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/*=========================================================================
Program: Insight Segmentation & Registration Toolkit
Module: $RCSfile: itkBinaryMinMaxCurvatureFlowImageFilter.h,v $
Language: C++
Date: $Date: 2006-03-23 15:26:09 $
Version: $Revision: 1.9 $
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 __itkBinaryMinMaxCurvatureFlowImageFilter_h_
#define __itkBinaryMinMaxCurvatureFlowImageFilter_h_
#include "itkMinMaxCurvatureFlowImageFilter.h"
#include "itkBinaryMinMaxCurvatureFlowFunction.h"
namespace itk {
/** \class BinaryMinMaxCurvatureFlowImageFilter
* \brief Denoise a binary image using min/max curvature flow.
*
* BinaryMinMaxCurvatureFlowImageFilter implements a curvature driven image
* denosing algorithm. This filter assumes that the image is essentially
* binary: consisting of two classes. Iso-brightness contours in the input
* image are viewed as a level set. The level set is then evolved using
* a curvature-based speed function:
*
* \f[ I_t = F_{\mbox{minmax}} |\nabla I| \f]
*
* where \f$ F_{\mbox{minmax}} = \min(\kappa,0) \f$ if
* \f$ \mbox{Avg}_{\mbox{stencil}}(x) \f$
* is less than or equal to \f$ T_{thresold} \f$
* and \f$ \max(\kappa,0) \f$, otherwise.
* \f$ \kappa \f$ is the mean curvature of the iso-brightness contour
* at point \f$ x \f$.
*
* In min/max curvature flow, movement is turned on or off depending
* on the scale of the noise one wants to remove. Switching depends on
* the average image value of a region of radius \f$ R \f$ around each
* point. The choice of \f$ R \f$, the stencil radius, governs the scale of
* the noise to be removed.
*
* The threshold value \f$ T_{threshold} \f$ is a user specified value which
* discriminates between the two pixel classes.
*
* This filter make use of the multi-threaded finite difference solver
* hierarchy. Updates are computed using a BinaryMinMaxCurvatureFlowFunction
* object. A zero flux Neumann boundary condition is used when computing
* derivatives near the data boundary.
*
* \warning This filter assumes that the input and output types have the
* same dimensions. This filter also requires that the output image pixels
* are of a real type. This filter works for any dimensional images.
*
* Reference:
* "Level Set Methods and Fast Marching Methods", J.A. Sethian,
* Cambridge Press, Chapter 16, Second edition, 1999.
*
* \sa BinaryMinMaxCurvatureFlowFunction
* \sa CurvatureFlowImageFilter
* \sa MinMaxCurvatureFlowImageFilter
*
* \ingroup ImageEnhancement
* \ingroup Multithreaded
*
*/
template <class TInputImage, class TOutputImage>
class ITK_EXPORT BinaryMinMaxCurvatureFlowImageFilter
: public MinMaxCurvatureFlowImageFilter<TInputImage, TOutputImage>
{
public:
/** Standard class typedefs. */
typedef BinaryMinMaxCurvatureFlowImageFilter Self;
typedef MinMaxCurvatureFlowImageFilter<TInputImage, TOutputImage>
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(BinaryMinMaxCurvatureFlowImageFilter,
MinMaxCurvatureFlowImageFilter);
/** Inherit typedefs from Superclass. */
typedef typename Superclass::FiniteDifferenceFunctionType
FiniteDifferenceFunctionType;
typedef typename Superclass::OutputImageType OutputImageType;
/** BinaryMinMaxCurvatureFlowFunction type. */
typedef BinaryMinMaxCurvatureFlowFunction<OutputImageType>
BinaryMinMaxCurvatureFlowFunctionType;
/** Dimensionality of input and output data is assumed to be the same.
* It is inherited from the superclass. */
itkStaticConstMacro(ImageDimension, unsigned int,Superclass::ImageDimension);
/** Set/Get the threshold value. */
itkSetMacro( Threshold, double );
itkGetMacro( Threshold, double );
#ifdef ITK_USE_CONCEPT_CHECKING
/** Begin concept checking */
itkConceptMacro(InputConvertibleToOutputCheck,
(Concept::Convertible<typename TInputImage::PixelType,
typename TOutputImage::PixelType>));
/** End concept checking */
#endif
protected:protected:
BinaryMinMaxCurvatureFlowImageFilter();
~BinaryMinMaxCurvatureFlowImageFilter() {}
void PrintSelf(std::ostream& os, Indent indent) const;
/** Initialize the state of filter and equation before each iteration.
* Progress feeback is implemented as part of this method. */
virtual void InitializeIteration();
private:
BinaryMinMaxCurvatureFlowImageFilter(const Self&); //purposely not implemented
void operator=(const Self&); //purposely not implemented
double m_Threshold;
};
} // end namspace itk
#ifndef ITK_MANUAL_INSTANTIATION
#include "itkBinaryMinMaxCurvatureFlowImageFilter.txx"
#endif
#endif
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