#include <itkImageModelEstimatorBase.h>
Inheritance diagram for itk::ImageModelEstimatorBase:
itkImageModelEstimatorBase is the base class for the ImageModelEstimator objects. It provides the basic function definitions that are inherent to a ImageModelEstimator objects.
This is the SuperClass for the ImageModelEstimator framework. This is an abstract class defining an interface for all such objects available through the ImageModelEstimator framework in the ITK toolkit.
The basic functionality of the ImageModelEstimator framework base class is to generate the models used in classification applications. It requires input images and a training image to be provided by the user. 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. The classified image is treated as a single band scalar image.
EstimateModels() is a pure virtual function making this an abstract class. The template parameter is the type of a membership function the ImageModelEstimator populates.
A membership function represents a specific knowledge about a class. In other words, it should tell us how "likely" is that a measurement vector (pattern) belong to the class.
As the method name indicates, you can have more than one membership function. One for each classes. The order you put the membership calculator becomes the class label for the class that is represented by the membership calculator.
Definition at line 65 of file itkImageModelEstimatorBase.h.
|
Reimplemented from itk::LightProcessObject. Reimplemented in itk::ImageGaussianModelEstimator< TInputImage, TMembershipFunction, TTrainingImage >, and itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >. Definition at line 72 of file itkImageModelEstimatorBase.h. |
|
Reimplemented in itk::ImageGaussianModelEstimator< TInputImage, TMembershipFunction, TTrainingImage >, and itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >. Definition at line 91 of file itkImageModelEstimatorBase.h. |
|
Type definitions for the training image. Reimplemented in itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >. Definition at line 90 of file itkImageModelEstimatorBase.h. |
|
Type definitions for the membership function . Reimplemented in itk::ImageGaussianModelEstimator< TInputImage, TMembershipFunction, TTrainingImage >, and itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >. Definition at line 84 of file itkImageModelEstimatorBase.h. |
|
Definition at line 87 of file itkImageModelEstimatorBase.h. |
|
Reimplemented from itk::LightProcessObject. Reimplemented in itk::ImageGaussianModelEstimator< TInputImage, TMembershipFunction, TTrainingImage >, and itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >. Definition at line 71 of file itkImageModelEstimatorBase.h. |
|
Standard class typedefs. Reimplemented from itk::LightProcessObject. Reimplemented in itk::ImageGaussianModelEstimator< TInputImage, TMembershipFunction, TTrainingImage >, and itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >. Definition at line 69 of file itkImageModelEstimatorBase.h. |
|
Reimplemented from itk::LightProcessObject. Reimplemented in itk::ImageGaussianModelEstimator< TInputImage, TMembershipFunction, TTrainingImage >, and itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >. Definition at line 70 of file itkImageModelEstimatorBase.h. |
|
|
|
|
|
Stores a MembershipCalculator of a class in its internal vector |
|
Method to reset the membership fucntion mean Definition at line 122 of file itkImageModelEstimatorBase.h. |
|
This method causes the filter to generate its output. Reimplemented from itk::LightProcessObject. Reimplemented in itk::ImageGaussianModelEstimator< TInputImage, TMembershipFunction, TTrainingImage >, and itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >. |
|
Run-time type information (and related methods). Reimplemented from itk::LightProcessObject. Reimplemented in itk::ImageGaussianModelEstimator< TInputImage, TMembershipFunction, TTrainingImage >, and itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >. |
|
Get the input image. |
|
Method to get mean Definition at line 110 of file itkImageModelEstimatorBase.h. |
|
Method to number of membership functions Definition at line 116 of file itkImageModelEstimatorBase.h. |
|
Get the number of classes. |
|
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. Reimplemented in itk::ImageGaussianModelEstimator< TInputImage, TMembershipFunction, TTrainingImage >, and itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >. |
|
Set the input image. |
|
Set the classified image. Definition at line 103 of file itkImageModelEstimatorBase.h. |
|
Set the number of classes. |
|
Define a virtual function to perform model generation from the input data |