Oil spill detection based on a superpixel segmentation method for SAR image

In this paper, a rapid oil spill detection approach which still maintains high detection accuracy is presented. The major contribution of the approach is using a superpixel segmentation method to subdivide the target SAR image into many approximate uniform scale pieces and preserves the boundaries well. Furthermore, a novel approach combine space distance, intensity deviation and size information together (SIS) is presented to eliminate the potential false positive, which is convenient and effective meanwhile. The proposed approach performs well and fast in both the synthetic data and RAD ARS AT-1 ScanSAR data which contain verified oil spills. The processing time is about 6s for a 512×512 image.