Coupled Markov random field models with phases as line field and region field

Kazuyuki Tanaka, Daiki Furusato, Tsuyoshi Horiguchi

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

We investigate a boundary-based and a region-based coupled Markov random field model, both of which are useful in image restorations of gray-level images. In the conventional boundary-based and the conventional region-based coupled Markov random field models, both a line field and a region field take only two discrete states, 0 and 1. In the boundary-based coupled random field model, existence and nonexistence of the edge at each nearest-neighbor pair of pixels are denoted by 1 and 0, respectively. In the region-based coupled random field model, some different regions at each pixel are labeled by discrete numbers. We propose a boundary-based coupled Markov random field model with continuous line field and a region-based coupled Markov random field model with continuous segmentation field from a standpoint of a plane rotator model in statistical mechanics. The iterative algorithms for image restoration are constructed by using a mean-field approximation. We investigate how the proposed models produce a better quality of restored images.

Original languageEnglish
Pages (from-to)24-33
Number of pages10
JournalSystems and Computers in Japan
Volume34
Issue number7
DOIs
Publication statusPublished - 2003 Jun 30

Keywords

  • Bayesian statistics
  • Cluster variation method
  • Image restoration
  • Marginal likelihood
  • Markov random fields
  • Mean field theory
  • Statistical techniques

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Information Systems
  • Hardware and Architecture
  • Computational Theory and Mathematics

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