Statistical characterization of clutter scenes based on a Markov random field model

T. Kasetkasem, P. K. Varshney

Research output: Contribution to journalArticle

15 Scopus citations

Abstract

The problem of clutter region identification based on Markov random field (MRF) models is addressed. Observations inside each clutter region are assumed homogenous, i.e., observations follow a single probability distribution. Our goal is to partition clutter scenes into homogenous regions and to determine this underlying probability distribution. Metropolis-Hasting and reversible jump Markov chain (RJMC) algorithms are used to search for solutions based on the maximum a posteriori (MAP) criterion. Several examples illustrate the performance of our algorithm.

Original languageEnglish (US)
Pages (from-to)1035-1050
Number of pages16
JournalIEEE Transactions on Aerospace and Electronic Systems
Volume39
Issue number3
DOIs
StatePublished - Jul 1 2003

ASJC Scopus subject areas

  • Aerospace Engineering
  • Electrical and Electronic Engineering

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