#include <itkImageKmeansModelEstimator.h>

Detailed Description

template<typename TInputImage, typename TMembershipFunction>
class itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >

Base class for ImageKmeansModelEstimator object.

itkImageKmeansModelEstimator generates the kmeans model (cluster centers). This object performs clustering of data sets into different clusters, either using user-provided seed points as an initial guess or generating the clusters using a recursive approach when the user provides the number of desired clusters. Each cluster is represented by its cluster center. The two algorithms used are the Generalized Lloyd algorithm (GLA) and the Linde-Buzo-Gray algorithm (LBG). The cluster centers are also referred to as codewords and a table of cluster centers is referred as a codebook.

As required by the GLA algorithm, the initial seed cluster should contain approximate centers of clusters. The GLA algorithm generates updated cluster centers that result in a lower distortion than the input seed cluster when the input vectors are mapped/classified/labelled using the given codebooks.

If no codebook is provided, the Linde-Buzo-Gray algorithm is used. This algorithm uses the GLA algorithm at its core to generate the centroids of the input vectors (data). However, since there is no initial codebook, LBG first creates a one word codebook (or centroid of one cluster comprising of all the input training vectors). The LBG uses codeword or centroid splitting to create an increasing number of clusters. Each new set of clusters are optimized using the GLA algorithm. The number of clusters increases as $2^{n}$ n= 0, 1, ... The codebook is expected to be in the form of a vnl matrix, where there are N rows, each row representing the cluster mean of a given cluster. The number of columns in the codebook should be equal to the input image vector dimension.

The threshold parameter controls the ''optimality'' of the returned codebook, where optimality is related to the least possible mean-squared error distortion that can be found by the algorithm. For larger thresholds, the result will be less optimal. For smaller thresholds, the result will be more optimal. If a more optimal result is desired, then the algorithm will take longer to complete. A reasonable threshold value is 0.01.

If, during the operation of the algorithm, there are any unused clusters or cells, the m_OffsetAdd and m_OffsetMultiply parameters are used to split the cells with the highest distortion. This function will attempt to fill empty cells up to 10 times (unless the overall distortion is zero). Using 0.01 is a reasonable default values for the m_OffsetAdd and m_OffsetMultiply parameters.

If the GLA is unable to resolve the data into the desired number of clusters or cells, only the codewords which were used will be returned.

In terms of clustering, codewords are cluster centers, and a codebook is a table containing all cluster centers. The GLA produces results that are equivalent to the K-means clustering algorithm.

For more information about the algorithms, see [41].

This object supports data handling of multiband images. The object accepts the input image in vector format only, where each pixel is a vector and each element of the vector corresponds to an entry from 1 particular band of a multiband dataset. A single band image is treated as a vector image with a single element for every vector.

This function is templated over the type of input image. In addition, a second parameter for the MembershipFunction needs to be specified. In this case a Membership function that store cluster centroids models needs to be specified.

The Update() function enables the calculation of the various models, creates the membership function objects and populates them.

Note: There is a second implementation of k-means algorithm in ITK under the itk::Statistics namespace. While this algorithm (GLA/LBG based algorithm) is memory efficient, the other algorithm is time efficient.

See also: KdTreeBasedKmeansEstimator, WeightedCentroidKdTreeGenerator, KdTree; ScalarImageKmeansImageFilter

ITK Sphinx Examples:

All ITK Sphinx Examples

K Means Cluster Of Pixels In Image

Definition at line 129 of file itkImageKmeansModelEstimator.h.

Inheritance diagram for itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >:

Collaboration diagram for itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >:

