Knowledge Management System Of South China Sea Institute of Oceanology,CAS
| Learning Discriminative Sparse Representations for Hyperspectral Image Classification | |
| Du, Peijun; Xue, Zhaohui; Li, Jun; Plaza, Antonio; xzh2012@163.com | |
| 2015 | |
| Source Publication | IEEE JOURNAL OF SELECTED TOPICS IN SIGNAL PROCESSING
 |
| Volume | 9Issue:6Pages:1089-1104 |
| Subtype | 1932-4553 |
| Abstract | 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. |
| Department | [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 |
| Keyword | Hyperspectral Image Classification Discriminative Sparse Representation (Dsr) Total Variation (Tv) Dictionary Learning Sparse Multinomial Logistic Regression (Smlr) |
| Subject Area | Engineering |
| Indexed By | SCI |
| Document Type | 期刊论文 |
| Identifier | http://ir.scsio.ac.cn/handle/344004/15039 |
| Collection | 热带海洋环境国家重点实验室(LTO) |
| Corresponding Author | xzh2012@163.com |
| Recommended Citation 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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| Learning Discriminat（5126KB） | 期刊论文 | 作者接受稿 | 开放获取 | CC BY-NC-SA | Application Full Text | |
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