基于结构特征分析的COSMO-SkyMed图像商用船舶分类算法

Algorithm for Merchant Ship Classification in COSMO-SkyMed Images based on Structural Feature Analysis

船舶分类与识别对于海洋交通运输监测与管理具有重要意义,同时也是SAR海洋应用的重要组成部分。COSMO-SkyMed高分辨率合成孔径雷达(SAR)图像下,商用船舶的结构轮廓明显,散货船、集装箱船和油船的特征清晰可辨,为船舶识别分类提供有效支持。提出了一种基于结构特征分析的商用船舶分类算法,通过提取核密度估计值、船舶积分主轴位置及左中右3部分积分量比例等特征,可实现船舶类型的区分。通过在东海试验区的同步实验,证明COSMO-SkyMed图像商用船舶分类算法的平均分类精度达到89.94%。

Ship classification and identification is of great significance for monitoring and management of marine transportation,and it's an important part of the SAR ocean applications.In the high resolution SAR images of COSMO-SkyMed,structural outlines of merchant ships are clear.Features of bulk carriers,container ships and oil tankers are legible,which provides support of ship classification effectively.This paper proposes an algorithm for merchant ship classification,which is based on structural feature analysis.Ship types are determined by feature extractions of Kernel Density Estimation,location of main axis,and the integration of left-middle-right part of the ship hull.Synchronous experiments performance in East China Sea shows that the average classification accuracy of the proposed algorithm is 89.94%.