Borkar, VS and Mitter, Sanjoy K (1996) Stochastic Processes that Generate Polygonal and Related Random Fields. In: IEEE Transactions on Information Theory, 42 (2). 606 -617.
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Abstract
A reversible, ergodic, Markov process taking values in the space of polygonally segmented images is constructed. The stationary distribution of this process can be made to correspond to a Gibbs-type distribution for polygonal random fields as introduced by Arak and Surgailis (1989) and a few variants thereof, such as those arising in Bayesian analysis of random fields. Extensions to generalized polygonal random fields are presented where the segmentation boundaries are not necessarily straight line segments.
Item Type: | Journal Article |
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Publication: | IEEE Transactions on Information Theory |
Publisher: | IEEE |
Additional Information: | Copyright 1990 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. |
Keywords: | Polygonal random fields;Generalized polygonal random fields;Reversible Markov process;Interacting particle system;Monte Carlo simulation of random fields |
Department/Centre: | Division of Electrical Sciences > Electrical Engineering |
Date Deposited: | 25 Aug 2008 |
Last Modified: | 27 Feb 2019 10:26 |
URI: | http://eprints.iisc.ac.in/id/eprint/6557 |
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