Public Types
using	CodebookMatrixOfDoubleType = vnl_matrix<double>

using	CodebookMatrixOfIntegerType = vnl_matrix<int>

using	ConstPointer = SmartPointer<const Self>

using	InputImageConstIterator = ImageRegionConstIterator<TInputImage>

using	InputImageConstPointer = typename TInputImage::ConstPointer

using	InputImageIterator = ImageRegionIterator<TInputImage>

using	InputImagePixelType = typename TInputImage::PixelType

using	InputImagePointer = typename TInputImage::Pointer

using	InputImageType = TInputImage

using	InputImageVectorType = typename TInputImage::PixelType::VectorType

using	MembershipFunctionPointer = typename TMembershipFunction::Pointer

using	Pointer = SmartPointer<Self>

using	Self = ImageKmeansModelEstimator

using	Superclass = ImageModelEstimatorBase<TInputImage, TMembershipFunction>

Public Types inherited from itk::ImageModelEstimatorBase< TInputImage, TMembershipFunction >
using	ConstPointer = SmartPointer<const Self>

using	InputImagePointer = typename TInputImage::Pointer

using	InputImageType = TInputImage

using	MembershipFunctionPointer = typename TMembershipFunction::Pointer

using	MembershipFunctionPointerVector = std::vector<MembershipFunctionPointer>

using	Pointer = SmartPointer<Self>

using	Self = ImageModelEstimatorBase

using	Superclass = LightProcessObject

Public Types inherited from itk::LightProcessObject
using	ConstPointer = SmartPointer<const Self>

using	Pointer = SmartPointer<Self>

using	Self = LightProcessObject

using	Superclass = Object

Public Types inherited from itk::Object
using	ConstPointer = SmartPointer<const Self>

using	Pointer = SmartPointer<Self>

using	Self = Object

using	Superclass = LightObject

Public Types inherited from itk::LightObject
using	ConstPointer = SmartPointer<const Self>

using	Pointer = SmartPointer<Self>

using	Self = LightObject

Public Member Functions
virtual::itk::LightObject::Pointer	CreateAnother () const

virtual CodebookMatrixOfDoubleType	GetCodebook () const

CodebookMatrixOfDoubleType	GetKmeansResults ()

const char *	GetNameOfClass () const override

CodebookMatrixOfDoubleType	GetOutCodebook ()

void	SetCodebook (CodebookMatrixOfDoubleType inCodebook)


virtual void	SetThreshold (double _arg)

virtual double	GetThreshold () const


virtual void	SetOffsetAdd (double _arg)

virtual double	GetOffsetAdd () const


virtual void	SetOffsetMultiply (double _arg)

virtual double	GetOffsetMultiply () const


virtual void	SetMaxSplitAttempts (int _arg)

virtual int	GetMaxSplitAttempts () const

Public Member Functions inherited from itk::ImageModelEstimatorBase< TInputImage, TMembershipFunction >
unsigned int	AddMembershipFunction (MembershipFunctionPointer function)

void	DeleteAllMembershipFunctions ()

const MembershipFunctionPointerVector	GetMembershipFunctions () const

const char *	GetNameOfClass () const override

unsigned int	GetNumberOfMembershipFunctions ()

virtual const unsigned int &	GetNumberOfModels () const

void	SetMembershipFunctions (MembershipFunctionPointerVector membershipFunctions)

virtual void	SetNumberOfModels (unsigned int _arg)

void	Update ()

virtual void	SetInputImage (InputImageType *_arg)

virtual InputImageType *	GetModifiableInputImage ()

virtual const InputImageType *	GetInputImage () const

Public Member Functions inherited from itk::LightProcessObject
virtual void	AbortGenerateDataOff ()

virtual void	AbortGenerateDataOn ()

virtual::itk::LightObject::Pointer	CreateAnother () const

virtual const bool &	GetAbortGenerateData () const

const char *	GetNameOfClass () const override

virtual void	SetAbortGenerateData (bool _arg)

virtual void	UpdateOutputData ()

void	UpdateProgress (float amount)

virtual void	SetProgress (float _arg)

virtual const float &	GetProgress () const

Public Member Functions inherited from itk::Object
unsigned long	AddObserver (const EventObject &event, Command *cmd) const

unsigned long	AddObserver (const EventObject &event, std::function< void(const EventObject &)> function) const

