ITK  4.4.0
Insight Segmentation and Registration Toolkit
Public Types | Public Member Functions | Static Public Member Functions | Protected Member Functions | Private Types | Private Member Functions | Private Attributes | List of all members
itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction > Class Template Reference

#include <itkImageKmeansModelEstimator.h>

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

Detailed Description

template<class TInputImage, class 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. 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 genrates 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 A. Gersho and R. M. Gray, {Vector Quantization and Signal Compression}, Kluwer Academic Publishers, Boston, MA, 1992.

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
Wiki Examples:

Definition at line 131 of file itkImageKmeansModelEstimator.h.

Public Types

typedef vnl_matrix< double > CodebookMatrixOfDoubleType
 
typedef vnl_matrix< int > CodebookMatrixOfIntegerType
 
typedef SmartPointer< const SelfConstPointer
 
typedef
ImageRegionConstIterator
< TInputImage > 
InputImageConstIterator
 
typedef TInputImage::ConstPointer InputImageConstPointer
 
typedef ImageRegionIterator
< TInputImage > 
InputImageIterator
 
typedef TInputImage::PixelType InputImagePixelType
 
typedef TInputImage::Pointer InputImagePointer
 
typedef TInputImage InputImageType
 
typedef
TInputImage::PixelType::VectorType 
InputImageVectorType
 
typedef
TMembershipFunction::Pointer 
MembershipFunctionPointer
 
typedef SmartPointer< SelfPointer
 
typedef ImageKmeansModelEstimator Self
 
typedef
ImageModelEstimatorBase
< TInputImage,
TMembershipFunction > 
Superclass
 
- Public Types inherited from itk::ImageModelEstimatorBase< TInputImage, TMembershipFunction >
typedef SmartPointer< const SelfConstPointer
 
typedef TInputImage::Pointer InputImagePointer
 
typedef TInputImage InputImageType
 
typedef
TMembershipFunction::Pointer 
MembershipFunctionPointer
 
typedef std::vector
< MembershipFunctionPointer
MembershipFunctionPointerVector
 
typedef SmartPointer< SelfPointer
 
typedef ImageModelEstimatorBase Self
 
typedef LightProcessObject Superclass
 
- Public Types inherited from itk::LightProcessObject
typedef SmartPointer< const SelfConstPointer
 
typedef SmartPointer< SelfPointer
 
typedef LightProcessObject Self
 
typedef Object Superclass
 
- Public Types inherited from itk::Object
typedef SmartPointer< const SelfConstPointer
 
typedef SmartPointer< SelfPointer
 
typedef Object Self
 
typedef LightObject Superclass
 
- Public Types inherited from itk::LightObject
typedef SmartPointer< const SelfConstPointer
 
typedef SmartPointer< SelfPointer
 
typedef LightObject Self
 

Public Member Functions

virtual ::itk::LightObject::Pointer CreateAnother (void) const
 
virtual CodebookMatrixOfDoubleType GetCodebook () const
 
CodebookMatrixOfDoubleType GetKmeansResults (void)
 
virtual int GetMaxSplitAttempts () const
 
virtual const char * GetNameOfClass () const
 
virtual double GetOffsetAdd () const
 
virtual double GetOffsetMultiply () const
 
CodebookMatrixOfDoubleType GetOutCodebook ()
 
virtual double GetThreshold () const
 
void SetCodebook (CodebookMatrixOfDoubleType InCodebook)
 
virtual void SetMaxSplitAttempts (int _arg)
 
virtual void SetOffsetAdd (double _arg)
 
virtual void SetOffsetMultiply (double _arg)
 
virtual void SetThreshold (double _arg)
 
