Spatial-spectral-combined sparse representation-based classification for hyperspectral imagery

被引:0
|
作者
Sen Jia
Yao Xie
Guihua Tang
Jiasong Zhu
机构
[1] Shenzhen University,The Shenzhen Key Laboratory of Spatial Information Smarting Sensing and Services
[2] Shenzhen University,College of Computer Science and Software Engineering
来源
Soft Computing | 2016年 / 20卷
关键词
Hyperspectral imagery; Sparse representation-based classification; Spatial information;
D O I
暂无
中图分类号
学科分类号
摘要
Recently, sparse representation-based classification (SRC), which assigns a test sample to the class with minimum representation error via a sparse linear combination of all the training samples, has successfully been applied to hyperspectral imagery. Alternatively, spatial information, which means the adjacent pixels belong to the same class with a high probability, is a valuable complement to the spectral information. In this paper, we have presented a new spectral-spatial-combined SRC method, abbreviated as SSSRC or S3RC\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\mathrm{S}^{3}\mathrm{RC}$$\end{document}, to jointly consider the spectral and spatial neighborhood information of each pixel to explore the spectral and spatial coherence by the SRC method. Furthermore, a fast interference-cancelation operation is adopted to accelerate the classification procedure of S3RC\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\mathrm{S}^{3}\mathrm{RC}$$\end{document}, named FS3RC\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\mathrm{FS}^{3}\mathrm{RC}$$\end{document}. Experimental results have shown that both the proposed SRC-based approaches, S3RC\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\mathrm{S}^{3}\mathrm{RC}$$\end{document} and FS3RC\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\mathrm{FS}^{3}\mathrm{RC}$$\end{document}, could achieve better performance than the other state-of-the-art methods.
引用
收藏
页码:4659 / 4668
页数:9
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