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e-Article

A Bayesian Approach to Oil Slicks Edge Detection Based on SAR Data
Document Type
Periodical
Source
IEEE Transactions on Geoscience and Remote Sensing IEEE Trans. Geosci. Remote Sensing Geoscience and Remote Sensing, IEEE Transactions on. 52(5):2901-2909 May, 2014
Subject
Geoscience
Signal Processing and Analysis
Synthetic aperture radar
Covariance matrices
Image edge detection
Vectors
Detectors
Azimuth
Bayes methods
Bayesian detection
oil slicks
polarimetric synthetic aperture radar (SAR) data
Language
ISSN
0196-2892
1558-0644
Abstract
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.