ITK  4.2.0
Insight Segmentation and Registration Toolkit
Public Types | Public Member Functions | Protected Member Functions | Private Attributes
itk::Statistics::MahalanobisDistanceMembershipFunction< TVector > Class Template Reference

#include <itkMahalanobisDistanceMembershipFunction.h>

+ Inheritance diagram for itk::Statistics::MahalanobisDistanceMembershipFunction< TVector >:
+ Collaboration diagram for itk::Statistics::MahalanobisDistanceMembershipFunction< TVector >:

List of all members.

Public Types

typedef SmartPointer< const SelfConstPointer
typedef VariableSizeMatrix
< double > 
CovarianceMatrixType
typedef MeasurementVectorRealType MeanVectorType
typedef itk::NumericTraits
< MeasurementVectorType >
::RealType 
MeasurementVectorRealType
typedef
Superclass::MeasurementVectorSizeType 
MeasurementVectorSizeType
typedef TVector MeasurementVectorType
typedef Superclass::Pointer MembershipFunctionPointer
typedef SmartPointer< SelfPointer
typedef
MahalanobisDistanceMembershipFunction 
Self
typedef MembershipFunctionBase
< TVector > 
Superclass
- Public Types inherited from itk::Statistics::MembershipFunctionBase< TVector >
- Public Types inherited from itk::FunctionBase< TVector, double >
typedef TVector InputType
typedef double OutputType
- Public Types inherited from itk::Object
- Public Types inherited from itk::LightObject

Public Member Functions

double Evaluate (const MeasurementVectorType &measurement) const
virtual const
CovarianceMatrixType
GetCovariance ()
virtual const MeanVectorTypeGetMean ()
virtual LightObject::Pointer InternalClone () const
void SetCovariance (const CovarianceMatrixType &cov)
void SetMean (const MeanVectorType &mean)
- Public Member Functions inherited from itk::Statistics::MembershipFunctionBase< TVector >
virtual MeasurementVectorSizeType GetMeasurementVectorSize () const
virtual void SetMeasurementVectorSize (MeasurementVectorSizeType s)

Protected Member Functions

 MahalanobisDistanceMembershipFunction (void)
void PrintSelf (std::ostream &os, Indent indent) const
virtual ~MahalanobisDistanceMembershipFunction (void)
- Protected Member Functions inherited from itk::Statistics::MembershipFunctionBase< TVector >
 MembershipFunctionBase ()
virtual ~MembershipFunctionBase (void)
- Protected Member Functions inherited from itk::FunctionBase< TVector, double >
 FunctionBase ()
 ~FunctionBase ()
- Protected Member Functions inherited from itk::Object
 Object ()
bool PrintObservers (std::ostream &os, Indent indent) const
virtual void SetTimeStamp (const TimeStamp &time)
virtual ~Object ()
- Protected Member Functions inherited from itk::LightObject
 LightObject ()
virtual void PrintHeader (std::ostream &os, Indent indent) const
virtual void PrintTrailer (std::ostream &os, Indent indent) const
virtual ~LightObject ()

Private Attributes

CovarianceMatrixType m_Covariance
bool m_CovarianceNonsingular
CovarianceMatrixType m_InverseCovariance
MeanVectorType m_Mean
virtual const char * GetNameOfClass () const
virtual ::itk::LightObject::Pointer CreateAnother (void) const
static Pointer New ()

Additional Inherited Members


Detailed Description

template<class TVector>
class itk::Statistics::MahalanobisDistanceMembershipFunction< TVector >

MahalanobisDistanceMembershipFunction models class membership using Mahalanobis distance.

MahalanobisDistanceMembershipFunction is a subclass of MembershipFunctionBase that models class membership (or likelihood) using the Mahalanobis distance. The mean and covariance structure of the Mahalanobis distance are established using the methods SetMean() and SetCovariance(). The mean is a vector-type that is the same vector-type as the measurement vector but guaranteed to have a real element type. For instance, if the measurement type is an Vector<int,3>, then the mean is Vector<double,3>. If the measurement type is a VariableLengthVector<float>, then the mean is VariableLengthVector<double>. In contrast to this behavior, the covariance is always a VariableSizeMatrix<double>.

Note that this membership function does not return a probability density function in contrast to the GaussianMembershipFunction.

Note, as is the case in other packages (MATLAB, R), the value returned by this membership function is the squared distance.

If the covariance is singular or nearly singular, the membership function behaves somewhat like (the opposite of) an impulse located at the mean. In this case, we specify the covariance to be a diagonal matrix with large values along the diagonal. This membership function, therefore, will return large but differentiable values everywhere and decay to zero sharply near the mean.

Definition at line 62 of file itkMahalanobisDistanceMembershipFunction.h.


Member Typedef Documentation

template<class TVector >
typedef SmartPointer< const Self > itk::Statistics::MahalanobisDistanceMembershipFunction< TVector >::ConstPointer

Type of the covariance matrix

Definition at line 92 of file itkMahalanobisDistanceMembershipFunction.h.

Definition at line 89 of file itkMahalanobisDistanceMembershipFunction.h.

Type of the mean vector. RealType on a vector-type is the same vector-type but with a real element type.

Definition at line 88 of file itkMahalanobisDistanceMembershipFunction.h.

template<class TVector >
typedef Superclass::MeasurementVectorSizeType itk::Statistics::MahalanobisDistanceMembershipFunction< TVector >::MeasurementVectorSizeType

Typedef to represent the length of measurement vectors

Reimplemented from itk::Statistics::MembershipFunctionBase< TVector >.