LightObject::Pointer	CreateAnother () const override

virtual void	DebugOff () const

virtual void	DebugOn () const

Command *	GetCommand (unsigned long tag)

bool	GetDebug () const

MetaDataDictionary &	GetMetaDataDictionary ()

const MetaDataDictionary &	GetMetaDataDictionary () const

virtual ModifiedTimeType	GetMTime () const

const char *	GetNameOfClass () const override

virtual const TimeStamp &	GetTimeStamp () const

bool	HasObserver (const EventObject &event) const

void	InvokeEvent (const EventObject &)

void	InvokeEvent (const EventObject &) const

virtual void	Modified () const

void	Register () const override

void	RemoveAllObservers ()

void	RemoveObserver (unsigned long tag) const

void	SetDebug (bool debugFlag) const

void	SetReferenceCount (int) override

void	UnRegister () const noexcept override

void	SetMetaDataDictionary (const MetaDataDictionary &rhs)

void	SetMetaDataDictionary (MetaDataDictionary &&rrhs)

virtual void	SetObjectName (std::string _arg)

virtual const std::string &	GetObjectName () const

Public Member Functions inherited from itk::LightObject
Pointer	Clone () const

virtual void	Delete ()

virtual int	GetReferenceCount () const

void	Print (std::ostream &os, Indent indent=0) const

Static Public Member Functions
static Pointer	New ()

Static Public Member Functions inherited from itk::LightProcessObject
static Pointer	New ()

Static Public Member Functions inherited from itk::Object
static bool	GetGlobalWarningDisplay ()

static void	GlobalWarningDisplayOff ()

static void	GlobalWarningDisplayOn ()

static Pointer	New ()

static void	SetGlobalWarningDisplay (bool val)

Static Public Member Functions inherited from itk::LightObject
static void	BreakOnError ()

static Pointer	New ()

Protected Member Functions
void	Allocate ()

void	GenerateData () override

	ImageKmeansModelEstimator ()

void	PrintKmeansAlgorithmResults ()

void	PrintSelf (std::ostream &os, Indent indent) const override

	~ImageKmeansModelEstimator () override=default

Protected Member Functions inherited from itk::ImageModelEstimatorBase< TInputImage, TMembershipFunction >
void	GenerateData () override

	ImageModelEstimatorBase ()

void	PrintSelf (std::ostream &os, Indent indent) const override

	~ImageModelEstimatorBase () override=default

Protected Member Functions inherited from itk::LightProcessObject
	LightProcessObject ()

void	PrintSelf (std::ostream &os, Indent indent) const override

	~LightProcessObject () override

Protected Member Functions inherited from itk::Object
	Object ()

bool	PrintObservers (std::ostream &os, Indent indent) const

void	PrintSelf (std::ostream &os, Indent indent) const override

virtual void	SetTimeStamp (const TimeStamp &timeStamp)

	~Object () override

Protected Member Functions inherited from itk::LightObject
virtual LightObject::Pointer	InternalClone () const

	LightObject ()

virtual void	PrintHeader (std::ostream &os, Indent indent) const

virtual void	PrintTrailer (std::ostream &os, Indent indent) const

virtual	~LightObject ()

Private Types
using	ImageSizeType = typename TInputImage::SizeType

using	InputPixelVectorType = typename TInputImage::PixelType::VectorType

Private Member Functions
void	EstimateKmeansModelParameters ()

void	EstimateModels () override

void	NearestNeighborSearchBasic (double *distortion)

void	Perturb (double oldCodeword, int scale, double newCodeword)

void	Reallocate (int oldSize, int newSize)

void	SplitCodewords (int currentSize, int numDesired, int scale)

int	WithCodebookUseGLA ()

int	WithoutCodebookUseLBG ()

Private Attributes
CodebookMatrixOfDoubleType	m_Centroid {}

CodebookMatrixOfDoubleType	m_Codebook {}

CodebookMatrixOfDoubleType	m_CodewordDistortion {}

CodebookMatrixOfIntegerType	m_CodewordHistogram {}

SizeValueType	m_CurrentNumberOfCodewords {}

double	m_DoubleMaximum {}

int	m_MaxSplitAttempts {}

SizeValueType	m_NumberOfCodewords {}

double	m_OffsetAdd {}

double	m_OffsetMultiply {}

double	m_OutputDistortion {}

int	m_OutputNumberOfEmptyCells {}

double	m_Threshold {}

bool	m_ValidInCodebook {}

SizeValueType	m_VectorDimension {}

Additional Inherited Members
Protected Attributes inherited from itk::LightObject
std::atomic< int >	m_ReferenceCount {}

Member Typedef Documentation

◆ CodebookMatrixOfDoubleType

template<typename TInputImage, typename TMembershipFunction>

using itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >::CodebookMatrixOfDoubleType = vnl_matrix<double>

Type definition for a double matrix.

