18 April 2010 Target detection in SAR images using codifference and directional filters
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Abstract
Target detection in SAR images using region covariance (RC) and codifference methods is shown to be accurate despite the high computational cost. The proposed method uses directional filters in order to decrease the search space. As a result the computational cost of the RC based algorithm significantly decreases. Images in MSTAR SAR database are first classified into several categories using directional filters (DFs). Target and clutter image features are extracted using RC and codifference methods in each class. The RC and codifference matrix features are compared using l1 norm distance metric. Support vector machines which are trained using these matrices are also used in decision making. Simulation results are presented.
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Kaan Duman, Kaan Duman, A. Enis Çetin, A. Enis Çetin, } "Target detection in SAR images using codifference and directional filters", Proc. SPIE 7699, Algorithms for Synthetic Aperture Radar Imagery XVII, 76990S (18 April 2010); doi: 10.1117/12.850206; https://doi.org/10.1117/12.850206
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