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Multiregion Level-Set Partitioning of Synthetic Aperture Radar Images
May 2005 (vol. 27 no. 5)
pp. 793-800
The purpose of this study is to investigate Synthetic Aperture Radar (SAR) image segmentation into a given but arbitrary number of gamma homogeneous regions via active contours and level sets. The segmentation of SAR images is a difficult problem due to the presence of speckle which can be modeled as strong, multiplicative noise. The proposed algorithm consists of evolving simple closed planar curves within an explicit correspondence between the interiors of curves and regions of segmentation to minimize a criterion containing a term of conformity of data to a speckle model of noise and a term of regularization. Results are shown on both synthetic and real images.

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Index Terms:
Image segmentation, active contours, level sets, statistical modeling, synthetic aperture radar.
Citation:
Ismail Ben Ayed, Amar Mitiche, Ziad Belhadj, "Multiregion Level-Set Partitioning of Synthetic Aperture Radar Images," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 27, no. 5, pp. 793-800, May 2005, doi:10.1109/TPAMI.2005.106
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