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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.
*
*=========================================================================*/
#ifndef itkLandweberDeconvolutionImageFilter_h
#define itkLandweberDeconvolutionImageFilter_h
#include "itkIterativeDeconvolutionImageFilter.h"
#include "itkComplexConjugateImageAdaptor.h"
#include "itkTernaryFunctorImageFilter.h"
namespace itk
{
namespace Functor
{
/** \class LandweberMethod
* \brief Functor class for computing a Landweber iteration.
* \ingroup ITKDeconvolution
*/
template< typename TInput1, typename TInput2, typename TInput3, typename TOutput >
class ITK_TEMPLATE_EXPORT LandweberMethod
{
public:
LandweberMethod() {}
~LandweberMethod() {}
bool operator!=(const LandweberMethod &) const
{
return false;
}
bool operator==(const LandweberMethod & other) const
{
return !( *this != other );
}
inline TOutput operator()(const TInput1 & estimateFT,
const TInput2 & kernelFT,
const TInput2 & inputFT) const
{
return m_Alpha * std::conj( kernelFT ) * inputFT +
( NumericTraits< typename TInput1::value_type >::OneValue() - m_Alpha * std::norm( kernelFT ) ) * estimateFT;
}
typename TInput1::value_type m_Alpha;
};
} // end namespace Functor
/** \class LandweberDeconvolutionImageFilter
* \brief Deconvolve an image using the Landweber deconvolution
* algorithm.
*
* This filter implements the Landweber deconvolution algorthm as
* defined in Bertero M and Boccacci P, "Introduction to Inverse
* Problems in Imaging", 1998. The algorithm assumes that the input
* image has been formed by a linear shift-invariant system with a
* known kernel.
*
* The Landweber algorithm converges to a solution that minimizes the
* sum of squared errors \f$||f \otimes h - g||\f$ where \f$f\f$ is
* the estimate of the unblurred image, \f$\otimes\f$ is the
* convolution operator, \f$h\f$ is the blurring kernel, and \f$g\f$ is
* the blurred input image. As such, it is best suited for images that
* have zero-mean Gaussian white noise.
*
* This is the base implementation of the Landweber algorithm. It may
* produce results with negative values. For a version of this
* algorithm that enforces a positivity constraint on each
* intermediate solution, see ProjectedLandweberDeconvolutionImageFilter.
*
* This code was adapted from the Insight Journal contribution:
*
* "Deconvolution: infrastructure and reference algorithms"
* by Gaetan Lehmann
* https://hdl.handle.net/10380/3207
*
* \author Gaetan Lehmann, Biologie du Developpement et de la Reproduction, INRA de Jouy-en-Josas, France
* \author Cory Quammen, The University of North Carolina at Chapel Hill
*
* \ingroup ITKDeconvolution
* \sa IterativeDeconvolutionImageFilter
* \sa RichardsonLucyDeconvolutionImageFilter
* \sa ProjectedLandweberDeconvolutionImageFilter
*/
template< typename TInputImage, typename TKernelImage=TInputImage, typename TOutputImage=TInputImage, typename TInternalPrecision=double >
class ITK_TEMPLATE_EXPORT LandweberDeconvolutionImageFilter :
public IterativeDeconvolutionImageFilter< TInputImage, TKernelImage, TOutputImage, TInternalPrecision >
{
public:
/** Standard typedefs. */
typedef LandweberDeconvolutionImageFilter Self;
typedef IterativeDeconvolutionImageFilter< TInputImage,
TKernelImage,
TOutputImage,
TInternalPrecision > Superclass;
typedef SmartPointer< Self > Pointer;
typedef SmartPointer< const Self > ConstPointer;
/** Other useful typedefs. */
typedef TInputImage InputImageType;
typedef TKernelImage KernelImageType;
typedef TOutputImage OutputImageType;
/** Internal types used by the FFT filters. */
typedef typename Superclass::InternalImageType InternalImageType;
typedef typename Superclass::InternalImagePointerType InternalImagePointerType;
typedef typename Superclass::InternalComplexType InternalComplexType;
typedef typename Superclass::InternalComplexImageType InternalComplexImageType;
typedef typename Superclass::InternalComplexImagePointerType InternalComplexImagePointerType;
/** Method for creation through the object factory. */
itkNewMacro(Self);
/** Runtime information support. */
itkTypeMacro(LandweberDeconvolutionImageFilter,
IterativeDeconvolutionImageFilter);
/** Set/get relaxation factor. */
itkSetMacro(Alpha, double);
itkGetMacro(Alpha, double);
protected:
LandweberDeconvolutionImageFilter();
virtual ~LandweberDeconvolutionImageFilter() ITK_OVERRIDE;
virtual void Initialize(ProgressAccumulator * progress,
float progressWeight,
float iterationProgressWeight) ITK_OVERRIDE;
virtual void Iteration(ProgressAccumulator * progress,
float iterationProgressWeight) ITK_OVERRIDE;
virtual void Finish(ProgressAccumulator *progress, float progressWeight) ITK_OVERRIDE;
typedef typename Superclass::FFTFilterType FFTFilterType;
typedef typename Superclass::IFFTFilterType IFFTFilterType;
virtual void PrintSelf(std::ostream & os, Indent indent) const ITK_OVERRIDE;
private:
ITK_DISALLOW_COPY_AND_ASSIGN(LandweberDeconvolutionImageFilter);
double m_Alpha;
InternalComplexImagePointerType m_TransformedInput;
typedef Functor::LandweberMethod< InternalComplexType,
InternalComplexType,
InternalComplexType,
InternalComplexType > LandweberFunctor;
typedef TernaryFunctorImageFilter< InternalComplexImageType,
InternalComplexImageType,
InternalComplexImageType,
InternalComplexImageType,
LandweberFunctor > LandweberFilterType;
typename LandweberFilterType::Pointer m_LandweberFilter;
typename IFFTFilterType::Pointer m_IFFTFilter;
};
} // end namespace itk
#ifndef ITK_MANUAL_INSTANTIATION
#include "itkLandweberDeconvolutionImageFilter.hxx"
#endif
#endif
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