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Proceedings Paper

Simultaneous restoration and segmentation using cluster approximations to Markov random fields
Author(s): Chi-hsin Wu; Peter C. Doerschuk
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Paper Abstract

We describe a Bayesian estimator for simultaneous restoration and segmentation of images. The estimator is based on a pixel-line Markov random field and is computed by using an efficient approximation. The approximation is based on locality of interactions within the Markov random field. An example, the simultaneous restoration and segmentation of a medical tomographic image, is described.

Paper Details

Date Published: 11 August 1995
PDF: 8 pages
Proc. SPIE 2568, Neural, Morphological, and Stochastic Methods in Image and Signal Processing, (11 August 1995); doi: 10.1117/12.216349
Show Author Affiliations
Chi-hsin Wu, Industrial Technology Research Institute (Taiwan)
Peter C. Doerschuk, Purdue Univ. (United States)


Published in SPIE Proceedings Vol. 2568:
Neural, Morphological, and Stochastic Methods in Image and Signal Processing
Edward R. Dougherty; Francoise J. Preteux; Sylvia S. Shen, Editor(s)

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