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/*=========================================================================
Program: Insight Segmentation & Registration Toolkit
Module: $RCSfile: itkCurvatureNDAnisotropicDiffusionFunction.h,v $
Language: C++
Date: $Date: 2008-01-24 19:25:07 $
Version: $Revision: 1.18 $
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 __itkCurvatureNDAnisotropicDiffusionFunction_h_
#define __itkCurvatureNDAnisotropicDiffusionFunction_h_
#include "itkScalarAnisotropicDiffusionFunction.h"
#include "itkNeighborhoodAlgorithm.h"
#include "itkNeighborhoodInnerProduct.h"
#include "itkDerivativeOperator.h"
namespace itk {
/**
* \class CurvatureNDAnisotropicDiffusionFunction
*
* This class implements a variation on the classic, Perona-Malik anisotropic
* image diffusion equation as described in
* itkGradientNDAnisotropicDiffusionFunction. This object is a level-set
* analog of that equation and will be referred to below as the \em modified
* \em curvature \em diffusion \em equation (MCDE). MCDE does not exhibit
* the edge enhancing properties of classic anisotropic diffusion, which can under
* certain conditions undergo a ``negative'' diffusion,which enhances the
* contrast of edges. Equations of the form of MCDE always undergo positive
* diffusion, with the conductance term only varying the strength of that
* diffusion.
*
* \par
* Qualitatively, MCDE compares well with other non-linear diffusion
* techniques. It is less sensitive to contrast than classic Perona-Malik
* style diffusion, and preserves finer detailed structures in images.
* There is a potential speed trade-off for using this function in place of
* itkGradientNDAnisotropicDiffusionFunction. Each iteration of the solution
* takes roughly twice as long. Fewer iterations, however, may be required to
* reach an acceptable solution.
*
* \par
* The MCDE equation is given as:
*
* \f[ f_t = \mid \nabla f \mid \nabla \cdot c( \mid \nabla f \mid ) \frac{
* \nabla f }{ \mid \nabla f \mid } \f] ,
*
* \par
* where the conductance modified curvature term is
*
* \f[ \nabla \cdot \frac{\nabla f}{\mid \nabla f \mid} \f] .
*
* \par References
* R. Whitaker and X. Xue. Variable-Conductance, Level-Set Curvature for
* Image Denoising, International Conference on Image Processing, 2001
* pp. 142-145, Vol.3.
*
*
* \sa AnisotropicDiffusionFunction
* \ingroup FiniteDifferenceFunctions
* \ingroup ImageEnhancement
* \todo References */
template <class TImage>
class ITK_EXPORT CurvatureNDAnisotropicDiffusionFunction :
public ScalarAnisotropicDiffusionFunction<TImage>
{
public:
/** Standard class typedefs. */
typedef CurvatureNDAnisotropicDiffusionFunction Self;
typedef ScalarAnisotropicDiffusionFunction<TImage> Superclass;
typedef SmartPointer<Self> Pointer;
typedef SmartPointer<const Self> ConstPointer;
/** Method for creation through the object factory. */
itkNewMacro(Self);
/** Run-time type information (and related methods) */
itkTypeMacro( CurvatureNDAnisotropicDiffusionFunction,
ScalarAnisotropicDiffusionFunction );
/** Inherit some parameters from the superclass type. */
typedef typename Superclass::ImageType ImageType;
typedef typename Superclass::PixelType PixelType;
typedef typename Superclass::TimeStepType TimeStepType;
typedef typename Superclass::RadiusType RadiusType;
typedef typename Superclass::NeighborhoodType NeighborhoodType;
typedef typename Superclass::FloatOffsetType FloatOffsetType;
/** Inherit some parameters from the superclass type. */
itkStaticConstMacro(ImageDimension, unsigned int,Superclass::ImageDimension);
/** Compute incremental update. */
virtual PixelType ComputeUpdate(const NeighborhoodType &neighborhood,
void *globalData,
const FloatOffsetType& offset = FloatOffsetType(0.0)
);
/** This method is called prior to each iteration of the solver. */
virtual void InitializeIteration()
{
m_K = static_cast<PixelType>(this->GetAverageGradientMagnitudeSquared() *
this->GetConductanceParameter() *
this->GetConductanceParameter() * -2.0f);
}
protected:
CurvatureNDAnisotropicDiffusionFunction();
~CurvatureNDAnisotropicDiffusionFunction() {}
void PrintSelf(std::ostream& os, Indent indent) const
{
Superclass::PrintSelf(os,indent);
}
private:
CurvatureNDAnisotropicDiffusionFunction(const Self&); //purposely not implemented
void operator=(const Self&); //purposely not implemented
/** Inner product function. */
NeighborhoodInnerProduct<ImageType> m_InnerProduct;
/** Slices for the ND neighborhood. */
std::slice x_slice[ImageDimension];
std::slice xa_slice[ImageDimension][ImageDimension];
std::slice xd_slice[ImageDimension][ImageDimension];
/** Derivative operator */
DerivativeOperator<PixelType, itkGetStaticConstMacro(ImageDimension)> dx_op;
/** Modified global average gradient magnitude term. */
PixelType m_K;
/** */
static double m_MIN_NORM;
unsigned long m_Center;
unsigned long m_Stride[ImageDimension];
};
}// end namespace itk
#ifndef ITK_MANUAL_INSTANTIATION
#include "itkCurvatureNDAnisotropicDiffusionFunction.txx"
#endif
#endif
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