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Source continuity and boundary discontinuity considerations in Bayesian image processing
Author(s) -
Liang Z.,
Hart H.
Publication year - 1988
Publication title -
medical physics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.473
H-Index - 180
eISSN - 2473-4209
pISSN - 0094-2405
DOI - 10.1118/1.596298
Subject(s) - discontinuity (linguistics) , poisson distribution , bayesian probability , mathematics , probability density function , boundary (topology) , probability distribution , expectation–maximization algorithm , density estimation , multi source , algorithm , image processing , computer science , mathematical optimization , image (mathematics) , mathematical analysis , statistics , artificial intelligence , maximum likelihood , estimator
This paper extends the Bayesian image processing (BIP) formalism by considering the effect of simple source continuity and boundary discontinuity and a p r i o r i information in estimating an optimal source distribution from observed data. The a p r i o r i source information is formulated in terms of probability density functions of source element strengths and spatial correlations. The estimation is carried out iteratively by a BIP algorithm derived by applying the expectation maximization technique to the a p r i o r i source probability density functions and assuming the data obey Poisson statistics. The suppression of boundary oscillations and enhancement of overall image are demonstrated for computer generated ideal and Poisson randomized data.