Detection of Oil Spills in SAR Images using Threshold Segmentation Algorithms

Identification of potential oil spills on Synthetic Aperture Radar (SAR) satellite images is a complex process. Oil companies, as well as the coast guard have tested a whole range of methods for monitoring and detection of possible oil spills. These meth-ods are found to be expensive, complex and require high pro-cessing power and time. In this paper, an oil spill detection method is proposed. The method consists of four main stages, namely: 1) Image enhancement; 2) Image segmentation 3) fea-ture extraction; and 4) Object recognition of the segmented ob-jects as oil spills or look-likes. The algorithm was trained on a large number of Synthetic Aperture Radar (SAR) images. The proposed thresholding algorithm can be considered an alterna-tive to manual inspection for large ocean areas. Promising results and high detection rates for the oil spills have been achieved. General Terms