Definition at line 169 of file itkImageKmeansModelEstimator.h.

◆ CodebookMatrixOfIntegerType

template<typename TInputImage, typename TMembershipFunction>

using itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >::CodebookMatrixOfIntegerType = vnl_matrix<int>

Type definition for an integer vector.

Definition at line 172 of file itkImageKmeansModelEstimator.h.

◆ ConstPointer

template<typename TInputImage, typename TMembershipFunction>

using itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >::ConstPointer = SmartPointer<const Self>

Definition at line 140 of file itkImageKmeansModelEstimator.h.

◆ ImageSizeType

template<typename TInputImage, typename TMembershipFunction>

using itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >::ImageSizeType = typename TInputImage::SizeType

private

Definition at line 249 of file itkImageKmeansModelEstimator.h.

◆ InputImageConstIterator

template<typename TInputImage, typename TMembershipFunction>

using itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >::InputImageConstIterator = ImageRegionConstIterator<TInputImage>

Definition at line 163 of file itkImageKmeansModelEstimator.h.

◆ InputImageConstPointer

template<typename TInputImage, typename TMembershipFunction>

using itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >::InputImageConstPointer = typename TInputImage::ConstPointer

Definition at line 151 of file itkImageKmeansModelEstimator.h.

◆ InputImageIterator

template<typename TInputImage, typename TMembershipFunction>

using itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >::InputImageIterator = ImageRegionIterator<TInputImage>

Type definition for the input image iterator type.

Definition at line 161 of file itkImageKmeansModelEstimator.h.

◆ InputImagePixelType

template<typename TInputImage, typename TMembershipFunction>

using itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >::InputImagePixelType = typename TInputImage::PixelType

Type definition for the input image pixel type.

Definition at line 158 of file itkImageKmeansModelEstimator.h.

◆ InputImagePointer

template<typename TInputImage, typename TMembershipFunction>

using itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >::InputImagePointer = typename TInputImage::Pointer

Definition at line 150 of file itkImageKmeansModelEstimator.h.

◆ InputImageType

template<typename TInputImage, typename TMembershipFunction>

using itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >::InputImageType = TInputImage

Type definition for the input image.

Definition at line 149 of file itkImageKmeansModelEstimator.h.

◆ InputImageVectorType

template<typename TInputImage, typename TMembershipFunction>

using itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >::InputImageVectorType = typename TInputImage::PixelType::VectorType

Type definition for the vector associated with input image pixel type.

Definition at line 155 of file itkImageKmeansModelEstimator.h.

◆ InputPixelVectorType

template<typename TInputImage, typename TMembershipFunction>

using itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >::InputPixelVectorType = typename TInputImage::PixelType::VectorType

private

Set up the vector to store the image data.

Definition at line 252 of file itkImageKmeansModelEstimator.h.

◆ MembershipFunctionPointer

template<typename TInputImage, typename TMembershipFunction>

using itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >::MembershipFunctionPointer = typename TMembershipFunction::Pointer

Type definitions for the membership function .

Definition at line 166 of file itkImageKmeansModelEstimator.h.

◆ Pointer

template<typename TInputImage, typename TMembershipFunction>

using itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >::Pointer = SmartPointer<Self>

Definition at line 139 of file itkImageKmeansModelEstimator.h.

◆ Self

template<typename TInputImage, typename TMembershipFunction>

using itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >::Self = ImageKmeansModelEstimator

Standard class type aliases.

Definition at line 136 of file itkImageKmeansModelEstimator.h.

◆ Superclass

template<typename TInputImage, typename TMembershipFunction>

using itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >::Superclass = ImageModelEstimatorBase<TInputImage, TMembershipFunction>

Definition at line 137 of file itkImageKmeansModelEstimator.h.

