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Proceedings Paper

Iterative Bayesian method for segmenting images that have undergone a gray-level degradation
Author(s): Kurt R. Smith; Michael I. Miller
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Paper Abstract

We extend the MRF image model commonly employed in the Bayesian development of image segmentation procedures to include a degradation channel resulting in a 2D hidden Markov model as the basis for the segmentation problem. We solve the segmentation problem by deriving the expectation-maximization algorithm for the case where the 'hidden' Markov source is the 2-D MRF that generates a true scene and the degradation channel is an additive, memoryless, grey-level degradation process that produces the observed scene.

Paper Details

Date Published: 30 April 1992
PDF: 9 pages
Proc. SPIE 1611, Sensor Fusion IV: Control Paradigms and Data Structures, (30 April 1992); doi: 10.1117/12.57964
Show Author Affiliations
Kurt R. Smith, Southern Illinois Univ. (United States)
Michael I. Miller, Washington Univ. (United States)


Published in SPIE Proceedings Vol. 1611:
Sensor Fusion IV: Control Paradigms and Data Structures
Paul S. Schenker, Editor(s)

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