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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 "itkFFTConvolutionImageFilter.h"
#include "itkGaussianImageSource.h"
#include "itkImageFileReader.h"
#include "itkImageFileWriter.h"
#include "itkParametricBlindLeastSquaresDeconvolutionImageFilter.h"
#include "itkTestingMacros.h"
// Define a version of the GaussianImageSource that has only the sigma
// parameters
namespace itk
{
template< typename TOutputImage >
class ExampleImageSource : public GaussianImageSource< TOutputImage >
{
public:
/** Standard typedefs. */
typedef ExampleImageSource Self;
typedef GaussianImageSource< TOutputImage > Superclass;
typedef SmartPointer< Self > Pointer;
typedef SmartPointer< const Self > ConstPointer;
/** Output image typedefs */
typedef TOutputImage OutputImageType;
typedef typename OutputImageType::Pointer OutputImagePointer;
typedef typename OutputImageType::PixelType OutputImagePixelType;
typedef typename OutputImageType::PixelType PixelType;
typedef typename OutputImageType::RegionType RegionType;
typedef typename OutputImageType::SpacingType SpacingType;
typedef typename OutputImageType::PointType PointType;
typedef typename OutputImageType::DirectionType DirectionType;
typedef typename OutputImageType::SizeType SizeType;
typedef typename OutputImageType::SizeValueType SizeValueType;
typedef typename Superclass::ParametersValueType ParametersValueType;
typedef typename Superclass::ParametersType ParametersType;
typedef std::vector< bool > EnabledArrayType;
/** Method for creation through the object factory. */
itkNewMacro(Self);
/** ImageDimension constant */
itkStaticConstMacro(OutputImageDimension,
unsigned int,
TOutputImage::ImageDimension);
/** Run-time type information (and related methods). */
itkTypeMacro(ExampleImageSource, GaussianImageSource);
/** Set the parameters for this source. Setting the parameters does
* not mark the image source as modified; subclasses should override
* this method to forward parameters through setters that call
* Modified(). */
virtual void SetParameters( const ParametersType & parameters ) ITK_OVERRIDE
{
ParametersType gaussianParameters = this->Superclass::GetParameters();
for ( unsigned int i = 0; i < OutputImageDimension; ++i )
{
gaussianParameters[i] = parameters[i];
}
this->Superclass::SetParameters( gaussianParameters );
}
/** Get the parameters for this source. */
virtual ParametersType GetParameters() const ITK_OVERRIDE
{
ParametersType gaussianParameters = this->Superclass::GetParameters();
ParametersType parameters(OutputImageDimension);
for ( unsigned int i = 0; i < OutputImageDimension; ++i )
{
parameters[i] = gaussianParameters[i];
}
return parameters;
}
/** Get the number of parameters. */
virtual unsigned int GetNumberOfParameters() const ITK_OVERRIDE
{
return OutputImageDimension;
}
protected:
ExampleImageSource() {};
virtual ~ExampleImageSource() ITK_OVERRIDE {};
private:
ITK_DISALLOW_COPY_AND_ASSIGN(ExampleImageSource);
};
}
int itkParametricBlindLeastSquaresDeconvolutionImageFilterTest(int argc, char* argv[])
{
if ( argc < 6 )
{
std::cerr << "Usage: " << argv[0]
<< " <input image> <output image> <iterations> <alpha> <beta> [convolution image]"
<< std::endl;
return EXIT_FAILURE;
}
typedef float PixelType;
const unsigned int Dimension = 2;
typedef itk::Image< PixelType, Dimension > ImageType;
typedef itk::ImageFileReader< ImageType > ReaderType;
typedef itk::ImageFileWriter< ImageType > WriterType;
ReaderType::Pointer inputReader = ReaderType::New();
inputReader->SetFileName( argv[1] );
inputReader->Update();
// Create a masked parametric image source so that we can optimize
// for the sigma parameters only.
