An Inshore Ship Detection Method in SAR Images Based on Contextual Fluctuation Information
Rufei Wang, Yulin Huang, Yin Zhang, Jifang Pei, Junjie Wu, Jianyu Yang · 2019
During the inshore ship detection in SAR images, the high similarity between the harbor and the ship body on gray and texture features, resulting in low detection accuracy and high false alarm rate. In this paper, we propose a new approach using contextual fluctuation information to deal with this problem. Firstly, the maximum stability extremal region (MSER) method is used for global pre-screening to quickly obtain candidate targets. Next, the context slice of each candidate target is obtained, then each slice is devided into grids. Distinguish real ship targets from false alarms based on the fluctuations in pixel values within the divided grid. Experimental results based on satellite-borne SAR data illustrate that the proposed method obtains excellent detection performance and low false alarm rate.