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Bayesian image processing of data from constrained source distributions-II. valued, uncorrelated and correlated constraints

  • City University of New York
  • Albert Einstein College of Medicine

Research output: Contribution to journalArticlepeer-review

13 Scopus citations

Abstract

Bayesian image processing formalisms which incorporate a priori information about valued-uncorrelated and valued-correlated (patterned) source distributions are introduced and the corresponding iterative algorithms are derived using the EM technique. Striking improvement in image processing is demonstrated when applying these algorithms to Poisson and Gaussian randomized data in one-dimensional cases.

Original languageEnglish
Pages (from-to)75-91
Number of pages17
JournalBulletin of Mathematical Biology
Volume49
Issue number1
DOIs
StatePublished - Jan 1987

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