17 March 2008 Dynamic range compression deconvolution for enhancement of automatic target recognition system performance
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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.
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Bahareh Haji-saeed, Bahareh Haji-saeed, Jed Khoury, Jed Khoury, W. D. Goodhue, W. D. Goodhue, Charles L. Woods, Charles L. Woods, John Kierstead, John Kierstead, } "Dynamic range compression deconvolution for enhancement of automatic target recognition system performance", Proc. SPIE 6977, Optical Pattern Recognition XIX, 697706 (17 March 2008); doi: 10.1117/12.785891; https://doi.org/10.1117/12.785891
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