Hyperspectral image super-resolution via nonlocal low-rank tensor approximation and total variation regularization
文献类型：期刊论文
| 作者 | He, Shiying; Han Z(韩志) ; Chen XA(陈希爱); Wang Y(王尧)
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| 刊名 | Remote Sensing
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| 出版日期 | 2017 |
| 卷号 | 9期号:12页码:1-16 |
| ISSN号 | 2072-4292 |
| 关键词 | hyperspectral image super-resolution low-rank tensor approximation nonlocal self-similarity folded-concave regularization total variation ADMM |
| 通讯作者 | Han Z(韩志) |
| 产权排序 | 1 |
| 中文摘要 | Hyperspectral image (HSI) possesses three intrinsic characteristics: the global correlation across spectral domain, the nonlocal self-similarity across spatial domain, and the local smooth structure across both spatial and spectral domains. This paper proposes a novel tensor based approach to handle the problem of HSI spatial super-resolution by modeling such three underlying characteristics. Specifically, a noncovex tensor penalty is used to exploit the former two intrinsic characteristics hidden in several 4D tensors formed by nonlocal similar patches within the 3D HSI. In addition, the local smoothness in both spatial and spectral modes of the HSI cube is characterized by a 3D total variation (TV) term. Then, we develop an effective algorithm for solving the resulting optimization by using the local linear approximation (LLA) strategy and the alternative direction method of multipliers (ADMM). A series of experiments are carried out to illustrate the superiority of the proposed approach over some state-of-the-art approaches. |
| WOS标题词 | Science & Technology ; Technology |
| 类目[WOS] | Remote Sensing |
| 研究领域[WOS] | Remote Sensing |
| 关键词[WOS] | HIGH-RESOLUTION IMAGE ; RECONSTRUCTION ; SPARSE ; SELECTION |
| 收录类别 | SCI ; EI |
| 语种 | 英语 |
| WOS记录号 | WOS:000419235700082 |
| 源URL | [http://ir.sia.cn/handle/173321/21473]  |
| 专题 | 沈阳自动化研究所_机器人学研究室 |
| 作者单位 | 1.School of Mathematics and Statistics, Xi'an Jiaotong University, Xi'an, 710049, China 2.University of Chinese Academy of Sciences, Beijing 100049, China 3.State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China |
| 推荐引用方式 GB/T 7714 | He, Shiying,Han Z,Chen XA,et al. Hyperspectral image super-resolution via nonlocal low-rank tensor approximation and total variation regularization[J]. Remote Sensing,2017,9(12):1-16. |
| APA | He, Shiying,Han Z,Chen XA,&Wang Y.(2017).Hyperspectral image super-resolution via nonlocal low-rank tensor approximation and total variation regularization.Remote Sensing,9(12),1-16. |
| MLA | He, Shiying,et al."Hyperspectral image super-resolution via nonlocal low-rank tensor approximation and total variation regularization".Remote Sensing 9.12(2017):1-16. |
入库方式： OAI收割
来源：沈阳自动化研究所
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