Target detection in SAR images using codifference and directional filters

Kaan Duman; A. Enis Çetin

doi:10.1117/12.850206

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18 April 2010 Target detection in SAR images using codifference and directional filters

Kaan Duman, A. Enis Çetin

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Proceedings Volume 7699, Algorithms for Synthetic Aperture Radar Imagery XVII; 76990S (2010) https://doi.org/10.1117/12.850206
Event: SPIE Defense, Security, and Sensing, 2010, Orlando, Florida, United States

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 and 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); https://doi.org/10.1117/12.850206

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