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Proceedings Paper

Image restoration and identification using the EM and adaptive RAP algorithms
Author(s): Shyh-shiaw Kuo; Richard J. Mammone
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Paper Abstract

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

Paper Details

Date Published: 1 November 1991
PDF: 12 pages
Proc. SPIE 1606, Visual Communications and Image Processing '91: Image Processing, (1 November 1991); doi: 10.1117/12.50312
Show Author Affiliations
Shyh-shiaw Kuo, Rutgers Univ. (United States)
Richard J. Mammone, Rutgers Univ. (United States)

Published in SPIE Proceedings Vol. 1606:
Visual Communications and Image Processing '91: Image Processing
Kou-Hu Tzou; Toshio Koga, Editor(s)

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