- Public Member Functions inherited from itk::ImageModelEstimatorBase< TInputImage, TMembershipFunction >
unsigned int AddMembershipFunction (MembershipFunctionPointer function)
 
void DeleteAllMembershipFunctions ()
 
const
MembershipFunctionPointerVector 
GetMembershipFunctions () const
 
unsigned int GetNumberOfMembershipFunctions ()
 
virtual const unsigned int & GetNumberOfModels ()
 
void SetMembershipFunctions (MembershipFunctionPointerVector membershipFunctions)
 
virtual void SetNumberOfModels (unsigned int _arg)
 
void Update ()
 
virtual void SetInputImage (InputImageType *_arg)
 
virtual InputImageTypeGetModifiableInputImage ()
 
virtual const InputImageTypeGetInputImage () const
 
- Public Member Functions inherited from itk::LightProcessObject
virtual void AbortGenerateDataOff ()
 
virtual void AbortGenerateDataOn ()
 
virtual const bool & GetAbortGenerateData ()
 
virtual void SetAbortGenerateData (bool _arg)
 
virtual void UpdateOutputData ()
 
void UpdateProgress (float amount)
 
virtual void SetProgress (float _arg)
 
virtual const float & GetProgress ()
 
- Public Member Functions inherited from itk::Object
unsigned long AddObserver (const EventObject &event, Command *)
 
unsigned long AddObserver (const EventObject &event, Command *) const
 
virtual void DebugOff () const
 
virtual void DebugOn () const
 
CommandGetCommand (unsigned long tag)
 
bool GetDebug () const
 
MetaDataDictionaryGetMetaDataDictionary (void)
 
const MetaDataDictionaryGetMetaDataDictionary (void) const
 
virtual ModifiedTimeType GetMTime () const
 
virtual const TimeStampGetTimeStamp () const
 
bool HasObserver (const EventObject &event) const
 
void InvokeEvent (const EventObject &)
 
void InvokeEvent (const EventObject &) const
 
virtual void Modified () const
 
virtual void Register () const
 
void RemoveAllObservers ()
 
void RemoveObserver (unsigned long tag)
 
void SetDebug (bool debugFlag) const
 
void SetMetaDataDictionary (const MetaDataDictionary &rhs)
 
virtual void SetReferenceCount (int)
 
virtual void UnRegister () const
 
- Public Member Functions inherited from itk::LightObject
virtual void Delete ()
 
virtual int GetReferenceCount () const
 
 itkCloneMacro (Self)
 
void Print (std::ostream &os, Indent indent=0) const
 

Static Public Member Functions

static Pointer New ()
 

Protected Member Functions

void Allocate ()
 
void GenerateData ()
 
 ImageKmeansModelEstimator ()
 
void PrintKmeansAlgorithmResults ()
 
virtual void PrintSelf (std::ostream &os, Indent indent) const
 
 ~ImageKmeansModelEstimator ()
 
- Protected Member Functions inherited from itk::ImageModelEstimatorBase< TInputImage, TMembershipFunction >
 ImageModelEstimatorBase ()
 
void PrintSelf (std::ostream &os, Indent indent) const
 
 ~ImageModelEstimatorBase ()
 
- Protected Member Functions inherited from itk::LightProcessObject
 LightProcessObject ()
 
 ~LightProcessObject ()
 
- 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
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

typedef TInputImage::SizeType ImageSizeType
 
typedef
TInputImage::PixelType::VectorType 
InputPixelVectorType
 

Private Member Functions

void EstimateKmeansModelParameters ()
 
virtual void EstimateModels ()
 
 ImageKmeansModelEstimator (const Self &)
 
void NearestNeighborSearchBasic (double *distortion)
 
void operator= (const Self &)
 
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 Types inherited from itk::LightObject
typedef int InternalReferenceCountType
 
- Protected Attributes inherited from itk::LightObject
InternalReferenceCountType m_ReferenceCount
 
SimpleFastMutexLock m_ReferenceCountLock
 

Member Typedef Documentation

template<class TInputImage , class TMembershipFunction >
typedef vnl_matrix< double > itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >::CodebookMatrixOfDoubleType

Type definition for a double matrix.

Definition at line 170 of file itkImageKmeansModelEstimator.h.

template<class TInputImage , class TMembershipFunction >
typedef vnl_matrix< int > itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >::CodebookMatrixOfIntegerType

Type definition for an integer vector.

