SAR Image Segmentation Based on Fuzzy Region Competition Method and Gamma Model

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.