ITK  5.2.0
Insight Toolkit
Public Types | Public Member Functions | Static Public Member Functions | Protected Member Functions | Private Types | Private Member Functions | Private Attributes | List of all members

#include <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 ()
 
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 >
virtual const unsigned int & GetNumberOfModels () const
 
virtual void SetNumberOfModels (unsigned int _arg)
 
virtual void SetInputImage (InputImageType *_arg)
 
virtual InputImageTypeGetModifiableInputImage ()
 
virtual const InputImageTypeGetInputImage () const
 
void SetMembershipFunctions (MembershipFunctionPointerVector membershipFunctions)
 
const MembershipFunctionPointerVector GetMembershipFunctions () const
 
unsigned int GetNumberOfMembershipFunctions ()
 
void DeleteAllMembershipFunctions ()
 
unsigned int AddMembershipFunction (MembershipFunctionPointer function)
 
void Update ()
 
- Public Member Functions inherited from itk::LightProcessObject
virtual void AbortGenerateDataOff ()
 
virtual void AbortGenerateDataOn ()
 
virtual const bool & GetAbortGenerateData () const
 
virtual void SetAbortGenerateData (bool _arg)
 
virtual void SetProgress (float _arg)
 
virtual const float & GetProgress () const
 
void UpdateProgress (float amount)
 
virtual void UpdateOutputData ()
 
- Public Member Functions inherited from itk::Object
unsigned long AddObserver (const EventObject &event, Command *)
 
unsigned long AddObserver (const EventObject &event, Command *) const
 
unsigned long AddObserver (const EventObject &event, std::function< void(const EventObject &)> function) const
 
virtual void DebugOff () const
 
virtual void DebugOn () const
 
CommandGetCommand (unsigned long tag)
 
bool GetDebug () const
 
MetaDataDictionaryGetMetaDataDictionary ()
 
const MetaDataDictionaryGetMetaDataDictionary () 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
 
void Register () const override
 
void RemoveAllObservers ()
 
void RemoveObserver (unsigned long tag)
 
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
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 ()
 
- 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 flag)
 
- 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 >
 ImageModelEstimatorBase ()
 
 ~ImageModelEstimatorBase () override=default
 
void PrintSelf (std::ostream &os, Indent indent) const override
 
void GenerateData () override
 
- Protected Member Functions inherited from itk::LightProcessObject
 LightProcessObject ()
 
 ~LightProcessObject () override
 
- Protected Member Functions inherited from itk::Object
 Object ()
 
 ~Object () override
 
bool PrintObservers (std::ostream &os, Indent indent) const
 
virtual void SetTimeStamp (const TimeStamp &time)
 
- 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
 

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. 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
ITK Sphinx Examples:
Examples
SphinxExamples/src/Segmentation/Classifiers/KMeansClusterOfPixelsInImage/Code.cxx.

Definition at line 131 of file itkImageKmeansModelEstimator.h.

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 171 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 174 of file itkImageKmeansModelEstimator.h.

◆ ConstPointer

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

Definition at line 142 of file itkImageKmeansModelEstimator.h.

◆ ImageSizeType

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

Definition at line 252 of file itkImageKmeansModelEstimator.h.

◆ InputImageConstIterator

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

Definition at line 165 of file itkImageKmeansModelEstimator.h.

◆ InputImageConstPointer

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

Definition at line 153 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 163 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 160 of file itkImageKmeansModelEstimator.h.

◆ InputImagePointer

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

Definition at line 152 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 151 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 157 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 255 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 168 of file itkImageKmeansModelEstimator.h.

◆ Pointer

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

Definition at line 141 of file itkImageKmeansModelEstimator.h.

◆ Self

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

Standard class type aliases.

Definition at line 138 of file itkImageKmeansModelEstimator.h.

◆ Superclass

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

Definition at line 139 of file itkImageKmeansModelEstimator.h.

Constructor & Destructor Documentation

◆ ImageKmeansModelEstimator()

template<typename TInputImage , typename TMembershipFunction >
itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >::ImageKmeansModelEstimator ( )
protected

◆ ~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::LightProcessObject.

◆ EstimateKmeansModelParameters()

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

◆ EstimateModels()

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

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 >.

◆ GenerateData()

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

Starts the image modelling 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 216 of file itkImageKmeansModelEstimator.h.

◆ GetMaxSplitAttempts()

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

Get the maximum number of attempts to split a codeword.

◆ GetNameOfClass()

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

Run-time type information (and related methods).

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

◆ GetOffsetAdd()

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

Get the offset add parameter.

◆ GetOffsetMultiply()

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

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 185 of file itkImageKmeansModelEstimator.h.

◆ GetThreshold()

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

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

These support the progress method and aborting filter execution.

Reimplemented from itk::LightProcessObject.

◆ Reallocate()

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

◆ 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 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 the offset add parameter.

◆ SetOffsetMultiply()

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

Set the offset multiplication parameter.

◆ SetThreshold()

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

Set 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 279 of file itkImageKmeansModelEstimator.h.

◆ m_Codebook

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

Definition at line 276 of file itkImageKmeansModelEstimator.h.

◆ m_CodewordDistortion

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

Definition at line 296 of file itkImageKmeansModelEstimator.h.

◆ m_CodewordHistogram

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

Definition at line 295 of file itkImageKmeansModelEstimator.h.

◆ m_CurrentNumberOfCodewords

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

Definition at line 293 of file itkImageKmeansModelEstimator.h.

◆ m_DoubleMaximum

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

Definition at line 287 of file itkImageKmeansModelEstimator.h.

◆ m_MaxSplitAttempts

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

Definition at line 284 of file itkImageKmeansModelEstimator.h.

◆ m_NumberOfCodewords

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

Definition at line 292 of file itkImageKmeansModelEstimator.h.

◆ m_OffsetAdd

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

Definition at line 282 of file itkImageKmeansModelEstimator.h.

◆ m_OffsetMultiply

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

Definition at line 283 of file itkImageKmeansModelEstimator.h.

◆ m_OutputDistortion

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

Definition at line 288 of file itkImageKmeansModelEstimator.h.

◆ m_OutputNumberOfEmptyCells

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

Definition at line 289 of file itkImageKmeansModelEstimator.h.

◆ m_Threshold

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

Definition at line 281 of file itkImageKmeansModelEstimator.h.

◆ m_ValidInCodebook

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

Definition at line 286 of file itkImageKmeansModelEstimator.h.

◆ m_VectorDimension

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

Definition at line 291 of file itkImageKmeansModelEstimator.h.


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