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Proceedings Paper

Refinement of EM (expectation maximization) restored images
Author(s): Shyh-shiaw Kuo; Richard J. Mammone
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Paper Abstract

A new iterative algorithm for restoring noisy blurred images with unknown point spread function (PSF) is presented. The method initially estimates the PSF and the original image with the Expectation Maximization (EM) algorithm. The resulting image estimate is then refined by using the adaptive Row Action Projection (RAP) algorithm which is based on the theory of Projection Onto Convex Sets (POCS). The new implementation of the RAP can be performed efficiently in parallel and facilitates locally adaptive constraints and cycling strategies. Computer simulations illustrate the new method to be very competitive in restoring degrading images from noisy blurred images with unknown PSF.

Paper Details

Date Published: 1 June 1991
PDF: 11 pages
Proc. SPIE 1452, Image Processing Algorithms and Techniques II, (1 June 1991); doi: 10.1117/12.45383
Show Author Affiliations
Shyh-shiaw Kuo, Rutgers Univ. (United States)
Richard J. Mammone, Rutgers Univ. (United States)

Published in SPIE Proceedings Vol. 1452:
Image Processing Algorithms and Techniques II
Mehmet Reha Civanlar; Sanjit K. Mitra; Robert J. Moorhead, Editor(s)

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