Definition at line 84 of file itkMahalanobisDistanceMembershipFunction.h.

template<class TVector >
typedef TVector itk::Statistics::MahalanobisDistanceMembershipFunction< TVector >::MeasurementVectorType

Typedef alias for the measurement vectors

Reimplemented from itk::Statistics::MembershipFunctionBase< TVector >.

Definition at line 81 of file itkMahalanobisDistanceMembershipFunction.h.

SmartPointer class for superclass

Definition at line 74 of file itkMahalanobisDistanceMembershipFunction.h.

template<class TVector >
typedef SmartPointer< Self > itk::Statistics::MahalanobisDistanceMembershipFunction< TVector >::Pointer

Standard class typedefs

Reimplemented from itk::Statistics::MembershipFunctionBase< TVector >.

Definition at line 67 of file itkMahalanobisDistanceMembershipFunction.h.

template<class TVector >
typedef MembershipFunctionBase< TVector > itk::Statistics::MahalanobisDistanceMembershipFunction< TVector >::Superclass

Constructor & Destructor Documentation

template<class TVector >
itk::Statistics::MahalanobisDistanceMembershipFunction< TVector >::MahalanobisDistanceMembershipFunction ( void  )
protected
template<class TVector >
virtual itk::Statistics::MahalanobisDistanceMembershipFunction< TVector >::~MahalanobisDistanceMembershipFunction ( void  )
inlineprotectedvirtual

Definition at line 125 of file itkMahalanobisDistanceMembershipFunction.h.


Member Function Documentation

template<class TVector >
virtual::itk::LightObject::Pointer itk::Statistics::MahalanobisDistanceMembershipFunction< TVector >::CreateAnother ( void  ) const
virtual

Strandard macros

Reimplemented from itk::Object.

template<class TVector >
double itk::Statistics::MahalanobisDistanceMembershipFunction< TVector >::Evaluate ( const MeasurementVectorType measurement) const
virtual

Evaluate the Mahalanobis distance of a measurement using the prescribed mean and covariance. Note that the Mahalanobis distance is not a probability density. The square of the distance is returned.

Implements itk::Statistics::MembershipFunctionBase< TVector >.

template<class TVector >
virtual const CovarianceMatrixType& itk::Statistics::MahalanobisDistanceMembershipFunction< TVector >::GetCovariance ( )
virtual

Get the covariance matrix. Covariance matrix is a VariableSizeMatrix of doubles.

template<class TVector >
virtual const MeanVectorType& itk::Statistics::MahalanobisDistanceMembershipFunction< TVector >::GetMean ( )
virtual

Get the mean of the Mahalanobis distance. Mean is a vector type similar to the measurement type but with a real element type.

template<class TVector >
virtual const char* itk::Statistics::MahalanobisDistanceMembershipFunction< TVector >::GetNameOfClass ( ) const
virtual

Strandard macros

Reimplemented from itk::Statistics::MembershipFunctionBase< TVector >.

template<class TVector >
virtual LightObject::Pointer itk::Statistics::MahalanobisDistanceMembershipFunction< TVector >::InternalClone ( ) const
virtual

Method to clone a membership function, i.e. create a new instance of the same type of membership function and configure its ivars to match.

Reimplemented from itk::LightObject.

template<class TVector >
static Pointer itk::Statistics::MahalanobisDistanceMembershipFunction< TVector >::New ( )
static

Strandard macros

Reimplemented from itk::Object.

template<class TVector >
void itk::Statistics::MahalanobisDistanceMembershipFunction< TVector >::PrintSelf ( std::ostream &  os,
Indent  indent 
) const
protectedvirtual

Methods invoked by Print() to print information about the object including superclasses. Typically not called by the user (use Print() instead) but used in the hierarchical print process to combine the output of several classes.

Reimplemented from itk::Statistics::MembershipFunctionBase< TVector >.

template<class TVector >
void itk::Statistics::MahalanobisDistanceMembershipFunction< TVector >::SetCovariance ( const CovarianceMatrixType cov)

Set the covariance matrix. Covariance matrix is a VariableSizeMatrix of doubles. The inverse of the covariance matrix is calculated whenever the covaraince matrix is changed.

template<class TVector >
void itk::Statistics::MahalanobisDistanceMembershipFunction< TVector >::SetMean ( const MeanVectorType mean)

Set the mean used in the Mahalanobis distance. Mean is a vector type similar to the measurement type but with a real element type.


Member Data Documentation

template<class TVector >
CovarianceMatrixType itk::Statistics::MahalanobisDistanceMembershipFunction< TVector >::m_Covariance
private

Definition at line 130 of file itkMahalanobisDistanceMembershipFunction.h.

template<class TVector >
bool itk::Statistics::MahalanobisDistanceMembershipFunction< TVector >::m_CovarianceNonsingular
private

Boolean to cache whether the covarinace is singular or nearly singular

Definition at line 137 of file itkMahalanobisDistanceMembershipFunction.h.

template<class TVector >
CovarianceMatrixType itk::Statistics::MahalanobisDistanceMembershipFunction< TVector >::m_InverseCovariance
private

Definition at line 134 of file itkMahalanobisDistanceMembershipFunction.h.

template<class TVector >
MeanVectorType itk::Statistics::MahalanobisDistanceMembershipFunction< TVector >::m_Mean
private

Definition at line 129 of file itkMahalanobisDistanceMembershipFunction.h.


The documentation for this class was generated from the following file: