Denoise an image using min/max curvature flow. More...

#include <sitkMinMaxCurvatureFlowImageFilter.h>

Inheritance diagram for itk::simple::MinMaxCurvatureFlowImageFilter:

Collaboration diagram for itk::simple::MinMaxCurvatureFlowImageFilter:

Public Types
typedef RealPixelIDTypeList	PixelIDTypeList

typedef MinMaxCurvatureFlowImageFilter	Self

Public Types inherited from itk::simple::ImageFilter< 1 >
typedef ImageFilter	Self

Public Types inherited from itk::simple::ProcessObject
typedef ProcessObject	Self

Public Member Functions
Image	Execute (const Image &image1)

Image	Execute (const Image &image1, double timeStep, uint32_t numberOfIterations, int stencilRadius)

std::string	GetName () const

uint32_t	GetNumberOfIterations () const

int	GetStencilRadius () const

double	GetTimeStep () const

	MinMaxCurvatureFlowImageFilter ()

Self &	SetNumberOfIterations (uint32_t NumberOfIterations)

Self &	SetStencilRadius (int StencilRadius)

Self &	SetTimeStep (double TimeStep)

std::string	ToString () const

	~MinMaxCurvatureFlowImageFilter ()

Public Member Functions inherited from itk::simple::ImageFilter< 1 >
	ImageFilter ()

virtual	~ImageFilter ()=0

Public Member Functions inherited from itk::simple::ProcessObject
virtual void	Abort ()

virtual int	AddCommand (itk::simple::EventEnum event, itk::simple::Command &cmd)
	Add a Command Object to observer the event. More...

virtual float	GetProgress () const
	An Active Measurement of the progress of execution. More...

virtual bool	HasCommand (itk::simple::EventEnum event) const
	Query of this object has any registered commands for event. More...

	ProcessObject ()

virtual void	RemoveAllCommands ()
	Remove all registered commands. More...

virtual	~ProcessObject ()

virtual void	DebugOn ()

virtual void	DebugOff ()

virtual bool	GetDebug () const

virtual void	SetDebug (bool debugFlag)

virtual void	SetNumberOfThreads (unsigned int n)

virtual unsigned int	GetNumberOfThreads () const

Private Types
typedef Image(Self::*	MemberFunctionType) (const Image &image1)

Private Member Functions
template<class TImageType >
Image	ExecuteInternal (const Image &image1)

Private Attributes
nsstd::auto_ptr< detail::MemberFunctionFactory< MemberFunctionType > >	m_MemberFactory

uint32_t	m_NumberOfIterations

int	m_StencilRadius

double	m_TimeStep

Friends
struct	detail::MemberFunctionAddressor< MemberFunctionType >

Additional Inherited Members
Static Public Member Functions inherited from itk::simple::ProcessObject
static bool	GetGlobalDefaultDebug ()

static void	GlobalDefaultDebugOff ()

static void	GlobalDefaultDebugOn ()

static void	SetGlobalDefaultDebug (bool debugFlag)

static void	GlobalWarningDisplayOn ()

static void	GlobalWarningDisplayOff ()

static void	SetGlobalWarningDisplay (bool flag)

static bool	GetGlobalWarningDisplay ()

static void	SetGlobalDefaultNumberOfThreads (unsigned int n)

static unsigned int	GetGlobalDefaultNumberOfThreads ()

static double	GetGlobalDefaultCoordinateTolerance ()
	Access the global tolerance to determine congruent spaces. More...

static void	SetGlobalDefaultCoordinateTolerance (double)
	Access the global tolerance to determine congruent spaces. More...

static double	GetGlobalDefaultDirectionTolerance ()
	Access the global tolerance to determine congruent spaces. More...

static void	SetGlobalDefaultDirectionTolerance (double)
	Access the global tolerance to determine congruent spaces. More...

Protected Member Functions inherited from itk::simple::ProcessObject
virtual unsigned long	AddITKObserver (const itk::EventObject &, itk::Command *)

virtual itk::ProcessObject *	GetActiveProcess ()

virtual void	OnActiveProcessDelete ()

virtual void	onCommandDelete (const itk::simple::Command *cmd) throw ()

virtual void	PreUpdate (itk::ProcessObject *p)

virtual void	RemoveITKObserver (EventCommand &e)

Protected Member Functions inherited from itk::simple::NonCopyable
	NonCopyable ()

Static Protected Member Functions inherited from itk::simple::ImageFilter< 1 >
static void	FixNonZeroIndex (TImageType *img)

Static Protected Member Functions inherited from itk::simple::ProcessObject
template<class TImageType >
static TImageType::ConstPointer	CastImageToITK (const Image &img)

template<class TImageType >
static Image	CastITKToImage (TImageType *img)

template<class TPixelType , unsigned int VImageDimension, unsigned int VLength, template< typename, unsigned int > class TVector>
static Image	CastITKToImage (itk::Image< TVector< TPixelType, VLength >, VImageDimension > *img)

static const itk::EventObject &	GetITKEventObject (EventEnum e)

template<typename T >
static std::ostream &	ToStringHelper (std::ostream &os, const T &v)

static std::ostream &	ToStringHelper (std::ostream &os, const char &v)

static std::ostream &	ToStringHelper (std::ostream &os, const signed char &v)

static std::ostream &	ToStringHelper (std::ostream &os, const unsigned char &v)

Detailed Description

Denoise an image using min/max curvature flow.

MinMaxCurvatureFlowImageFilter implements a curvature driven image denoising algorithm. Iso-brightness contours in the grayscale input image are viewed as a level set. The level set is then evolved using a curvature-based speed function:

$I_t = F_{\mbox{minmax}} |\nabla I|$

where $F_{\mbox{minmax}} = \max(\kappa,0)$ if $\mbox{Avg}_{\mbox{stencil}}(x)$ is less than or equal to $T_{thresold}$ and $\min(\kappa,0)$ , otherwise. $\kappa$ is the mean curvature of the iso-brightness contour at point $ x $ .

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 $ R $ around each point. The choice of $ R $ , the stencil radius, governs the scale of the noise to be removed.

The threshold value $T_{threshold}$ is the average intensity obtained in the direction perpendicular to the gradient at point $ x $ at the extrema of the local neighborhood.

This filter make use of the multi-threaded finite difference solver hierarchy. Updates are computed using a MinMaxCurvatureFlowFunction 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, however for dimensions greater than 3D, an expensive brute-force search is used to compute the local threshold.

Reference: "Level Set Methods and Fast Marching Methods", J.A. Sethian, Cambridge Press, Chapter 16, Second edition, 1999.