doi: 10.4304/jsw.8.1.228-235
SAR Image Segmentation Based on Fuzzy Region Competition Method and Gamma Model
2College of Information Engineering, Qingdao University, Qingdao, China
Abstract—In this paper, we present a novel variational framework for multiphase synthetic aperture radar (SAR) image segmentation based on the fuzzy region competition method. A new energy functional is proposed to integrate the Gamma model and the edge detector based on the ratio of exponentially weighted averages (ROEWA) operator within the optimization process. To solve the optimization problem efficiently, the functional is firstly modified to be convex and differentiable by using the fuzzy membership functions. And then the constrained optimization problem is converted to an unconstrained one by using the variable splitting techniques and the augmented Lagrangian method (ALM). Finally the energy is minimized with an alternative iterative minimization algorithm. The effectiveness of our proposed algorithm is validated by experiments on both synthetic and real SAR images.
Index Terms—SAR image, segmentation, ROEWA, fuzzy membership functions, augmented Lagrangian method.
Cite: Cunliang Liu, Yongguo Zheng, Zhenkuan Pan, Jinming Duan, Guodong Wang, "SAR Image Segmentation Based on Fuzzy Region Competition Method and Gamma Model," Journal of Software vol. 8, no. 1, pp. 228-235, 2013.
General Information
ISSN: 1796-217X (Online)
Abbreviated Title: J. Softw.
Frequency: Quarterly
APC: 500USD
DOI: 10.17706/JSW
Editor-in-Chief: Prof. Antanas Verikas
Executive Editor: Ms. Cecilia Xie
Abstracting/ Indexing: DBLP, EBSCO,
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