A two-stage method for oil slick segmentation

In this paperwe propose a two-stage algorithmfor oil slick segmentation in synthetic aperture radar (SAR) images. In the first stage, we propose a new variational model to reduce speckles in non-textured SAR images. Applications to simulated and real SAR images showthat themethod is well balanced in the quality of the conventional criteria. Then, in the second stage, we use the fast Chan-Vese (CV) model and the level set method to segment the oil slick in the de-speckled SAR image. The additive operator splitting (AOS) scheme is used in the numerical implementation to improve computational efficiency. Experimental results show that our two-stage algorithmis effective for oil slick segmentation in SAR images.