itkAnisotropicDiffusionImageFilter.h

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/*=========================================================================

  Program:   Insight Segmentation & Registration Toolkit
  Module:    $RCSfile: itkAnisotropicDiffusionImageFilter.h,v $
  Language:  C++
  Date:      $Date: 2003/02/24 18:46:18 $
  Version:   $Revision: 1.32 $

  Copyright (c) 2002 Insight 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.

=========================================================================*/
#ifndef __itkAnisotropicDiffusionImageFilter_h_
#define __itkAnisotropicDiffusionImageFilter_h_

#include "itkDenseFiniteDifferenceImageFilter.h"
#include "itkAnisotropicDiffusionFunction.h"
#include "itkNumericTraits.h"

namespace itk {

template <class TInputImage, class TOutputImage>
class AnisotropicDiffusionImageFilter
  : public DenseFiniteDifferenceImageFilter<TInputImage, TOutputImage>
{
public:
  typedef AnisotropicDiffusionImageFilter Self;
  typedef DenseFiniteDifferenceImageFilter<TInputImage, TOutputImage>
   Superclass;
  typedef SmartPointer<Self> Pointer;
  typedef SmartPointer<const Self> ConstPointer;

  itkTypeMacro(AnisotropicDiffusionImageFilter,
               DenseFiniteDifferenceImageFilter);

  typedef typename Superclass::InputImageType   InputImageType;
  typedef typename Superclass::OutputImageType  OutputImageType;
  typedef typename Superclass::UpdateBufferType UpdateBufferType;

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

  typedef typename Superclass::PixelType PixelType;
  typedef typename Superclass::TimeStepType TimeStepType;

  itkSetMacro(Iterations, unsigned int);
  itkGetMacro(Iterations, unsigned int);

  itkSetMacro(TimeStep, TimeStepType);
  itkGetMacro(TimeStep, TimeStepType);

  itkSetMacro(ConductanceParameter, double);
  itkGetMacro(ConductanceParameter, double);

  itkSetMacro(ConductanceScalingUpdateInterval, unsigned int);
  itkGetMacro(ConductanceScalingUpdateInterval, unsigned int);
  itkSetMacro(ConductanceScalingParameter, double);
  itkGetMacro(ConductanceScalingParameter, double);

  void SetFixedAverageGradientMagnitude(double a)
    {
      m_FixedAverageGradientMagnitude= a;
      this->Modified();
      m_GradientMagnitudeIsFixed = true;
    }
  itkGetMacro(FixedAverageGradientMagnitude, double);
  
protected:
  AnisotropicDiffusionImageFilter()
    {
      m_Iterations = 0;
      m_ConductanceParameter = 1.0;
      m_TimeStep = 0.125f;
      m_FixedAverageGradientMagnitude = 0.0;
      m_GradientMagnitudeIsFixed = false;
    }
  ~AnisotropicDiffusionImageFilter() {}
  void PrintSelf(std::ostream& os, Indent indent) const
    {
      Superclass::PrintSelf(os, indent.GetNextIndent());
      os << indent << "TimeStep: " << m_TimeStep << std::endl;
      os << indent << "ConductanceParameter: "
         << m_ConductanceParameter << std::endl;
      os << indent << "ConductanceScalingParameter: "
         << m_ConductanceScalingParameter << std::endl;
      os << indent << "Iterations: " << m_Iterations
         << std::endl;
      os << indent << "ConductanceScalingUpdateInterval: "
         << m_ConductanceScalingUpdateInterval << std::endl;
      os << indent << "FixedAverageGradientMagnitude: "
         << m_FixedAverageGradientMagnitude << std::endl;
    }
  
  virtual bool Halt()
    {
      if (this->GetElapsedIterations() == m_Iterations) return true;
      else return false;
    }

  virtual void InitializeIteration()
    {
      AnisotropicDiffusionFunction<UpdateBufferType> *f = 
        dynamic_cast<AnisotropicDiffusionFunction<UpdateBufferType> *>
        (this->GetDifferenceFunction().GetPointer());
      if (! f)
        {  throw ExceptionObject(__FILE__, __LINE__);    }
      
      f->SetConductanceParameter(m_ConductanceParameter);
      f->SetTimeStep(m_TimeStep);

      if ( m_TimeStep >  1.0 / pow(2.0, static_cast<double>(ImageDimension))  )
        {
          f->SetTimeStep(1.0 / pow(2.0, static_cast<double>(ImageDimension))); 
          itkWarningMacro(<< "Anisotropic diffusion has attempted to use a time step which will introduce instability into the solution.  The time step has been automatically reduced to " << f->GetTimeStep() << ", which is the maximum value for which the solution is theoretically stable.");
        }
      
      if (m_GradientMagnitudeIsFixed == false)
        {
          f->CalculateAverageGradientMagnitudeSquared(this->GetOutput());
        }
      else
        {
          f->SetAverageGradientMagnitudeSquared(m_FixedAverageGradientMagnitude 
                                                *
                                                m_FixedAverageGradientMagnitude);
        }
      f->InitializeIteration();

      if (m_Iterations != 0)
          this->UpdateProgress(((float)(this->GetElapsedIterations()))
                               /((float)(m_Iterations)));
      else this->UpdateProgress(0);
    }

  bool m_GradientMagnitudeIsFixed;
  
private:
  AnisotropicDiffusionImageFilter(const Self&); //purposely not implemented
  void operator=(const Self&); //purposely not implemented
  
  double           m_ConductanceParameter;
  double           m_ConductanceScalingParameter;
  unsigned int     m_Iterations;
  unsigned int     m_ConductanceScalingUpdateInterval;
  double           m_FixedAverageGradientMagnitude;

  TimeStepType     m_TimeStep;
  
};

} // end namspace itk

#endif

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