ITK  4.2.0
Insight Segmentation and Registration Toolkit
Classes
Markov Random Field-based Filters
Region-Based Segmentation Filters
+ Collaboration diagram for Markov Random Field-based Filters:

Classes

class  itk::MRFImageFilter< TInputImage, TClassifiedImage >
 Implementation of a labeller object that uses Markov Random Fields to classify pixels in an image data set. More...
class  itk::RGBGibbsPriorFilter< TInputImage, TClassifiedImage >
 The RGBGibbsPriorFilter applies Gibbs Prior model for the segmentation of MRF images. More...

Detailed Description

Markov Random Field (MRF)-based Filters assume that the segmented image is Markovian in nature, i.e., adjacent pixels are likely to be of the same class. These methods typically combine intensity-based Filters with MRF prior models also known as Gibbs prior models.