Ocean Front Detection from SAR Imagery Using SLIC Superpixel Segmentation Method

Ocean front can influent the distribution of sea material and it has an impact on underwater acoustic communication. Thus, the detection of ocean front is very important. In this paper, the simple linear iterative clustering (SLIC) superpixel segmentation approach is applied to ocean front detection in SAR images, which can suppress the influence of coherent speckle noise and extract the fuzzy boundary from high-resolution SAR images. The results show that this method can extract ocean front with one pixel width and the extraction of ocean front is in good agreement with human visual interpretation. This method provides a new idea to extract ocean fronts from SAR images.