Journal
IEEE TRANSACTIONS ON IMAGE PROCESSING
Volume 27, Issue 5, Pages 2560-2574Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TIP.2018.2806201
Keywords
SAR image segmentation; level sets; edgeworth series expansion; multi-texture model; multi-region segmentation
Funding
- National Natural Science Foundation of China [41371340, 41571333]
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Synthetic aperture radar (SAR) image segmentation is a difficult problem due to the presence of strong multiplicative noise. To attain multi-region segmentation for SAR images, this paper presents a parametric segmentation method based on the multi-texture model with level sets. Segmentation is achieved by solving level set functions obtained from minimizing the proposed energy functional. To fully utilize image information, edge feature and region information are both included in the energy functional. For the need of level set evolution, the ratio of exponentially weighted averages operator is modified to obtain edge feature. Region information is obtained by the improved edgeworth series expansion, which can adaptively model a SAR image distribution with respect to various kinds of regions. The performance of the proposed method is verified by three high resolution SAR images. The experimental results demonstrate that SAR images can be segmented into multiple regions accurately without any speckle pre-processing steps by the proposed method.
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