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Proceedings Paper

Image Restoration Made Simple
Author(s): E. S. Meinel
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Paper Abstract

Many image restoration methods have been developed over the years ranging from the simple-minded inverse matrix method to the hard-to-understand maximum likelihood methods. Authors have tended to use high-falutin' language (projection onto convex sets, regularization methods, solution of the Fredholm equation of the first kind, etc.) scaring off potential users. These users fall back on the Wiener filter and its many variants because it is understandable and relatively simple to program. I will simplify the approach to image restoration by presenting a class of recursive restoration algorithms based on the classical imaging equation. These algorithms were developed by employing simple algebraic identities to manipulate the imaging equation into recursive forms. Some of the algorithms naturally satisfy the positivity constraint, making them useful for superresolution of degraded imagery. These recursive techniques are simple to understand and to implement, and give results approaching those of the most sophisticated image restoration algorithms.

Paper Details

Date Published: 13 October 1986
PDF: 6 pages
Proc. SPIE 0627, Instrumentation in Astronomy VI, (13 October 1986); doi: 10.1117/12.968151
Show Author Affiliations
E. S. Meinel, The Aerospace Corp. (United States)

Published in SPIE Proceedings Vol. 0627:
Instrumentation in Astronomy VI
David L. Crawford, Editor(s)

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