Target detection in SAR images based on a level set approach

Authors:
Regis C. P. Marques;Fatima N. Sombra De Medeiros;Daniela M. Ushizima
Affiliations:
Federal Center of Technology Education, Fortaleza, CE, Brazil;Department of Teleinformatics, Federal University of Ceara, Fortaleza, CE, Brazil;Math and Visualization Groups, Lawrence Berkeley National Laboratory, Berkeley, CA
Venue:
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Year:
2009

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Abstract

This paper introduces a new framework for point target detection in synthetic aperture radar (SAR) images. We focus on the task of locating reflective small regions using a level-set-based algorithm. Unlike most of the approaches in image segmentation, we address an algorithm that incorporates speckle statistics instead of empirical parameters and also discards speckle filtering. The curve evolves according to speckle statistics, initially propagating with a maximum upward velocity in homogeneous areas. Our approach is validated by a series of tests on synthetic and real SAR images and compared with three other segmentation algorithms, demonstrating that it configures a novel and efficient method for target-detection purpose.