ITK
6.0.0
Insight Toolkit
|
#include <itkImageKmeansModelEstimator.h>
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 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.
Definition at line 131 of file itkImageKmeansModelEstimator.h.
Public Member Functions | |
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 () |
Public Member Functions inherited from itk::LightProcessObject | |
virtual void | AbortGenerateDataOn () |
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 Pointer | CreateAnother () const |
virtual void | Delete () |
virtual const char * | GetNameOfClass () const |
virtual int | GetReferenceCount () const |
void | Print (std::ostream &os, Indent indent=0) const |
virtual void | Register () const |
virtual void | SetReferenceCount (int) |
virtual void | UnRegister () const noexcept |
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 | |
virtual void | GenerateData () |
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 | PrintSelf (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 {} |
using itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >::CodebookMatrixOfDoubleType = vnl_matrix<double> |
Type definition for a double matrix.
Definition at line 171 of file itkImageKmeansModelEstimator.h.
using itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >::CodebookMatrixOfIntegerType = vnl_matrix<int> |
Type definition for an integer vector.
Definition at line 174 of file itkImageKmeansModelEstimator.h.
using itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >::ConstPointer = SmartPointer<const Self> |
Definition at line 142 of file itkImageKmeansModelEstimator.h.
|
private |
Definition at line 251 of file itkImageKmeansModelEstimator.h.
using itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >::InputImageConstIterator = ImageRegionConstIterator<TInputImage> |
Definition at line 165 of file itkImageKmeansModelEstimator.h.
using itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >::InputImageConstPointer = typename TInputImage::ConstPointer |
Definition at line 153 of file itkImageKmeansModelEstimator.h.
using itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >::InputImageIterator = ImageRegionIterator<TInputImage> |
Type definition for the input image iterator type.
Definition at line 163 of file itkImageKmeansModelEstimator.h.
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.
using itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >::InputImagePointer = typename TInputImage::Pointer |
Definition at line 152 of file itkImageKmeansModelEstimator.h.
using itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >::InputImageType = TInputImage |
Type definition for the input image.
Definition at line 151 of file itkImageKmeansModelEstimator.h.
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.
|
private |
Set up the vector to store the image data.
Definition at line 254 of file itkImageKmeansModelEstimator.h.
using itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >::MembershipFunctionPointer = typename TMembershipFunction::Pointer |
Type definitions for the membership function .
Definition at line 168 of file itkImageKmeansModelEstimator.h.
using itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >::Pointer = SmartPointer<Self> |
Definition at line 141 of file itkImageKmeansModelEstimator.h.
using itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >::Self = ImageKmeansModelEstimator |
Standard class type aliases.
Definition at line 138 of file itkImageKmeansModelEstimator.h.
using itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >::Superclass = ImageModelEstimatorBase<TInputImage, TMembershipFunction> |
Definition at line 139 of file itkImageKmeansModelEstimator.h.
|
protected |
|
overrideprotecteddefault |
|
protected |
Allocate memory for the output model.
|
private |
Estimate K-means models for the core function.
|
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 >.
|
overrideprotectedvirtual |
Starts the image modeling process
Reimplemented from itk::LightProcessObject.
|
virtual |
Get the cluster centers.
|
inline |
Return the codebook/cluster centers.
Definition at line 212 of file itkImageKmeansModelEstimator.h.
|
virtual |
Set/Get the maximum number of attempts to split a codeword.
|
overridevirtual |
Reimplemented from itk::LightProcessObject.
|
virtual |
Set/Get the offset add parameter.
|
virtual |
Set/Get the offset multiplication parameter.
|
inline |
Get the optimized codebook or the centroids of the clusters.
Definition at line 185 of file itkImageKmeansModelEstimator.h.
|
virtual |
Set/Get the threshold parameter.
|
private |
|
static |
Method for creation through the object factory.
|
private |
|
protected |
Print out the results on the screen for visual feedback.
|
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::LightProcessObject.
|
private |
Reallocate various memories and then make a copy of the old data.
void itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >::SetCodebook | ( | CodebookMatrixOfDoubleType | inCodebook | ) |
Set the cluster centers.
|
virtual |
Set/Get the maximum number of attempts to split a codeword.
|
virtual |
Set/Get the offset add parameter.
|
virtual |
Set/Get the offset multiplication parameter.
|
virtual |
Set/Get the threshold parameter.
|
private |
|
private |
|
private |
|
private |
Definition at line 278 of file itkImageKmeansModelEstimator.h.
|
private |
Definition at line 275 of file itkImageKmeansModelEstimator.h.
|
private |
Definition at line 295 of file itkImageKmeansModelEstimator.h.
|
private |
Definition at line 294 of file itkImageKmeansModelEstimator.h.
|
private |
Definition at line 292 of file itkImageKmeansModelEstimator.h.
|
private |
Definition at line 286 of file itkImageKmeansModelEstimator.h.
|
private |
Definition at line 283 of file itkImageKmeansModelEstimator.h.
|
private |
Definition at line 291 of file itkImageKmeansModelEstimator.h.
|
private |
Definition at line 281 of file itkImageKmeansModelEstimator.h.
|
private |
Definition at line 282 of file itkImageKmeansModelEstimator.h.
|
private |
Definition at line 287 of file itkImageKmeansModelEstimator.h.
|
private |
Definition at line 288 of file itkImageKmeansModelEstimator.h.
|
private |
Definition at line 280 of file itkImageKmeansModelEstimator.h.
|
private |
Definition at line 285 of file itkImageKmeansModelEstimator.h.
|
private |
Definition at line 290 of file itkImageKmeansModelEstimator.h.