Oil Spill Candidate Detection from SAR Imagery Using Threasholding-Guided Maximally Stable Extremal Regions Algorithm

Oil spill will cause severe ecological disasters and enormous marine environment damages. we consider a robust and fast oil spill candidate detection problem for oil spill recognition systems for synthetic aperture radar (SAR) imagery. In this paper, we propose a automatic detection method called thresholding-guided maximally stable extremal regions (T-GMSERs) algorithm. First, thresholding approach is utlized to learn model parameters automatically. Candidate regions are extracted by using the maximally stable extremal region (MSER) detector. Then, we label each candidate region to obtain a binary potential target pixel map. Finally, the detection results are acquired by maximal stable criteria from the corresponding region map. Simulation based on satellite-borne data illustrates that the proposed algorithm obtains more precise detection performance without increasing the computational complexity.