Accession Number:

ADA238611

Title:

Stochastic Simulation Techniques for Partition Function Approximation of Gibbs Random Field Images

Descriptive Note:

Technical rept. 1 Jan 90-30 Jun 91,

Corporate Author:

JOHNS HOPKINS UNIV BALTIMORE MD DEPT OF ELECTRICAL AND COMPUTER ENGINEERING

Report Date:

1991-06-01

Pagination or Media Count:

70.0

Abstract:

A Monte Carlo simulation technique for the calculation of the partition function of a general Gibbs random field is presented. We show that the partition function of a general Gibbs random field is equivalent to an expectation. This observation allows us to develop an importance sampling approach for estimating this expectation by using Monte-Carlo simulations. Two different methods are proposed for this task. We show that the resulting estimators are unbiased and consistent. Computations are performed iteratively, by using a simple, Metropolis-like, Monte-Carlo algorithm with remarkable success, as it is demonstrated by our simulations. Our work concentrates on binary, second-order Gibbs random fields defined on a rectangular lattice.

Subject Categories:

  • Statistics and Probability

Distribution Statement:

APPROVED FOR PUBLIC RELEASE