Automatic Ship Recognition Chain on Satellite Multispectral Imagery

Abstract

This article elaborates a processing chain devised to recognize the ships existing on medium resolution multispectral imageries (MSI). The chain consists of the following three steps. Firstly, an adaptive local saliency mapping technique is instigated on open ocean regions to obtain all floating objects. Secondly, to extract the ship candidates, two-step verification is applied based on specific spectral and geometric information of the ships. Lastly, a calculation to determine the properties of the ships, including their length, breadth, and heading, is then carried out. Furthermore, we propose a novel method for correcting miscalculated ship heading; by combining wake segmentation and Radon Transform (RT) approaches to locate the position and estimate the length of the wake generated by the ships. With the detected wake length, ship velocity can also be assessed. The developed chain is then tested using imageries acquired by LAPAN-A3 microsatellite, and the results are compared to those reported by the Automatic Identification System (AIS). Experimental results indicate that the proposed chain achieves higher detection performance and can produce better heading information compared to the existing methods.