IMAGE SEGMENTATION ALGORITHM BASED ON RELAXATION WITH VARYING NEIGHBORHOOD STRUCTURES.

Haluk Derin, Chee Sun Won, Jinyu Kuang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

A segmentation algorithm based on deterministic relaxation with varying neighborhood structures is presented. The image is modeled as a discrete-valued Markov random field (MRF), or equivalently a Gibbs random field, corrupted by additive, independent, Gaussian noise. The algorithm seeks to determine the maximum a posteriori (MAP) estimate of noiseless scene. A comparison of this segmentation algorithm with other relaxation algorithms and a single-sweep dynamic programming algorithm, all seeking the MAP estimate, is also presented.

Original languageEnglish
Title of host publicationConference Record - Asilomar Conference on Circuits, Systems & Computers
PublisherIEEE
Pages439-443
Number of pages5
ISBN (Print)0818608161
StatePublished - 1987

Publication series

NameConference Record - Asilomar Conference on Circuits, Systems & Computers
ISSN (Print)0736-5861

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