Definition at line 173 of file itkImageKmeansModelEstimator.h.

template<class TInputImage , class TMembershipFunction >
typedef SmartPointer< const Self > itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >::ConstPointer

Definition at line 141 of file itkImageKmeansModelEstimator.h.

template<class TInputImage , class TMembershipFunction >
typedef TInputImage::SizeType itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >::ImageSizeType
private

Definition at line 239 of file itkImageKmeansModelEstimator.h.

template<class TInputImage , class TMembershipFunction >
typedef ImageRegionConstIterator< TInputImage > itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >::InputImageConstIterator

Definition at line 164 of file itkImageKmeansModelEstimator.h.

template<class TInputImage , class TMembershipFunction >
typedef TInputImage::ConstPointer itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >::InputImageConstPointer

Definition at line 152 of file itkImageKmeansModelEstimator.h.

template<class TInputImage , class TMembershipFunction >
typedef ImageRegionIterator< TInputImage > itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >::InputImageIterator

Type definition for the input image iterator type.

Definition at line 162 of file itkImageKmeansModelEstimator.h.

template<class TInputImage , class TMembershipFunction >
typedef TInputImage::PixelType itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >::InputImagePixelType

Type definition for the input image pixel type.

Definition at line 159 of file itkImageKmeansModelEstimator.h.

template<class TInputImage , class TMembershipFunction >
typedef TInputImage::Pointer itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >::InputImagePointer

Definition at line 151 of file itkImageKmeansModelEstimator.h.

template<class TInputImage , class TMembershipFunction >
typedef TInputImage itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >::InputImageType

Type definition for the input image.

Definition at line 147 of file itkImageKmeansModelEstimator.h.

template<class TInputImage , class TMembershipFunction >
typedef TInputImage::PixelType::VectorType itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >::InputImageVectorType

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

Definition at line 156 of file itkImageKmeansModelEstimator.h.

template<class TInputImage , class TMembershipFunction >
typedef TInputImage::PixelType::VectorType itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >::InputPixelVectorType
private

Set up the vector to store the image data.

Definition at line 242 of file itkImageKmeansModelEstimator.h.

template<class TInputImage , class TMembershipFunction >
typedef TMembershipFunction::Pointer itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >::MembershipFunctionPointer

Type definitions for the membership function .

Definition at line 167 of file itkImageKmeansModelEstimator.h.

template<class TInputImage , class TMembershipFunction >
typedef SmartPointer< Self > itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >::Pointer

Definition at line 140 of file itkImageKmeansModelEstimator.h.

template<class TInputImage , class TMembershipFunction >
typedef ImageKmeansModelEstimator itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >::Self

Standard class typedefs.

Definition at line 136 of file itkImageKmeansModelEstimator.h.

template<class TInputImage , class TMembershipFunction >
typedef ImageModelEstimatorBase< TInputImage, TMembershipFunction > itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >::Superclass

Definition at line 138 of file itkImageKmeansModelEstimator.h.

Constructor & Destructor Documentation

template<class TInputImage , class TMembershipFunction >
itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >::ImageKmeansModelEstimator ( )
protected
template<class TInputImage , class TMembershipFunction >
itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >::~ImageKmeansModelEstimator ( )
protected
template<class TInputImage , class TMembershipFunction >
itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >::ImageKmeansModelEstimator ( const Self )
private

Member Function Documentation

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

Allocate memory for the output model.

template<class TInputImage , class TMembershipFunction >
virtual::itk::LightObject::Pointer itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >::CreateAnother ( void  ) 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::LightProcessObject.

template<class TInputImage , class TMembershipFunction >
void itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >::EstimateKmeansModelParameters ( )
private
template<class TInputImage , class TMembershipFunction >
virtual void itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >::EstimateModels ( )
privatevirtual

A function that 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.

Implements itk::ImageModelEstimatorBase< TInputImage, TMembershipFunction >.

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

Starts the image modelling process

Reimplemented from itk::ImageModelEstimatorBase< TInputImage, TMembershipFunction >.

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

Get the cluster centers.

template<class TInputImage , class TMembershipFunction >
CodebookMatrixOfDoubleType itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >::GetKmeansResults ( void  )
inline

Return the codebook/cluster centers.

Definition at line 209 of file itkImageKmeansModelEstimator.h.

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

Get the manimum number of attempts to split a codeword.

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

Run-time type information (and related methods).

Reimplemented from itk::ImageModelEstimatorBase< TInputImage, TMembershipFunction >.

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

Get the offset add parameter.

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

Get the offset multiplication parameter.

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

Get the optimized codebook or the centroids of the clusters.

Definition at line 182 of file itkImageKmeansModelEstimator.h.

