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/*=========================================================================
*
* Copyright Insight Software Consortium
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0.txt
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*
*=========================================================================*/
#include "itkHistogramMatchingImageFilter.h"
#include "itkCommand.h"
/**
* This file tests the functionality of the HistogramMatchingImageFilter.
* This test uses artificial data, where we multiply different intensity
* classes by different factors and test whether we can recover the
* reference image.
*/
double refPattern( unsigned long offset )
{
if ( offset < 40 ) { return 5.0; }
if ( offset < 160 ) { return 10.0; }
if ( offset < 200 ) { return 15.0; }
if ( offset < 320 ) { return 20.0; }
return 0.0;
}
double srcPattern( unsigned long offset )
{
if ( offset < 40 ) { return 5.0 * 1.5; }
if ( offset < 160 ) { return 10.0 * 0.9; }
if ( offset < 200 ) { return 15.0 * 1.0; }
if ( offset < 320 ) { return 20.0 * 0.8; }
return 0.0;
}
namespace
{
// The following classe is used to support callbacks
// on the filter in the pipeline that follows later
class ShowProgressObject
{
public:
ShowProgressObject(itk::ProcessObject* o)
{m_Process = o;}
void ShowProgress()
{std::cout << "Progress " << m_Process->GetProgress() << std::endl;}
itk::ProcessObject::Pointer m_Process;
};
}
template <typename TScalar>
int itkHistogramMatchingImageFilterTest()
{
typedef TScalar PixelType;
enum {ImageDimension = 3};
typedef itk::Image<PixelType,ImageDimension> ImageType;
typedef itk::ImageRegionIterator<ImageType> Iterator;
typename ImageType::SizeType size;
size[0] = 30;
size[1] = 20;
size[2] = 2;
typename ImageType::RegionType region;
region.SetSize( size );
typename ImageType::Pointer reference = ImageType::New();
typename ImageType::Pointer source = ImageType::New();
reference->SetLargestPossibleRegion( region );
reference->SetBufferedRegion( region );
reference->Allocate();
// Change the origin of the reference image.
typename ImageType::PointType origin;
origin[0] = 1.0;
origin[1] = 10.0;
origin[2] = 100.0;
reference->SetOrigin(origin);
source->SetLargestPossibleRegion( region );
source->SetBufferedRegion( region );
source->Allocate();
Iterator refIter( reference, region );
Iterator srcIter( source, region );
unsigned long counter = 0;
while ( !refIter.IsAtEnd() )
{
refIter.Set( static_cast<PixelType>( refPattern( counter ) ) );
srcIter.Set( static_cast<PixelType>( srcPattern( counter ) ) );
++refIter;
++srcIter;
++counter;
}
typedef itk::HistogramMatchingImageFilter<ImageType,ImageType> FilterType;
typename FilterType::Pointer filter = FilterType::New();
filter->SetReferenceImage( reference );
filter->SetSourceImage( source );
filter->SetNumberOfHistogramLevels( 50 );
filter->SetNumberOfMatchPoints( 8 );
filter->ThresholdAtMeanIntensityOn();
ShowProgressObject progressWatch(filter);
itk::SimpleMemberCommand<ShowProgressObject>::Pointer command;
command = itk::SimpleMemberCommand<ShowProgressObject>::New();
command->SetCallbackFunction(&progressWatch,
&ShowProgressObject::ShowProgress);
filter->AddObserver(itk::ProgressEvent(), command);
filter->Update();
filter->Print( std::cout );
// Walk the output and compare with reference
Iterator outIter( filter->GetOutput(), region );
refIter.GoToBegin();
bool passed = true;
while( !outIter.IsAtEnd() )
{
PixelType diff = refIter.Get() - outIter.Get();
if ( itk::Math::abs( diff ) > 1 )
{
passed = false;
std::cout << "Test failed at: " << outIter.GetIndex() << " ";
std::cout << "Output value: " << outIter.Get() << " ";
std::cout << "Ref value: " << refIter.Get() << std::endl;
}
++outIter;
++refIter;
}
// Exercise auxiliary functions
std::cout << "Exercise auxiliary functions" << std::endl;
std::cout << filter->GetNumberOfHistogramLevels() << std::endl;
std::cout << filter->GetNumberOfMatchPoints() << std::endl;
std::cout << "Source Histogram: " <<
filter->GetSourceHistogram() << std::endl;
std::cout << "Reference Histogram: " <<
filter->GetReferenceHistogram() << std::endl;
std::cout << "Output Histogram: " <<
filter->GetOutputHistogram() << std::endl;
std::cout << "Threshold At Mean Intensity? ";
std::cout << filter->GetThresholdAtMeanIntensity() << std::endl;
filter->ThresholdAtMeanIntensityOff();
filter->Update();
filter->Print( std::cout );
if ( !passed )
{
std::cout << "Test failed." << std::endl;
return EXIT_FAILURE;
}
std::cout << "Test passed." << std::endl;
return EXIT_SUCCESS;
}
int itkHistogramMatchingImageFilterTest(int, char* [] )
{
if(itkHistogramMatchingImageFilterTest<float>() != EXIT_SUCCESS)
{
return EXIT_FAILURE;
}
#if !defined(ITKV3_COMPATIBILITY)
if(itkHistogramMatchingImageFilterTest<long>() != EXIT_SUCCESS)
{
return EXIT_FAILURE;
}
#endif
if(itkHistogramMatchingImageFilterTest<unsigned long>() != EXIT_SUCCESS)
{
return EXIT_FAILURE;
}
if(itkHistogramMatchingImageFilterTest<int>() != EXIT_SUCCESS)
{
return EXIT_FAILURE;
}
if(itkHistogramMatchingImageFilterTest<unsigned int>() != EXIT_SUCCESS)
{
return EXIT_FAILURE;
}
if(itkHistogramMatchingImageFilterTest<short>() != EXIT_SUCCESS)
{
return EXIT_FAILURE;
}
if(itkHistogramMatchingImageFilterTest<unsigned short>() != EXIT_SUCCESS)
{
return EXIT_FAILURE;
}
if(itkHistogramMatchingImageFilterTest<char>() != EXIT_SUCCESS)
{
return EXIT_FAILURE;
}
if(itkHistogramMatchingImageFilterTest<unsigned char>() != EXIT_SUCCESS)
{
return EXIT_FAILURE;
}
return EXIT_SUCCESS;
}
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