Constructor & Destructor Documentation

◆ ImageKmeansModelEstimator()

template<typename TInputImage, typename TMembershipFunction>

itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >::ImageKmeansModelEstimator ( )

protected

Referenced by GetNameOfClass().

◆ ~ImageKmeansModelEstimator()

template<typename TInputImage, typename TMembershipFunction>

itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >::~ImageKmeansModelEstimator ( )

overrideprotecteddefault

Member Function Documentation

◆ Allocate()

template<typename TInputImage, typename TMembershipFunction>

void itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >::Allocate ( )

protected

Allocate memory for the output model.

◆ CreateAnother()

template<typename TInputImage, typename TMembershipFunction>

virtual::itk::LightObject::Pointer itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >::CreateAnother ( ) const

virtual

Create an object from an instance, potentially deferring to a factory. This method allows you to create an instance of an object that is exactly the same type as the referring object. This is useful in cases where an object has been cast back to a base class.

Reimplemented from itk::LightObject.

◆ EstimateKmeansModelParameters()

template<typename TInputImage, typename TMembershipFunction>

void itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >::EstimateKmeansModelParameters ( )

private

Estimate K-means models for the core function.

◆ EstimateModels()

template<typename TInputImage, typename TMembershipFunction>

void itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >::EstimateModels ( )

overrideprivatevirtual

Generates the cluster centers (model) corresponding to the estimates of the cluster centers (in the initial codebook). If no codebook is provided, then use the number of classes to determine the cluster centers or the Kmeans model. This is the the base function to call the K-means classifier. Takes the set of training images and internally computes the means and variance of the various classes defined in the training set.

Implements itk::ImageModelEstimatorBase< TInputImage, TMembershipFunction >.

◆ GenerateData()

template<typename TInputImage, typename TMembershipFunction>

void itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >::GenerateData ( )

overrideprotectedvirtual

Starts the image modeling process

Reimplemented from itk::LightProcessObject.

◆ GetCodebook()

template<typename TInputImage, typename TMembershipFunction>

virtual CodebookMatrixOfDoubleType itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >::GetCodebook ( ) const

virtual

Get the cluster centers.

◆ GetKmeansResults()

template<typename TInputImage, typename TMembershipFunction>

CodebookMatrixOfDoubleType itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >::GetKmeansResults ( )

inline

Return the codebook/cluster centers.

Definition at line 210 of file itkImageKmeansModelEstimator.h.

References m_Centroid.

◆ GetMaxSplitAttempts()

template<typename TInputImage, typename TMembershipFunction>

virtual int itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >::GetMaxSplitAttempts ( ) const

virtual

Set/Get the maximum number of attempts to split a codeword.

◆ GetNameOfClass()

template<typename TInputImage, typename TMembershipFunction>

const char * itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >::GetNameOfClass ( ) const

overridevirtual

See also: LightObject::GetNameOfClass()

Reimplemented from itk::LightObject.

References ImageKmeansModelEstimator().

◆ GetOffsetAdd()

template<typename TInputImage, typename TMembershipFunction>

virtual double itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >::GetOffsetAdd ( ) const

virtual

Set/Get the offset add parameter.

◆ GetOffsetMultiply()

template<typename TInputImage, typename TMembershipFunction>

virtual double itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >::GetOffsetMultiply ( ) const

virtual

Set/Get the offset multiplication parameter.

◆ GetOutCodebook()

template<typename TInputImage, typename TMembershipFunction>

CodebookMatrixOfDoubleType itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >::GetOutCodebook ( )

inline

Get the optimized codebook or the centroids of the clusters.

Definition at line 183 of file itkImageKmeansModelEstimator.h.

References m_Codebook.

◆ GetThreshold()

template<typename TInputImage, typename TMembershipFunction>

virtual double itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >::GetThreshold ( ) const

virtual

Set/Get the threshold parameter.

◆ NearestNeighborSearchBasic()

template<typename TInputImage, typename TMembershipFunction>

void itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >::NearestNeighborSearchBasic ( double * distortion )

private

◆ New()

template<typename TInputImage, typename TMembershipFunction>

static Pointer itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >::New ( )

static

Method for creation through the object factory.

