurImageFunction< ImageType > GFunctionType;
// Create and allocate the image
ImageType::Pointer image = ImageType::New();
ImageType::SizeType size;
ImageType::IndexType start;
ImageType::RegionType region;
size[0] = 50;
size[1] = 50;
start.Fill( 0 );
region.SetIndex( start );
region.SetSize( size );
image->SetRegions( region );
image->Allocate();
ImageType::PixelType initialValue = 0;
image->FillBuffer( initialValue );
// Fill the image with a straight line
for(unsigned int i=0;i<50;i++)
{
ImageType::IndexType ind;
ind[0]=i;
ind[1]=25;
image->SetPixel(ind,1);
ind[1]=26;
image->SetPixel(ind,1);
}
// Test the derivative of Gaussian image function
GFunctionType::Pointer gaussianFunction = GFunctionType::New();
gaussianFunction->SetInputImage( image );
itk::Index<2> index;
index.Fill(25);
// Testing Set/GetVariance()
std::cout << "Testing Set/GetVariance(): ";
gaussianFunction->SetSigma(5.0);
const GFunctionType::SigmaArrayType & sigma = gaussianFunction->GetSigma();
for(unsigned int i=0;i<Dimension;i++)
{
if( sigma[i] != 5.0)
{
std::cerr << "[FAILED]" << std::endl;
return EXIT_FAILURE;
}
}
std::cout << "[PASSED] " << std::endl;
// Testing Set/GetExtent()
std::cout << "Testing Set/GetExtent(): ";
gaussianFunction->SetExtent(5.0);
const GFunctionType::ExtentArrayType & ext = gaussianFunction->GetExtent();
for(unsigned int i=0;i<Dimension;i++)
{
if( ext[i] != 5.0)
{
std::cerr << "[FAILED]" << std::endl;
return EXIT_FAILURE;
}
}
std::cout << "[PASSED] " << std::endl;
// Testing Set/GetMaximumError()
{
std::cout << "Testing Set/GetMaximumError(): ";
GFunctionType::ErrorArrayType setError;
setError.Fill( 0.05 );
gaussianFunction->SetMaximumError( setError );
const GFunctionType::ErrorArrayType & readError =
gaussianFunction->GetMaximumError();
for(unsigned int i=0;i<Dimension;i++)
{
if( vcl_fabs( setError[i] - readError[i] ) > 1e-6 )
{
std::cerr << "[FAILED]" << std::endl;
return EXIT_FAILURE;
}
}
std::cout << "[PASSED] " << std::endl;
}
// Testing Set/GetMaximumKernelWidth()
{
std::cout << "Testing Set/GetMaximumKernelWidth(): ";
int setKernelWidth = 47;
gaussianFunction->SetMaximumKernelWidth( setKernelWidth );
int readKernelWidth = gaussianFunction->GetMaximumKernelWidth();
if( readKernelWidth != setKernelWidth )
{
std::cerr << "[FAILED]" << std::endl;
return EXIT_FAILURE;
}
std::cout << "[PASSED] " << std::endl;
}
// Testing Set/GetUseImageSpacing()
{
std::cout << "Testing Set/GetUseImageSpacing(): ";
bool useImageSpacing = true;
gaussianFunction->SetUseImageSpacing( useImageSpacing );
if( gaussianFunction->GetUseImageSpacing() != useImageSpacing )
{
std::cerr << "Set/GetUseImageSpacing() FAILED !" << std::endl;
return EXIT_FAILURE;
}
useImageSpacing = false;
gaussianFunction->SetUseImageSpacing( useImageSpacing );
if( gaussianFunction->GetUseImageSpacing() != useImageSpacing )
{
std::cerr << "Set/GetUseImageSpacing() FAILED !" << std::endl;
return EXIT_FAILURE;
}
gaussianFunction->UseImageSpacingOn();
if( gaussianFunction->GetUseImageSpacing() != true )
{
std::cerr << "Set/GetUseImageSpacing() FAILED !" << std::endl;
return EXIT_FAILURE;
}
gaussianFunction->UseImageSpacingOff();
if( gaussianFunction->GetUseImageSpacing() != false )
{
std::cerr << "Set/GetUseImageSpacing() FAILED !" << std::endl;
return EXIT_FAILURE;
}
gaussianFunction->UseImageSpacingOn(); // leave it ON for the next test.
std::cout << "[PASSED] " << std::endl;
}
GFunctionType::OutputType blurredvalue_index;
blurredvalue_index = gaussianFunction->EvaluateAtIndex( index );
GFunctionType::PointType pt;
pt[0]=25.0;
pt[1]=25.0;
GFunctionType::OutputType blurredvalue_point;
blurredvalue_point = gaussianFunction->Evaluate( pt );
GFunctionType::ContinuousIndexType continuousIndex;
continuousIndex.Fill(25);
GFunctionType::OutputType blurredvalue_continuousIndex;
blurredvalue_continuousIndex = gaussianFunction->EvaluateAtContinuousIndex( continuousIndex );
std::cout << "Testing Evaluate(), EvaluateAtIndex() and EvaluateIndex: ";
if( (vcl_fabs(blurredvalue_index-blurredvalue_point)>0.01)
|| blurredvalue_point != blurredvalue_continuousIndex)
{
std::cerr << "[FAILED] : "
<< blurredvalue_index << " : "
<< blurredvalue_point << " : "
<< blurredvalue_continuousIndex << std::endl;
return EXIT_FAILURE;
}
std::cout << "[PASSED] " << std::endl;
std::cout << "Testing Evaluate() : ";
if( vcl_fabs(blurredvalue_point-0.158)> 0.1)
{
std::cerr << "[FAILED]" << std::endl;
return EXIT_FAILURE;
}
std::cout << "[PASSED] " << std::endl;
gaussianFunction->Print( std::cout );
std::cout << "GaussianBlurImageFunctionTest: [DONE] " << std::endl;
return EXIT_SUCCESS;
}
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