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Proceedings Paper

Dynamic range compression deconvolution for enhancement of automatic target recognition system performance
Author(s): Bahareh Haji-saeed; Jed Khoury; W. D. Goodhue; Charles L. Woods; John Kierstead
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Paper Abstract

A generic nonlinear dynamic range compression deconvolver (DRCD) is proposed. We have performed the dynamic range compression deconvolution using three forms of nonlinearities: (a) digital implementation- A-law/μ-law, (b) hybrid digital-optical implementation- two-beam coupling photorefractive holography, and (c) all optical implementation- MEMS deformable mirrors. The performance of image restoration improves as the saturation nonlinearity increases. The DRCD could be used as a preprocessor for enhancing Automatic Target Recognition (ATR) system performance. In imaging through atmosphere, factors such as rain, snow, haze, pollution, etc. affect the received information from a target; therefore the need for correcting these captured images before an ATR system is required. The DRCD outperforms well-established image restoration filters such as the inverse and the Wiener filters.

Paper Details

Date Published: 17 March 2008
PDF: 10 pages
Proc. SPIE 6977, Optical Pattern Recognition XIX, 697706 (17 March 2008); doi: 10.1117/12.785891
Show Author Affiliations
Bahareh Haji-saeed, Solid State Scientific Corp. (United States)
Jed Khoury, Air Force Research Lab. (United States)
W. D. Goodhue, Univ. of Massachusetts, Lowell (United States)
Charles L. Woods, Air Force Research Lab. (United States)
John Kierstead, Solid State Scientific Corp. (United States)


Published in SPIE Proceedings Vol. 6977:
Optical Pattern Recognition XIX
David P. Casasent; Tien-Hsin Chao, Editor(s)

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