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/*=========================================================================
Program: Insight Segmentation & Registration Toolkit
Module: $RCSfile: itkAnisotropicDiffusionImageFilter.txx,v $
Language: C++
Date: $Date: 2006-03-19 04:36:55 $
Version: $Revision: 1.28 $
Copyright (c) Insight Software 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_txx_
#define __itkAnisotropicDiffusionImageFilter_txx_
#include "itkAnisotropicDiffusionImageFilter.h"
namespace itk
{
/**
* Constructor
*/
template <class TInputImage, class TOutputImage>
AnisotropicDiffusionImageFilter<TInputImage, TOutputImage>
::AnisotropicDiffusionImageFilter()
{
this->SetNumberOfIterations(1);
m_ConductanceParameter = 1.0;
m_ConductanceScalingParameter = 1.0;
m_ConductanceScalingUpdateInterval = 1;
m_TimeStep = 0.5 / vcl_pow(2.0, static_cast<double>(ImageDimension));
m_FixedAverageGradientMagnitude = 1.0;
m_GradientMagnitudeIsFixed = false;
}
/** Prepare for the iteration process. */
template <class TInputImage, class TOutputImage>
void
AnisotropicDiffusionImageFilter<TInputImage, TOutputImage>
::InitializeIteration()
{
AnisotropicDiffusionFunction<UpdateBufferType> *f =
dynamic_cast<AnisotropicDiffusionFunction<UpdateBufferType> *>
(this->GetDifferenceFunction().GetPointer());
if (! f)
{
throw ExceptionObject(__FILE__, __LINE__, "Anisotropic diffusion function is not set.", ITK_LOCATION);
}
f->SetConductanceParameter(m_ConductanceParameter);
f->SetTimeStep(m_TimeStep);
// Check the timestep for stability
double minSpacing;
if (this->GetUseImageSpacing())
{
minSpacing = this->GetInput()->GetSpacing()[0];
for (unsigned int i = 1; i < ImageDimension; i++)
{
if (this->GetInput()->GetSpacing()[i] < minSpacing)
{
minSpacing = this->GetInput()->GetSpacing()[i];
}
}
}
else
{
minSpacing = 1.0;
}
if ( m_TimeStep > (minSpacing / vcl_pow(2.0, static_cast<double>(ImageDimension) + 1)) )
{
// f->SetTimeStep(1.0 / vcl_pow(2.0, static_cast<double>(ImageDimension)));
itkWarningMacro(<< std::endl << "Anisotropic diffusion unstable time step: " << m_TimeStep << std::endl << "Minimum stable time step for this image is " << minSpacing / vcl_pow(2.0, static_cast<double>(ImageDimension+1)));
}
if (m_GradientMagnitudeIsFixed == false)
{
if ((this->GetElapsedIterations() % m_ConductanceScalingUpdateInterval)==0 )
{
f->CalculateAverageGradientMagnitudeSquared(this->GetOutput());
}
}
else
{
f->SetAverageGradientMagnitudeSquared(m_FixedAverageGradientMagnitude
*
m_FixedAverageGradientMagnitude);
}
f->InitializeIteration();
if (this->GetNumberOfIterations() != 0)
{
this->UpdateProgress(((float)(this->GetElapsedIterations()))
/((float)(this->GetNumberOfIterations())));
}
else
{
this->UpdateProgress(0);
}
}
template <class TInputImage, class TOutputImage>
void
AnisotropicDiffusionImageFilter<TInputImage, TOutputImage>
::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 << "ConductanceScalingUpdateInterval: "
<< m_ConductanceScalingUpdateInterval << std::endl;
os << indent << "FixedAverageGradientMagnitude: "
<< m_FixedAverageGradientMagnitude << std::endl;
}
} // end namespace itk
#endif
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