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

Get the threshold parameter.

template<class TInputImage , class TMembershipFunction >
void itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >::NearestNeighborSearchBasic ( double *  distortion)
private
template<class TInputImage , class TMembershipFunction >
static Pointer itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >::New ( )
static

Method for creation through the object factory.

template<class TInputImage , class TMembershipFunction >
void itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >::operator= ( const Self )
private
template<class TInputImage , class TMembershipFunction >
void itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >::Perturb ( double *  oldCodeword,
int  scale,
double *  newCodeword 
)
private
template<class TInputImage , class TMembershipFunction >
void itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >::PrintKmeansAlgorithmResults ( )
protected

Print out the results on the screen for visual feedback.

template<class TInputImage , class TMembershipFunction >
virtual void itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >::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::LightProcessObject.

template<class TInputImage , class TMembershipFunction >
void itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >::Reallocate ( int  oldSize,
int  newSize 
)
private
template<class TInputImage , class TMembershipFunction >
void itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >::SetCodebook ( CodebookMatrixOfDoubleType  InCodebook)

Set the cluster centers.

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

Set the maximum number of attempts to split a codeword.

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

Set the offset add parameter.

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

Set the offset multiplication parameter.

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

Set the threshold parameter.

template<class TInputImage , class TMembershipFunction >
void itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >::SplitCodewords ( int  currentSize,
int  numDesired,
int  scale 
)
private
template<class TInputImage , class TMembershipFunction >
int itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >::WithCodebookUseGLA ( )
private
template<class TInputImage , class TMembershipFunction >
int itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >::WithoutCodebookUseLBG ( )
private

Member Data Documentation

template<class TInputImage , class TMembershipFunction >
CodebookMatrixOfDoubleType itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >::m_Centroid
private

Definition at line 264 of file itkImageKmeansModelEstimator.h.

template<class TInputImage , class TMembershipFunction >
CodebookMatrixOfDoubleType itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >::m_Codebook
private

Definition at line 261 of file itkImageKmeansModelEstimator.h.

template<class TInputImage , class TMembershipFunction >
CodebookMatrixOfDoubleType itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >::m_CodewordDistortion
private

Definition at line 282 of file itkImageKmeansModelEstimator.h.

template<class TInputImage , class TMembershipFunction >
CodebookMatrixOfIntegerType itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >::m_CodewordHistogram
private

Definition at line 281 of file itkImageKmeansModelEstimator.h.

template<class TInputImage , class TMembershipFunction >
SizeValueType itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >::m_CurrentNumberOfCodewords
private

Definition at line 279 of file itkImageKmeansModelEstimator.h.

template<class TInputImage , class TMembershipFunction >
double itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >::m_DoubleMaximum
private

Definition at line 273 of file itkImageKmeansModelEstimator.h.

template<class TInputImage , class TMembershipFunction >
int itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >::m_MaxSplitAttempts
private

Definition at line 269 of file itkImageKmeansModelEstimator.h.

template<class TInputImage , class TMembershipFunction >
SizeValueType itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >::m_NumberOfCodewords
private

Definition at line 278 of file itkImageKmeansModelEstimator.h.

template<class TInputImage , class TMembershipFunction >
double itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >::m_OffsetAdd
private

Definition at line 267 of file itkImageKmeansModelEstimator.h.

template<class TInputImage , class TMembershipFunction >
double itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >::m_OffsetMultiply
private

Definition at line 268 of file itkImageKmeansModelEstimator.h.

template<class TInputImage , class TMembershipFunction >
double itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >::m_OutputDistortion
private

Definition at line 274 of file itkImageKmeansModelEstimator.h.

template<class TInputImage , class TMembershipFunction >
int itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >::m_OutputNumberOfEmptyCells
private

Definition at line 275 of file itkImageKmeansModelEstimator.h.

template<class TInputImage , class TMembershipFunction >
double itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >::m_Threshold
private

Definition at line 266 of file itkImageKmeansModelEstimator.h.

template<class TInputImage , class TMembershipFunction >
bool itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >::m_ValidInCodebook
private

Definition at line 272 of file itkImageKmeansModelEstimator.h.

template<class TInputImage , class TMembershipFunction >
SizeValueType itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >::m_VectorDimension
private

Definition at line 277 of file itkImageKmeansModelEstimator.h.


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