IEECAS OpenIR  > 黄土与第四纪地质国家重点实验室(2010~)
Hyperspectral image classification based on joint spectrum of spatial space and spectral space
Zhang, XR(Zhang, Xiaorong)1,2,3; Pan, ZB(Pan, Zhibin)1; Lu, XQ(Lu, Xiaoqiang)3; Hu, BL(Hu,Bingliang)3; Zheng, X(Zheng, Xi)4; Zhang, Xiaorong
2018-01
Source PublicationMultimedia Tools and Applications
Issue2018Pages:1-19
AbstractThis 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.
KeywordClassification Hyperspectral Imagery Spectral-spatial Fusion Affine Transform Feature Extraction Probabilistic Fusion
DOI10.1007/s11042-017-5552-6
Language英语
Citation statistics
Document Type期刊论文
Identifierhttp://ir.ieecas.cn/handle/361006/5295
Collection黄土与第四纪地质国家重点实验室(2010~)
Corresponding AuthorZhang, Xiaorong
Affiliation1.School of Electronic & Information Engineering, Xi’an Jiaotong University, Xi’an 710049, People’s Republic of China
2.University of Chinese Academy of Sciences, Beijing 100039, People’s Republic of China
3.Xi’an Institute of Optics and Precision Mechanics, Chinese Academy of Science, Xi’an 710119, People’s Republic of China
4.Institute of Earth Environment Chinese Academy of Sciences, Xi’an 710016, People’s Republic of China
Recommended Citation
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(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(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 .2018(2018):1-19.
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