typedef itk::ExampleImageSource< ImageType > KernelSourceType;
KernelSourceType::Pointer kernelSource = KernelSourceType::New();
kernelSource->SetScale( 1.0 );
KernelSourceType::SizeType size = {{32, 32}};
kernelSource->SetSize( size );
KernelSourceType::PointType origin;
origin[0] = 0.0;
origin[1] = 0.0;
kernelSource->SetOrigin( origin );
KernelSourceType::SpacingType spacing;
spacing[0] = 1.0;
spacing[1] = 1.0;
kernelSource->SetSpacing( spacing );
KernelSourceType::ArrayType sigma;
sigma[0] = 2.0;
sigma[1] = 4.0;
kernelSource->SetSigma( sigma );
KernelSourceType::ArrayType mean;
mean[0] = 0.5 * (size[0] - 1) * spacing[0];
mean[1] = 0.5 * (size[1] - 1) * spacing[1];
kernelSource->SetMean( mean );
// Generate a convolution of the input image with a kernel computed
// from a parametric image source. We'll try to recover those
// parameters later.
typedef itk::FFTConvolutionImageFilter< ImageType > ConvolutionFilterType;
ConvolutionFilterType::Pointer convolutionFilter = ConvolutionFilterType::New();
convolutionFilter->SetInput( inputReader->GetOutput() );
convolutionFilter->NormalizeOn();
convolutionFilter->SetKernelImage( kernelSource->GetOutput() );
// Use the same SizeGreatestPrimeFactor across FFT backends to get
// consistent results.
convolutionFilter->SetSizeGreatestPrimeFactor( 5 );
// Create an instance of the deconvolution filter
typedef itk::ParametricBlindLeastSquaresDeconvolutionImageFilter< ImageType, KernelSourceType >
DeconvolutionFilterType;
DeconvolutionFilterType::Pointer deconvolutionFilter = DeconvolutionFilterType::New();
deconvolutionFilter->SetKernelSource( kernelSource );
deconvolutionFilter->SetSizeGreatestPrimeFactor( 5 );
// Change the sigma settings here to something different
KernelSourceType::ParametersType parameters( kernelSource->GetParameters() );
parameters[0] = 3.0;
parameters[1] = 3.0;
kernelSource->SetParameters( parameters );
deconvolutionFilter->NormalizeOn();
double alpha = atof( argv[4] );
double beta = atof( argv[5] );
deconvolutionFilter->SetAlpha( alpha );
deconvolutionFilter->SetBeta( beta );
deconvolutionFilter->SetInput( convolutionFilter->GetOutput() );
deconvolutionFilter->SetNumberOfIterations( atoi( argv[3] ) );
deconvolutionFilter->UpdateLargestPossibleRegion();
std::cout << "Kernel parameters: " << kernelSource->GetParameters()
<< std::endl;
try
{
WriterType::Pointer writer = WriterType::New();
writer->SetFileName( argv[2] );
writer->SetInput( deconvolutionFilter->GetOutput() );
writer->Update();
}
catch ( itk::ExceptionObject & e )
{
std::cerr << "Unexpected exception caught when writing deconvolution image: "
<< e << std::endl;
return EXIT_FAILURE;
}
KernelSourceType::ParametersValueType expectedSigmaX = 2.90243;
if ( std::abs( kernelSource->GetParameters()[0] - expectedSigmaX ) > 1e-5 )
{
std::cerr << "Kernel parameter[0] should have been " << expectedSigmaX
<< ", was " << kernelSource->GetParameters()[0] << "."
<< std::endl;
return EXIT_FAILURE;
}
KernelSourceType::ParametersValueType expectedSigmaY = 2.90597;
if ( std::abs( kernelSource->GetParameters()[1] - expectedSigmaY ) > 1e-5 )
{
std::cerr << "Kernel parameter[1] should have been " << expectedSigmaY
<< ", was " << kernelSource->GetParameters()[0] << "."
<< std::endl;
return EXIT_FAILURE;
}
// Optionally write the convolution image on which we're testing the
// deconvolution filter
if ( argc >= 7 )
{
try
{
WriterType::Pointer writer = WriterType::New();
writer->SetFileName( argv[6] );
writer->SetInput( convolutionFilter->GetOutput() );
writer->Update();
}
catch ( itk::ExceptionObject & e )
{
std::cerr << "Unexpected exception caught when writing convolution image: "
<< e << std::endl;
return EXIT_FAILURE;
}
}
// Exercise the setters/getters
TEST_SET_GET_VALUE( alpha, deconvolutionFilter->GetAlpha() );
TEST_SET_GET_VALUE( beta, deconvolutionFilter->GetBeta() );
return EXIT_SUCCESS;
}
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