Markov Random Field-based 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...

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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.