A Clustering and Enhancement Algorithm for SAR Surface Ship Targets

Marine target recognition technology from Synthetic Aperture Radar (SAR) images is of great significance in both civil and military fields, so it has become a research hotspot in various countries. However, in complex sea scenes, the existing Marine target detection and recognition technologies have poor accuracy and robustness in high-complexity and strong interference scenes, and cannot stably identify Marine targets in the face of various interference factors. This paper focuses on image preprocessing, and proposes a selection algorithm for the region of interest of the sea surface and a clustering and enhancement algorithm for potential targets based on sea-land separation. This method clusters strong points of the ship SAR image into a single connected surface target, and verifies that it can lay a good foundation for subsequent detection and recognition.