热门
Hyperspectral Image Classification via Multitask Joint Sparse Representation and Stepwise MRF Optimization
文献类型：期刊论文
| 作者 | Yuan, Yuan1; Lin, Jianzhe1; Wang, Qi2,3 |
| 刊名 | ieee transactions on cybernetics
 |
| 出版日期 | 2016-12-01 |
| 卷号 | 46期号:12页码:2966-2977 |
| 关键词 | Hyperspectral image (HSI) classification Markov random field (MRF) multitask sparse representation |
| ISSN号 | 2168-2267 |
| 产权排序 | 1 |
| 通讯作者 | wang, q (reprint author), northwestern polytech univ, sch comp sci, xian 710072, peoples r china. |
| 英文摘要 | hyperspectral image (hsi) classification is a crucial issue in remote sensing. accurate classification benefits a large number of applications such as land use analysis and marine resource utilization. but high data correlation brings difficulty to reliable classification, especially for hsi with abundant spectral information. furthermore, the traditional methods often fail to well consider the spatial coherency of hsi that also limits the classification performance. to address these inherent obstacles, a novel spectral-spatial classification scheme is proposed in this paper. the proposed method mainly focuses on multitask joint sparse representation (mjsr) and a stepwise markov random filed framework, which are claimed to be two main contributions in this procedure. first, the mjsr not only reduces the spectral redundancy, but also retains necessary correlation in spectral field during classification. second, the stepwise optimization further explores the spatial correlation that significantly enhances the classification accuracy and robustness. as far as several universal quality evaluation indexes are concerned, the experimental results on indian pines and pavia university demonstrate the superiority of our method compared with the state-of-the-art competitors. |
| WOS标题词 | science & technology ; technology |
| 学科主题 | computer science, artificial intelligence ; computer science, cybernetics |
| 类目[WOS] | computer science, artificial intelligence ; computer science, cybernetics |
| 研究领域[WOS] | computer science |
| 关键词[WOS] | discriminant-analysis ; selection ; recognition ; regression ; svm ; reconstruction ; segmentation ; saliency ; models |
| 收录类别 | SCI |
| 语种 | 英语 |
| WOS记录号 | WOS:000388923100023 |
| 源URL | [http://ir.opt.ac.cn/handle/181661/28558]  |
| 专题 | 西安光学精密机械研究所_光学影像学习与分析中心 |
| 作者单位 | 1.Chinese Acad Sci, Xian Inst Opt & Precis Mech, State Key Lab Transient Opt & Photon, Ctr Opt Imagery Anal & Learning, Xian 710119, Peoples R China 2.Northwestern Polytech Univ, Sch Comp Sci, Xian 710072, Peoples R China 3.Northwestern Polytech Univ, Ctr Opt Imagery Anal & Learning, Xian 710072, Peoples R China |
| 推荐引用方式 GB/T 7714 | Yuan, Yuan,Lin, Jianzhe,Wang, Qi. Hyperspectral Image Classification via Multitask Joint Sparse Representation and Stepwise MRF Optimization[J]. ieee transactions on cybernetics,2016,46(12):2966-2977. |
| APA | Yuan, Yuan,Lin, Jianzhe,&Wang, Qi.(2016).Hyperspectral Image Classification via Multitask Joint Sparse Representation and Stepwise MRF Optimization.ieee transactions on cybernetics,46(12),2966-2977. |
| MLA | Yuan, Yuan,et al."Hyperspectral Image Classification via Multitask Joint Sparse Representation and Stepwise MRF Optimization".ieee transactions on cybernetics 46.12(2016):2966-2977. |
入库方式： OAI收割
来源：西安光学精密机械研究所
浏览0
下载0
收藏0
其他版本
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。