◆ Perturb()

template<typename TInputImage, typename TMembershipFunction>

void itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >::Perturb	(	double *	oldCodeword,
		int	scale,
		double *	newCodeword )

private

◆ PrintKmeansAlgorithmResults()

template<typename TInputImage, typename TMembershipFunction>

void itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >::PrintKmeansAlgorithmResults ( )

protected

Print out the results on the screen for visual feedback.

◆ PrintSelf()

template<typename TInputImage, typename TMembershipFunction>

void itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >::PrintSelf	(	std::ostream &	os,
		Indent	indent ) const

overrideprotectedvirtual

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::LightObject.

◆ Reallocate()

template<typename TInputImage, typename TMembershipFunction>

void itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >::Reallocate	(	int	oldSize,
		int	newSize )

private

Reallocate various memories and then make a copy of the old data.

◆ SetCodebook()

template<typename TInputImage, typename TMembershipFunction>

void itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >::SetCodebook ( CodebookMatrixOfDoubleType inCodebook )

Set the cluster centers.

◆ SetMaxSplitAttempts()

template<typename TInputImage, typename TMembershipFunction>

virtual void itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >::SetMaxSplitAttempts ( int _arg )

virtual

Set/Get the maximum number of attempts to split a codeword.

◆ SetOffsetAdd()

template<typename TInputImage, typename TMembershipFunction>

virtual void itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >::SetOffsetAdd ( double _arg )

virtual

Set/Get the offset add parameter.

◆ SetOffsetMultiply()

template<typename TInputImage, typename TMembershipFunction>

virtual void itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >::SetOffsetMultiply ( double _arg )

virtual

Set/Get the offset multiplication parameter.

◆ SetThreshold()

template<typename TInputImage, typename TMembershipFunction>

virtual void itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >::SetThreshold ( double _arg )

virtual

Set/Get the threshold parameter.

◆ SplitCodewords()

template<typename TInputImage, typename TMembershipFunction>

void itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >::SplitCodewords	(	int	currentSize,
		int	numDesired,
		int	scale )

private

◆ WithCodebookUseGLA()

template<typename TInputImage, typename TMembershipFunction>

int itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >::WithCodebookUseGLA ( )

private

◆ WithoutCodebookUseLBG()

template<typename TInputImage, typename TMembershipFunction>

int itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >::WithoutCodebookUseLBG ( )

private

Member Data Documentation

◆ m_Centroid

template<typename TInputImage, typename TMembershipFunction>

CodebookMatrixOfDoubleType itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >::m_Centroid {}

private

Definition at line 276 of file itkImageKmeansModelEstimator.h.

Referenced by GetKmeansResults().

◆ m_Codebook

template<typename TInputImage, typename TMembershipFunction>

CodebookMatrixOfDoubleType itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >::m_Codebook {}

private

Definition at line 273 of file itkImageKmeansModelEstimator.h.

Referenced by GetOutCodebook().

◆ m_CodewordDistortion

template<typename TInputImage, typename TMembershipFunction>

CodebookMatrixOfDoubleType itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >::m_CodewordDistortion {}

private

Definition at line 293 of file itkImageKmeansModelEstimator.h.

◆ m_CodewordHistogram

template<typename TInputImage, typename TMembershipFunction>

CodebookMatrixOfIntegerType itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >::m_CodewordHistogram {}

private

Definition at line 292 of file itkImageKmeansModelEstimator.h.

◆ m_CurrentNumberOfCodewords

template<typename TInputImage, typename TMembershipFunction>

SizeValueType itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >::m_CurrentNumberOfCodewords {}

private

Definition at line 290 of file itkImageKmeansModelEstimator.h.

◆ m_DoubleMaximum

template<typename TInputImage, typename TMembershipFunction>

double itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >::m_DoubleMaximum {}

private

Definition at line 284 of file itkImageKmeansModelEstimator.h.

◆ m_MaxSplitAttempts

template<typename TInputImage, typename TMembershipFunction>

int itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >::m_MaxSplitAttempts {}

private

Definition at line 281 of file itkImageKmeansModelEstimator.h.

