Hyperspectral image classification based on joint spectrum of spatial space and spectral space
Zhang, XR(Zhang, Xiaorong)1,2,3; Pan, ZB(Pan, Zhibin)2; Lu, XQ(Lu, Xiaoqiang)1; Hu, BL(Hu,Bingliang)1; Zheng, X(Zheng, Xi)4; Zhang, Xiaorong
刊名Multimedia Tools and Applications
2018-01
卷号77期号:2018页码:1-19
关键词Classification Hyperspectral Imagery Spectral-spatial Fusion Affine Transform Feature Extraction Probabilistic Fusion
ISSN号1380-7501
DOI10.1007/s11042-017-5552-6
通讯作者Zhang, Xiaorong(zhangxiaorong@opt.ac.cn)
英文摘要This paper presents a novel feature extraction model that incorporates local histogram in spatial space and pixel spectrum in spectral space, with the goal of hyperspectral image classification. We named this joint spectrum as 3D spectrum. Moreover, as a pre-processing step, an iterative procedure, which exploits spectral information in such a way that it considers corrupted bands existing in the data cube, is applied to original hyperspectral image. Further, Affine transform is applied to the bands chosen by the aforementioned procedure. The final feature is extracted by affine transform and 3D spectrum model, and as an input of widely used classifier of Support Vector Machine. As a post-processing step, multiple iterative results are fused in the level of probability. Our experimental results indicate that the proposed methodology leads to state-of-the-art classification results when combined with probabilistic classifiers for several widely used hyperspectral data sets, even when very only limited training samples are available.
资助项目National Natural Science Foundation of China (NSFC)[61501456] ; National Natural Science Foundation of China (NSFC)[XAB2016B20]
WOS关键词FEATURE-EXTRACTION ; BAND SELECTION ; SALIENCY ; KERNEL
WOS研究方向Computer Science ; Engineering
语种英语
出版者SPRINGER
WOS记录号WOS:000451780800033
资助机构National Natural Science Foundation of China (NSFC)
内容类型期刊论文
源URL[http://ir.ieecas.cn/handle/361006/5295]  
专题地球环境研究所_黄土与第四纪地质国家重点实验室(2010~)
通讯作者Zhang, Xiaorong
作者单位1.Xi’an Institute of Optics and Precision Mechanics, Chinese Academy of Science, Xi’an 710119, People’s Republic of China
2.School of Electronic & Information Engineering, Xi’an Jiaotong University, Xi’an 710049, People’s Republic of China
3.University of Chinese Academy of Sciences, Beijing 100039, People’s Republic of China
4.Institute of Earth Environment Chinese Academy of Sciences, Xi’an 710016, People’s Republic of China
推荐引用方式
GB/T 7714
Zhang, XR,Pan, ZB,Lu, XQ,et al. Hyperspectral image classification based on joint spectrum of spatial space and spectral space[J]. Multimedia Tools and Applications,2018,77(2018):1-19.
APA Zhang, XR,Pan, ZB,Lu, XQ,Hu, BL,Zheng, X,&Zhang, Xiaorong.(2018).Hyperspectral image classification based on joint spectrum of spatial space and spectral space.Multimedia Tools and Applications,77(2018),1-19.
MLA Zhang, XR,et al."Hyperspectral image classification based on joint spectrum of spatial space and spectral space".Multimedia Tools and Applications 77.2018(2018):1-19.
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