Small target detection in hyperspectral remote sensing image based on adaptive parameter SVM

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	Small target detection in hyperspectral remote sensing image based on adaptive parameter SVM
其他题名	基于自适应参数支持向量机的高光谱遥感图像小目标检测
	Wu, Yiquan; Zhou, Yang; Long, Yunlin
	2015-09-10
发表期刊	Guangxue Xuebao/Acta Optica Sinica
卷号	35 期号:9
摘要	As for the problem of small target detection in hyperspectral remote sensing image, a detection method based on adaptiveparameter support vector machine (SVM) is proposed. The low dimensional information of the hyperspectral image is obtained using the method of principal component analysis (PCA) and the redundancy of data is reduced. Then, small targets are positioned fast and roughly by an unsupervised detection method, and the posterior information of SVM is got by the position result. The kernel parameter of SVM is determined adaptively based on the posterior information and the criteria of divergence in the kernel space. The best hyperplane in the kernel space for the segmentation of targets and background is found by the SVM. Pixels are separated to targets and background by the best hyperplane. The accurate and stable target detection result is obtained by iteration. A large number of experimental results show that, compared to the existing methods such as RX method, kernel RX method and support vector data description (SVDD) method, the proposed method is more effective to detect small targets accurately in the hyperspectral remote sensing image. ©, 2015, Chinese Optical Society. All right reserved.
收录类别	EI
语种	中文
文献类型	期刊论文
条目标识符	http://ir.opt.ac.cn/handle/181661/27323
专题	光谱成像技术研究室
推荐引用方式 GB/T 7714	Wu, Yiquan,Zhou, Yang,Long, Yunlin. Small target detection in hyperspectral remote sensing image based on adaptive parameter SVM[J]. Guangxue Xuebao/Acta Optica Sinica,2015,35(9).
APA	Wu, Yiquan,Zhou, Yang,&Long, Yunlin.(2015).Small target detection in hyperspectral remote sensing image based on adaptive parameter SVM.Guangxue Xuebao/Acta Optica Sinica,35(9).
MLA	Wu, Yiquan,et al."Small target detection in hyperspectral remote sensing image based on adaptive parameter SVM".Guangxue Xuebao/Acta Optica Sinica 35.9(2015).

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