◆ m_NumberOfCodewords

template<typename TInputImage, typename TMembershipFunction>

SizeValueType itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >::m_NumberOfCodewords {}

private

Definition at line 289 of file itkImageKmeansModelEstimator.h.

◆ m_OffsetAdd

template<typename TInputImage, typename TMembershipFunction>

double itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >::m_OffsetAdd {}

private

Definition at line 279 of file itkImageKmeansModelEstimator.h.

◆ m_OffsetMultiply

template<typename TInputImage, typename TMembershipFunction>

double itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >::m_OffsetMultiply {}

private

Definition at line 280 of file itkImageKmeansModelEstimator.h.

◆ m_OutputDistortion

template<typename TInputImage, typename TMembershipFunction>

double itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >::m_OutputDistortion {}

private

Definition at line 285 of file itkImageKmeansModelEstimator.h.

◆ m_OutputNumberOfEmptyCells

template<typename TInputImage, typename TMembershipFunction>

int itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >::m_OutputNumberOfEmptyCells {}

private

Definition at line 286 of file itkImageKmeansModelEstimator.h.

◆ m_Threshold

template<typename TInputImage, typename TMembershipFunction>

double itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >::m_Threshold {}

private

Definition at line 278 of file itkImageKmeansModelEstimator.h.

◆ m_ValidInCodebook

template<typename TInputImage, typename TMembershipFunction>

bool itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >::m_ValidInCodebook {}

private

Definition at line 283 of file itkImageKmeansModelEstimator.h.

◆ m_VectorDimension

template<typename TInputImage, typename TMembershipFunction>

SizeValueType itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >::m_VectorDimension {}

private

Definition at line 288 of file itkImageKmeansModelEstimator.h.

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

itkImageKmeansModelEstimator.h

Detailed Description

Public Types

Public Member Functions

Static Public Member Functions

Protected Member Functions

Private Types

Private Member Functions

Private Attributes

Additional Inherited Members

Member Typedef Documentation

◆ CodebookMatrixOfDoubleType

◆ CodebookMatrixOfIntegerType

◆ ConstPointer

◆ ImageSizeType

◆ InputImageConstIterator

◆ InputImageConstPointer

◆ InputImageIterator

◆ InputImagePixelType

◆ InputImagePointer

◆ InputImageType

◆ InputImageVectorType

◆ InputPixelVectorType

◆ MembershipFunctionPointer

◆ Pointer

◆ Self

◆ Superclass

Constructor & Destructor Documentation

◆ ImageKmeansModelEstimator()

◆ ~ImageKmeansModelEstimator()

Member Function Documentation

◆ Allocate()

◆ CreateAnother()

◆ EstimateKmeansModelParameters()

◆ EstimateModels()

◆ GenerateData()

◆ GetCodebook()

◆ GetKmeansResults()

◆ GetMaxSplitAttempts()

◆ GetNameOfClass()

◆ GetOffsetAdd()

◆ GetOffsetMultiply()

◆ GetOutCodebook()

◆ GetThreshold()

◆ NearestNeighborSearchBasic()

◆ New()

◆ Perturb()

◆ PrintKmeansAlgorithmResults()

◆ PrintSelf()

◆ Reallocate()

◆ SetCodebook()

◆ SetMaxSplitAttempts()

◆ SetOffsetAdd()

◆ SetOffsetMultiply()

◆ SetThreshold()

◆ SplitCodewords()

◆ WithCodebookUseGLA()

◆ WithoutCodebookUseLBG()

Member Data Documentation

◆ m_Centroid

◆ m_Codebook

◆ m_CodewordDistortion

◆ m_CodewordHistogram

◆ m_CurrentNumberOfCodewords

◆ m_DoubleMaximum

◆ m_MaxSplitAttempts

◆ m_NumberOfCodewords

◆ m_OffsetAdd

◆ m_OffsetMultiply

◆ m_OutputDistortion

◆ m_OutputNumberOfEmptyCells

◆ m_Threshold

◆ m_ValidInCodebook

◆ m_VectorDimension