A Bayesian Approach to Oil Slicks Edge Detection Based on SAR Data

This paper proposes a Bayesian edge detector to be fed by polarimetric, possibly multifrequency, synthetic aperture radar (SAR) data. It can be used to detect dark spots on the ocean surface and, hence, as the first stage of a system for identification and monitoring of oil slicks. The proposed detector does not require secondary data (i.e., pixels from a slick-free area) but for a certain a priori knowledge; remarkably, a preliminary performance assessment, based on both synthetic and real SAR recordings, shows that it has a slightly better performance in terms of detection and false alarm control than previously proposed classical (i.e., non-Bayesian) detectors.