Title :
An approximate method of evaluating the joint likelihood for first-order GMRFs
Author :
Wu, Zhenyu ; Leahy, Richard
Author_Institution :
Dept. of Radiol., Pennsylvania Univ., Philadelphia, PA, USA
fDate :
10/1/1993 12:00:00 AM
Abstract :
A highly accurate approximation is proposed for computing the joint likelihood for first-order Gauss-Markov random fields (GMRFs) defined on irregularly shaped lattices. The problem in computing the likelihood lies in evaluating the determinant of a very large matrix B. Its exact evaluation is limited to either very small irregular regions or a few regularly shaped regions. The approximation proposed here is based on an eigenanalysis of B
Keywords :
Markov processes; eigenvalues and eigenfunctions; image processing; lattice theory and statistics; maximum likelihood estimation; parameter estimation; random processes; approximate method; determinant; eigenanalysis; first-order Gauss-Markov random fields; image modelling; irregularly shaped lattices; joint likelihood; very large matrix; Biomedical engineering; Boundary conditions; Gaussian processes; Image processing; Lattices; Mathematical model; Nearest neighbor searches; Probability density function; Shape; Zinc;
Journal_Title :
Image Processing, IEEE Transactions on
