Incorporation Of Prior Knowledge In Automatic Classification Of Oil Spills In Ers Sar Images

We present algorithms for automatic detection of oil spills in SAR images. The developed framework consists of first detecting dark spots in the image, then computing a set of features for each dark spot, before the spot is classified as either an oil slick or a ''lookalike'' (other oceanographic phenomena which resembles oil slicks). Knowledge about the external conditions like wind level and slick surroundings are modelled. The presented algorithms are tested on 84 SAR images. The improved algorithms achieve a much higher classification accuracy than a previous classification model which did not incorporate prior knowledge.