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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