Multiregion level-set segmentation of synthetic aperture radar images

9 years 11 months ago
Multiregion level-set segmentation of synthetic aperture radar images
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.
Michael Ying Yang
Added 19 Feb 2011
Updated 19 Feb 2011
Type Journal
Year 2009
Where ICIP
Authors Michael Ying Yang
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