Ship detection for Radarsat-2 ScanSAR data using DoG scale-space

Synthetic Aperture Radar (SAR) is a significant tool to satisfy the growing demand of the maritime vessel traffic. ScanSAR, as an important role of SAR systems with very high imageries swath, is more suitable for the detection issue. In this paper, features of ships on Radarsat-2 ScanSAR imagery are characterized as “Bright-Dark” structure. According to the unique features, a new ship detector based on the Difference of Gauss (DoG) scale-space is proposed. To enhance the robustness, a threshold method simulated by the “dark spots” matrix is designed. In the threshold method, the average KL test is carried out with 6 different distributions on several Radarsat-2 ScanSAR Narrow imageries of sea which shows the Gamma distribution fits the sea clutter the best and is selected. Finally, the proposed detector is validated on a slice of Radarsat-2 ScanSAR imagery and comparisons with CFAR are made.