Multiregion level-set segmentation of synthetic aperture radar images

Research output: Contribution to conferencePaper

6 Citations (Scopus)

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.
Original languageEnglish
Pages1717-1720
Number of pages4
DOIs
Publication statusPublished - Nov 2009
Event16th IEEE International Conference on Image Processing, ICIP 2009 - Cairo, Egypt
Duration: 7 Nov 200910 Nov 2009
Conference number: 16

Conference

Conference16th IEEE International Conference on Image Processing, ICIP 2009
Abbreviated titleICIP
CountryEgypt
CityCairo
Period7/11/0910/11/09

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    Yang, M. Y. (2009). Multiregion level-set segmentation of synthetic aperture radar images. 1717-1720. Paper presented at 16th IEEE International Conference on Image Processing, ICIP 2009, Cairo, Egypt. https://doi.org/10.1109/ICIP.2009.5413378