otb::EigenvalueLikelihoodMaximisation< TPrecision > Class Template Reference

#include <otbEigenvalueLikelihoodMaximisation.h>

Inheritance diagram for otb::EigenvalueLikelihoodMaximisation< TPrecision >:

Collaboration diagram for otb::EigenvalueLikelihoodMaximisation< TPrecision >:

Public Types
typedef itk::SmartPointer< const Self >	ConstPointer
typedef vnl_matrix< PrecisionType >	MatrixType
typedef itk::SmartPointer< Self >	Pointer
typedef TPrecision	PrecisionType
typedef EigenvalueLikelihoodMaximisation	Self
typedef itk::LightObject	Superclass
typedef vnl_vector< PrecisionType >	VectorType

Public Member Functions
void	Compute ()
virtual ::itk::LightObject::Pointer	CreateAnother (void) const
const VectorType &	GetLikelihood ()
virtual const char *	GetNameOfClass () const
unsigned int	GetNumberOfEndmembers ()
void	SetCorrelation (const MatrixType &m)
void	SetCovariance (const MatrixType &m)
void	SetNumberOfPixels (unsigned int n)

Static Public Member Functions
static Pointer	New ()

Protected Member Functions
	EigenvalueLikelihoodMaximisation ()
void	PrintSelf (std::ostream &os, itk::Indent indent) const override
	~EigenvalueLikelihoodMaximisation () override

Private Member Functions
	EigenvalueLikelihoodMaximisation (const Self &)=delete
void	operator= (const Self &)=delete

Private Attributes
MatrixType	m_Correlation
MatrixType	m_Covariance
VectorType	m_Likelihood
unsigned int	m_NumberOfEndmembers
unsigned int	m_NumberOfPixels

Detailed Description

template<class TPrecision>
class otb::EigenvalueLikelihoodMaximisation< TPrecision >

Estimates the number of endmembers in a hyperspectral image.

This filter applies the ELM (Eigenvalue Likelihood Maximisation) algorithm to a hyperspectral image and outputs the number of endmember. It takes as input the covariance and correlation matrices of the input data, the number of observed pixel for those matrices estimations, and outputs the number of endmembers, and the log-likelihood.

References : "Unsupervised Endmember Extraction of Martian Hyperspectral Images", B.Luo, J. Chanussot, S. Dout\'e and X. Ceamanos, IEEE Whispers 2009, Grenoble France, 2009

"Unsupervised classification of hyperspectral images by using linear unmixing algorithm", Luo, B. and Chanussot, J., IEEE Int. Conf. On Image Processing(ICIP) 2009, Cairo, Egypte, 2009

Definition at line 57 of file otbEigenvalueLikelihoodMaximisation.h.

Member Typedef Documentation

ConstPointer

template<class TPrecision >

typedef itk::SmartPointer<const Self> otb::EigenvalueLikelihoodMaximisation< TPrecision >::ConstPointer

Definition at line 64 of file otbEigenvalueLikelihoodMaximisation.h.

MatrixType

template<class TPrecision >

typedef vnl_matrix<PrecisionType> otb::EigenvalueLikelihoodMaximisation< TPrecision >::MatrixType

Definition at line 76 of file otbEigenvalueLikelihoodMaximisation.h.

Pointer

template<class TPrecision >

typedef itk::SmartPointer<Self> otb::EigenvalueLikelihoodMaximisation< TPrecision >::Pointer

Definition at line 63 of file otbEigenvalueLikelihoodMaximisation.h.

PrecisionType

template<class TPrecision >

typedef TPrecision otb::EigenvalueLikelihoodMaximisation< TPrecision >::PrecisionType

Types to use for computations.

Definition at line 70 of file otbEigenvalueLikelihoodMaximisation.h.

Self

template<class TPrecision >

typedef EigenvalueLikelihoodMaximisation otb::EigenvalueLikelihoodMaximisation< TPrecision >::Self

Standard Self typedef

Definition at line 61 of file otbEigenvalueLikelihoodMaximisation.h.

Superclass

template<class TPrecision >

typedef itk::LightObject otb::EigenvalueLikelihoodMaximisation< TPrecision >::Superclass

Definition at line 62 of file otbEigenvalueLikelihoodMaximisation.h.

VectorType

template<class TPrecision >

typedef vnl_vector<PrecisionType> otb::EigenvalueLikelihoodMaximisation< TPrecision >::VectorType

Definition at line 75 of file otbEigenvalueLikelihoodMaximisation.h.

