Unsupervised classification of radar images using hidden Markov chains and hidden Markov random fields

2003 ◽  
Vol 41 (3) ◽  
pp. 675-686 ◽  
Author(s):  
R. Fjortoft ◽  
Y. Delignon ◽  
W. Pieczynski ◽  
M. Sigelle ◽  
F. Tupin
Keyword(s):  
Markov Chains ◽  
Random Fields ◽  
Markov Random Fields ◽  
Hidden Markov ◽  
Unsupervised Classification ◽  
Hidden Markov Chains ◽  
Radar Images ◽  
Markov Random

Markov Chains in Many Dimensions

1994 ◽  
Vol 26 (3) ◽  
pp. 756-774 ◽  
Author(s):  
Dimitris N. Politis
Keyword(s):  
Markov Chain ◽  
Markov Chains ◽  
Maximum Entropy ◽  
Stationary Distribution ◽  
Random Fields ◽  
Special Class ◽  
Markov Random Fields ◽  
One Dimension ◽  
Stationary Markov Chain ◽  
Markov Random

A generalization of the notion of a stationary Markov chain in more than one dimension is proposed, and is found to be a special class of homogeneous Markov random fields. Stationary Markov chains in many dimensions are shown to possess a maximum entropy property, analogous to the corresponding property for Markov chains in one dimension. In addition, a representation of Markov chains in many dimensions is provided, together with a method for their generation that converges to their stationary distribution.

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