Level-Set Formulation Based on an Infinite Series of Sample Moments for SAR Image Segmentation

Abstract

SAR image segmentation plays a central role in geoscience and remote sensing of the environment. Recently, methodologies that apply traditional segmentation algorithms to maps of statistical information extracted from SAR image rather than to the raw data itself have shown promising results. Nonetheless, the application of more powerful segmentation methods to these maps is constrained by the lack of adequate statistical models for such data. In this letter, we present a level-set-based algorithm that embodies much of the data statistics without assuming any prior model for it. We also evaluated its performance on both real and synthetic SAR images.