Constructor & Destructor Documentation

EigenvalueLikelihoodMaximisation() [1/2]

template<class TPrecision >

otb::EigenvalueLikelihoodMaximisation< TPrecision >::EigenvalueLikelihoodMaximisation

protected

Definition at line 33 of file otbEigenvalueLikelihoodMaximisation.hxx.

~EigenvalueLikelihoodMaximisation()

template<class TPrecision >

otb::EigenvalueLikelihoodMaximisation< TPrecision >::~EigenvalueLikelihoodMaximisation ( )

inlineoverrideprotected

Definition at line 107 of file otbEigenvalueLikelihoodMaximisation.h.

EigenvalueLikelihoodMaximisation() [2/2]

template<class TPrecision >

otb::EigenvalueLikelihoodMaximisation< TPrecision >::EigenvalueLikelihoodMaximisation ( const Self &  )

privatedelete

Member Function Documentation

Compute()

template<class TInputImage >

void otb::EigenvalueLikelihoodMaximisation< TInputImage >::Compute

Definition at line 38 of file otbEigenvalueLikelihoodMaximisation.hxx.

CreateAnother()

template<class TPrecision >

virtual::itk::LightObject::Pointer otb::EigenvalueLikelihoodMaximisation< TPrecision >::CreateAnother

(

void

)

const

GetLikelihood()

template<class TPrecision >

const VectorType& otb::EigenvalueLikelihoodMaximisation< TPrecision >::GetLikelihood ( )

inline

Definition at line 100 of file otbEigenvalueLikelihoodMaximisation.h.

GetNameOfClass()

template<class TPrecision >

virtual const char* otb::EigenvalueLikelihoodMaximisation< TPrecision >::GetNameOfClass ( ) const

virtual

Runtime information support.

GetNumberOfEndmembers()

template<class TPrecision >

unsigned int otb::EigenvalueLikelihoodMaximisation< TPrecision >::GetNumberOfEndmembers ( )

inline

Definition at line 95 of file otbEigenvalueLikelihoodMaximisation.h.

New()

template<class TPrecision >

static Pointer otb::EigenvalueLikelihoodMaximisation< TPrecision >::New ( )

static

Method for creation through the object factory.

operator=()

template<class TPrecision >

void otb::EigenvalueLikelihoodMaximisation< TPrecision >::operator= ( const Self &  )

privatedelete

PrintSelf()

template<class TImage >

void otb::EigenvalueLikelihoodMaximisation< TImage >::PrintSelf ( std::ostream &  os, itk::Indent  indent  ) const

overrideprotected

Definition at line 93 of file otbEigenvalueLikelihoodMaximisation.hxx.

SetCorrelation()

template<class TPrecision >

void otb::EigenvalueLikelihoodMaximisation< TPrecision >::SetCorrelation ( const MatrixType &  m )

inline

Definition at line 83 of file otbEigenvalueLikelihoodMaximisation.h.

SetCovariance()

template<class TPrecision >

void otb::EigenvalueLikelihoodMaximisation< TPrecision >::SetCovariance ( const MatrixType &  m )

inline

Definition at line 78 of file otbEigenvalueLikelihoodMaximisation.h.

SetNumberOfPixels()

template<class TPrecision >

void otb::EigenvalueLikelihoodMaximisation< TPrecision >::SetNumberOfPixels ( unsigned int  n )

inline

Definition at line 88 of file otbEigenvalueLikelihoodMaximisation.h.

Member Data Documentation

m_Correlation

template<class TPrecision >

MatrixType otb::EigenvalueLikelihoodMaximisation< TPrecision >::m_Correlation

private

Definition at line 117 of file otbEigenvalueLikelihoodMaximisation.h.

m_Covariance

template<class TPrecision >

MatrixType otb::EigenvalueLikelihoodMaximisation< TPrecision >::m_Covariance

private

Definition at line 116 of file otbEigenvalueLikelihoodMaximisation.h.

m_Likelihood

template<class TPrecision >

VectorType otb::EigenvalueLikelihoodMaximisation< TPrecision >::m_Likelihood

private

Definition at line 121 of file otbEigenvalueLikelihoodMaximisation.h.

m_NumberOfEndmembers

template<class TPrecision >

unsigned int otb::EigenvalueLikelihoodMaximisation< TPrecision >::m_NumberOfEndmembers

private

Definition at line 120 of file otbEigenvalueLikelihoodMaximisation.h.

m_NumberOfPixels

template<class TPrecision >

unsigned int otb::EigenvalueLikelihoodMaximisation< TPrecision >::m_NumberOfPixels

private

Definition at line 119 of file otbEigenvalueLikelihoodMaximisation.h.

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

• otbEigenvalueLikelihoodMaximisation.h
• otbEigenvalueLikelihoodMaximisation.hxx