Learning Discriminative Sparse Representations for Hyperspectral Image Classification
Du, Peijun; Xue, Zhaohui; Li, Jun; Plaza, Antonio; xzh2012@163.com
2015
发表期刊IEEE JOURNAL OF SELECTED TOPICS IN SIGNAL PROCESSING
卷号9期号:6页码:1089-1104
摘要In sparse representation (SR) driven hyperspectral image classification, signal-to-reconstruction rule-based classification may lack generalization performance. In order to overcome this limitation, we presents a new method for discriminative sparse representation of hyperspectral data by learning a reconstructive dictionary and a discriminative classifier in a SR model regularized with total variation (TV). The proposed method features the following components. First, we adopt a spectral unmixing by variable splitting augmented Lagrangian and TV method to guarantee the spatial homogeneity of sparse representations. Second, we embed dictionary learning in the method to enhance the representative power of sparse representations via gradient descent in a class-wise manner. Finally, we adopt a sparse multinomial logistic regression (SMLR) model and design a class-oriented optimization strategy to obtain a powerful classifier, which improves the performance of the learnt model for specific classes. The first two components are beneficial to produce discriminative sparse representations. Whereas, adopting SMLR allows for effectively modeling the discriminative information. Experimental results with both simulated and real hyperspectral data sets in a number of experimental comparisons with other related approaches demonstrate the superiority of the proposed method.
部门归属[Du, Peijun; Xue, Zhaohui] Nanjing Univ, Jiangsu Ctr Collaborat Innovat Geog Informat Reso, Jiangsu Prov Key Lab Geog Informat Sci & Technol, Key Lab Satellite Mapping Technol & Applicat,Natl, Nanjing 210023, Jiangsu, Peoples R China; [Du, Peijun; Xue, Zhaohui] Nanjing Univ, Collaborat Innovat Ctr South China Sea Studies, Nanjing 210023, Jiangsu, Peoples R China; [Li, Jun] Sun Yat Sen Univ, Sch Geog & Planning, Guangdong Prov Key Lab Urbanizat & Geosimulat, Guangzhou 510275, Guangdong, Peoples R China; [Plaza, Antonio] Univ Extremadura, Escuela Politecn, Dept Technol Comp & Commun, Hyperspectral Comp Lab, Caceres 10071, Spain ; LTO
关键词Hyperspectral Image Classification Discriminative Sparse Representation (Dsr) Total Variation (Tv) Dictionary Learning Sparse Multinomial Logistic Regression (Smlr)
学科领域Engineering
文献类型期刊论文
条目标识符http://ir.scsio.ac.cn/handle/344004/14926
专题热带海洋环境国家重点实验室(LTO)
通讯作者xzh2012@163.com
推荐引用方式
GB/T 7714
Du, Peijun,Xue, Zhaohui,Li, Jun,et al. Learning Discriminative Sparse Representations for Hyperspectral Image Classification[J]. IEEE JOURNAL OF SELECTED TOPICS IN SIGNAL PROCESSING,2015,9(6):1089-1104.
APA Du, Peijun,Xue, Zhaohui,Li, Jun,Plaza, Antonio,&xzh2012@163.com.(2015).Learning Discriminative Sparse Representations for Hyperspectral Image Classification.IEEE JOURNAL OF SELECTED TOPICS IN SIGNAL PROCESSING,9(6),1089-1104.
MLA Du, Peijun,et al."Learning Discriminative Sparse Representations for Hyperspectral Image Classification".IEEE JOURNAL OF SELECTED TOPICS IN SIGNAL PROCESSING 9.6(2015):1089-1104.
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