Refinement of EM (expectation maximization) restored images

Shyh-shiaw Kuo; Richard J. Mammone

doi:10.1117/12.45383

1 June 1991 Refinement of EM (expectation maximization) restored images

Shyh-shiaw Kuo, Richard J. Mammone

Proceedings Volume 1452, Image Processing Algorithms and Techniques II; (1991) https://doi.org/10.1117/12.45383
Event: Electronic Imaging '91, 1991, San Jose, CA, United States

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.

Citation Download Citation

Shyh-shiaw Kuo and Richard J. Mammone "Refinement of EM (expectation maximization) restored images", Proc. SPIE 1452, Image Processing Algorithms and Techniques II, (1 June 1991); https://doi.org/10.1117/12.45383

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