Multiregion level-set segmentation of synthetic aperture radar images

Authors:
Michael Ying Yang
Affiliations:
Department of Photogrammetry, University of Bonn, Bonn, Germany
Venue:
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Year:
2009

Citing 3
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Multiregion Level-Set Partitioning of Synthetic Aperture Radar Images

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Edge location in SAR images: performance of the likelihood ratio filter and accuracy improvement with an active contour approach

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Abstract

Due to the presence of speckle, segmentation of SAR images is generally acknowledged as a difficult problem. A large effort has been done in order to cope with the influence of speckle noise on image segmentation such as edge detection or direct global segmentation. Recent works address this problem by using statistical image representation and deformable models. We suggest a novel variational approach to SAR image segmentation, which consists of minimizing a functional containing an original observation term derived from maximum a posteriori (MAP) estimation framework and a Gamma image representation. The minimization is carried out efficiently by a new multiregion method which embeds a simple partition assumption directly in curve evolution to guarantee a partition of the image domain from an arbitrary initial partition. Experiments on both synthetic and real images show the effectiveness of the proposed method.