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Graph-Regularized Low-Rank Representation for Destriping of Hyperspectral Images
文献类型：期刊论文
| 作者 | Lu, Xiaoqiang1 ; Wang, Yulong2; Yuan, Yuan1
|
| 刊名 | ieee transactions on geoscience and remote sensing
 |
| 出版日期 | 2013-07-01 |
| 卷号 | 51期号:7页码:4009-4018 |
| 关键词 | Destriping graph regularizer hyperspectral image low-rank representation (LRR) spectral correlation |
| ISSN号 | 0196-2892 |
| 产权排序 | 1 |
| 英文摘要 | hyperspectral image destriping is a challenging and promising theme in remote sensing. striping noise is a ubiquitous phenomenon in hyperspectral imagery, which may severely degrade the visual quality. a variety of methods have been proposed to effectively alleviate the effects of the striping noise. however, most of them fail to take full advantage of the high spectral correlation between the observation subimages in distinct bands and consider the local manifold structure of the hyperspectral data space. in order to remedy this drawback, in this paper, a novel graph-regularized low-rank representation (lrr) destriping algorithm is proposed by incorporating the lrr technique. to obtain desired destriping performance, two sides of performing destriping are included: 1) to exploit the high spectral correlation between the observation subimages in distinct bands, the technique of lrr is first utilized for destriping, and 2) to preserve the intrinsic local structure of the original hyperspectral data, the graph regularizer is incorporated in the objective function. the experimental results and quantitative analysis demonstrate that the proposed method can both remove striping noise and achieve cleaner and higher contrast reconstructed results. |
| WOS标题词 | science & technology ; physical sciences ; technology |
| 类目[WOS] | geochemistry & geophysics ; engineering, electrical & electronic ; remote sensing ; imaging science & photographic technology |
| 研究领域[WOS] | geochemistry & geophysics ; engineering ; remote sensing ; imaging science & photographic technology |
| 关键词[WOS] | landsat mss images ; histogram-modification ; striping removal ; modis data ; noise ; algorithm ; reduction ; transform ; pursuit |
| 收录类别 | SCI ; EI |
| 语种 | 英语 |
| WOS记录号 | WOS:000320942600018 |
| 源URL | [http://ir.opt.ac.cn/handle/181661/23181]  |
| 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, State Key Lab Transient Opt & Photon, Xian Inst Opt & Precis Mech, Ctr Opt Imagery Anal & Learning, Xian 710119, Peoples R China 2.Hubei Univ, Fac Math & Comp Sci, Wuhan 430062, Peoples R China |
| 推荐引用方式 GB/T 7714 | Lu, Xiaoqiang,Wang, Yulong,Yuan, Yuan. Graph-Regularized Low-Rank Representation for Destriping of Hyperspectral Images[J]. ieee transactions on geoscience and remote sensing,2013,51(7):4009-4018. |
| APA | Lu, Xiaoqiang,Wang, Yulong,&Yuan, Yuan.(2013).Graph-Regularized Low-Rank Representation for Destriping of Hyperspectral Images.ieee transactions on geoscience and remote sensing,51(7),4009-4018. |
| MLA | Lu, Xiaoqiang,et al."Graph-Regularized Low-Rank Representation for Destriping of Hyperspectral Images".ieee transactions on geoscience and remote sensing 51.7(2013):4009-4018. |
入库方式： OAI收割
来源：西安光学精密机械研究所
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