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Proceedings Paper

Multipurpose mean-square-error filter for processing obscured images
Author(s): Jehad Khoury; Peter D. Gianino; Charles L. Woods
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Paper Abstract

We develop a generalized minimum mean-square-error image processing filter for recognition and retrieval of noisy, blurred and obscured images. We examined the performance of this filter in four modes: (1) the well-known mean-square- error correlation filter; (2) the phase-only mean-square- error correlation filter; (3) the matched mean-square-error correlation filter, and (4) the image retrieving filter. Our simulation result show that it is possible to retrieve and recognize blurred images that are 90 percent obscured and whose signal-to-noise ratio is 0.1.

Paper Details

Date Published: 6 March 2002
PDF: 6 pages
Proc. SPIE 4734, Optical Pattern Recognition XIII, (6 March 2002); doi: 10.1117/12.458404
Show Author Affiliations
Jehad Khoury, Air Force Research Lab. (United States)
Peter D. Gianino, Air Force Research Lab. (United States)
Charles L. Woods, Air Force Research Lab. (United States)

Published in SPIE Proceedings Vol. 4734:
Optical Pattern Recognition XIII
David P. Casasent; Tien-Hsin Chao, Editor(s)

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