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An Improved Shape Contexts Based Ship Classification in SAR Images

机译:SAR图像中基于形状上下文的改进舰船分类

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In synthetic aperture radar (SAR) imagery, relating to maritime surveillance studies, the ship has always been the main focus of study. In this letter, a method of ship classification in SAR images is proposed to enhance classification accuracy. In the proposed method, to fully exploit the distinguishing characters of the ship targets, both topology and intensity of the scattering points of the ship are considered. The results of testing the proposed method on a data set of three types of ships, collected via a space-borne SAR sensor designed by the Institute of Electronics, Chinese Academy of Sciences (IECAS), establish that the proposed method is superior to several existing methods, including the original shape contexts method, traditional invariant moments and the recent approach.
机译:在与海上监视研究有关的合成孔径雷达(SAR)图像中,船舶一直是研究的主要重点。在这封信中,提出了一种在SAR图像中进行船舶分类的方法,以提高分类精度。在该方法中,为了充分利用舰船目标的区别特征,同时考虑了舰船散射点的拓扑结构和强度。通过由中国科学院电子学研究所(IECAS)设计的星载SAR传感器在三种类型的船舶数据集上测试该方法的结果表明,该方法优于现有的几种方法方法,包括原始形状上下文方法,传统不变矩和最新方法。

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