A Ship Target Discrimination Method Based on Change Detection in SAR Imagery

In order to reserve ship targets and reduce sea clutters as the false alarms from the SAR Regions Of Interest (ROI) chips, a ship discrimination feature named Target Pixel Aggregative Measure (TPAM) is proposed in this paper. Benefited from the technology of change detection, TPAM using the gray difference in SAR imagery to separate the target pixels and background pixels. Firstly, based on the assumption that the central pixels of a ROI belong to target pixels while the surrounding pixels fall into sea clutters, a change detection measure based on the likelihood ratio is used to generate the residual data. Then the target pixels and background pixels are automatically separated and produce a binary image by the KSW entropy method. Finally, the center of the binary image is used as a seed to implement region growing and TPAM can be obtained to discriminate targets and clutters. Experimental results using RADARSAT-1 SAR data show that the propose discrimination feature is not only simple and robust, but also has a strong differentiate ability, which can eliminate most of false alarms effectively.