A method for coastal oil tank detection in polarimetric SAR images based on recognition of T-shaped harbor

To automatically detect oil tanks in polarimetric syn-thetic aperture radar (SAR) images, a coastal oil tank detection method is proposed based on recognition of T-shaped harbor. First of all, the T-shaped harbor is detected to locate the region of inter-est (ROI) of oil tanks. Then all suspicious targets in the ROI are extracted by the segmentation of strong scattering targets and the classifier of H/α . The template targets are selected from the sus-picious targets by the combination of a proposed circular degree parameter and the similarity parameter (SP) of the polarimetric coherency matrix. Finally, oil tanks are detected according to the statistics of the similarity parameter between each suspicious tar-get and template targets in ROI. Polarimetric SAR data acquired by RADARSAT-2 over Berkeley and Singapore areas are used for testing. Experiment results show that most of the targets are correctly detected and the overall detection rate is close to 80%. The false rate is effectively reduced by the proposed algorithm compared with the method without T-shaped harbor recognition.