Wishart分布
人工智能
计算机科学
分类器(UML)
分割
旋光法
计算机视觉
合成孔径雷达
模式识别(心理学)
图像分割
雷达成像
保险丝(电气)
目标检测
遥感
雷达
散射
地理
机器学习
工程类
物理
光学
电气工程
电信
多元统计
作者
Xiaokang Dai,Junjun Yin,Jian Yang,Liangjiang Zhou
标识
DOI:10.1109/igarss47720.2021.9553381
摘要
To solve the problem of dense vehicle target detection in polarimetric synthetic aperture radar (PolSAR) images from urban areas under complex scenarios, this paper proposes a target detection method that combines the superpixel segmentation and the Wishart classifier. Firstly, the buildings are detected based on the different polarimetric scattering characteristics of ground objects. Then, the morphological information of the target is obtained by the local Wishart classifier and the superpixel segmentation. After that, the center points of the target are obtained by the global Wishart classifier. Finally, the region growing procedure is used to fuse the information obtained by above-mentioned classifiers to complete the target detection task.
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