itkWienerDeconvolutionImageFilter.h

Go to the documentation of this file.

/*=========================================================================
 *
 *  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 __itkWienerDeconvolutionImageFilter_h
#define __itkWienerDeconvolutionImageFilter_h

#include "itkInverseDeconvolutionImageFilter.h"

namespace itk
{
template< class TInputImage, class TKernelImage = TInputImage, class TOutputImage = TInputImage, class TInternalPrecision=double >
class ITK_EXPORT WienerDeconvolutionImageFilter :
  public InverseDeconvolutionImageFilter< TInputImage, TKernelImage, TOutputImage >
{
public:
  typedef WienerDeconvolutionImageFilter                         Self;
  typedef FFTConvolutionImageFilter< TInputImage, TOutputImage > Superclass;
  typedef SmartPointer< Self >                                   Pointer;
  typedef SmartPointer< const Self >                             ConstPointer;

  itkNewMacro(Self);

  itkTypeMacro(WienerDeconvolutionImageFilter, InverseDeconvolutionImageFilter);

  itkStaticConstMacro(ImageDimension, unsigned int,
                      TInputImage::ImageDimension);

  typedef TInputImage                           InputImageType;
  typedef TOutputImage                          OutputImageType;
  typedef TKernelImage                          KernelImageType;
  typedef typename Superclass::InputPixelType   InputPixelType;
  typedef typename Superclass::OutputPixelType  OutputPixelType;
  typedef typename Superclass::KernelPixelType  KernelPixelType;
  typedef typename Superclass::InputIndexType   InputIndexType;
  typedef typename Superclass::OutputIndexType  OutputIndexType;
  typedef typename Superclass::KernelIndexType  KernelIndexType;
  typedef typename Superclass::InputSizeType    InputSizeType;
  typedef typename Superclass::OutputSizeType   OutputSizeType;
  typedef typename Superclass::KernelSizeType   KernelSizeType;
  typedef typename Superclass::SizeValueType    SizeValueType;
  typedef typename Superclass::InputRegionType  InputRegionType;
  typedef typename Superclass::OutputRegionType OutputRegionType;
  typedef typename Superclass::KernelRegionType KernelRegionType;

  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;

  itkSetMacro(NoiseVariance, double);
  itkGetConstMacro(NoiseVariance, double);

protected:
  WienerDeconvolutionImageFilter();
  ~WienerDeconvolutionImageFilter() {}

  void GenerateData();

  virtual void PrintSelf( std::ostream & os, Indent indent ) const;

private:
  WienerDeconvolutionImageFilter(const Self &); //purposely not implemented
  void operator=(const Self &);                 //purposely not implemented

  double m_NoiseVariance;
};

namespace Functor
{
template< class TPixel >
class WienerDeconvolutionFunctor
{
public:
  WienerDeconvolutionFunctor() { m_KernelZeroMagnitudeThreshold = 0.0; }
  ~WienerDeconvolutionFunctor() {}

  bool operator!=( const WienerDeconvolutionFunctor & ) const
  {
    return false;
  }
  bool operator==( const WienerDeconvolutionFunctor & other) const
  {
    return !(*this != other);
  }
  inline TPixel operator()(const TPixel & I, const TPixel & H) const
  {
    TPixel Pn = m_NoisePowerSpectralDensityConstant;

    // We estimate the power spectral density of the output image to
    // be the same as the power spectral density of the blurred input
    // minus the power spectral density of the noise.
    TPixel Pf = std::norm( I );

    TPixel denominator = std::norm( H ) + ( Pn / (Pf - Pn) );
    TPixel value = NumericTraits< TPixel >::ZeroValue();
    if ( std::abs( denominator ) >= m_KernelZeroMagnitudeThreshold )
      {
      value = I * ( std::conj( H ) / denominator );
      }

    return value;
  }

  void SetNoisePowerSpectralDensityConstant(double constant)
  {
    m_NoisePowerSpectralDensityConstant = constant;
  }
  double GetNoisePowerSpectralDensityConstant() const
  {
    return m_NoisePowerSpectralDensityConstant;
  }

  void SetKernelZeroMagnitudeThreshold(double mu)
  {
    m_KernelZeroMagnitudeThreshold = mu;
  }
  double GetKernelZeroMagnitudeThreshold() const
  {
    return m_KernelZeroMagnitudeThreshold;
  }

private:
  double m_NoisePowerSpectralDensityConstant;
  double m_KernelZeroMagnitudeThreshold;
};
} //namespace Functor

}

#ifndef ITK_MANUAL_INSTANTIATION
#include "itkWienerDeconvolutionImageFilter.hxx"
#endif

#endif