Merchant Vessel Classification Based on Scattering Component Analysis for COSMO-SkyMed SAR Images

Abstract

Ship classification in high-resolution synthetic aperture radar (SAR) satellite images is a hotspot and a continuing problem in SAR applications. The scattering components of ships are the strong scatter of objects in SAR images, and these can represent the superstructure of different ship types. Based on analyses of different scattering components of bulk carriers, oil tankers, and container ships, we propose a new classification method for these three ship types in COSMO-SkyMed SAR images. First, morphological preprocessing is applied to suppress sidelobes. Second, based on Hough transform (HT), the orientation of the principal axis is extracted, and the modified minimum enclosing rectangle (MER) of the ship is obtained and rotated along the principal axis. Finally, the ship type is decided according to the width ratio of MER between the HT line, the ratio of ship and nonship points on the principal axis, and the scattering density. The results show that this method has good performance in ship classification, with an overall accuracy of over 80%.