Image Super-Resolution via Double Sparsity Regularized Manifold Learning
文献类型：期刊论文
| 作者 | Lu, Xiaoqiang ; Yuan, Yuan; Yan, Pingkun
|
| 刊名 | ieee transactions on circuits and systems for video technology
 |
| 出版日期 | 2013-12-01 |
| 卷号 | 23期号:12页码:2022-2033 |
| 关键词 | Double sparsity manifold learning single-image super-resolution (SR) sparse coding |
| 英文摘要 | over the past few years, high resolutions have been desirable or essential, e. g., in online video systems, and therefore, much has been done to achieve an image of higher resolution from the corresponding low-resolution ones. this procedure of recovering/rebuilding is called single-image super-resolution (sr). performance of image sr has been significantly improved via methods of sparse coding. that is to say, the image frame patch can be sparse linear combinations of basis elements. however, most of these existing methods fail to consider the local geometrical structure in the space of the training data. to take this crucial issue into account, this paper proposes a method named double sparsity regularized manifold learning (dsrml). dsrml can preserve the properties of the aforementioned local geometrical structure by employing manifold learning, e. g., locally linear embedding. based on a large amount of experimental results, dsrml is demonstrated to be more robust and more effective than previous efforts in the task of single-image sr. |
| WOS标题词 | science & technology ; technology |
| 类目[WOS] | engineering, electrical & electronic |
| 研究领域[WOS] | engineering |
| 关键词[WOS] | nonlinear dimensionality reduction ; quality assessment ; algorithm ; representations ; reconstruction ; interpolation ; dictionaries ; information ; regression ; robust |
| 收录类别 | SCI ; EI |
| 语种 | 英语 |
| WOS记录号 | WOS:000328047000002 |
| 公开日期 | 2015-06-30 |
| 源URL | [http://ir.opt.ac.cn/handle/181661/23467]  |
| 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 | Chinese Acad Sci, Ctr Opt Imagery Anal & Learning, Xian Inst Opt & Precis Mech, State Key Lab Transient Opt & Photon, Xian 710119, Peoples R China |
| 推荐引用方式 GB/T 7714 | Lu, Xiaoqiang,Yuan, Yuan,Yan, Pingkun. Image Super-Resolution via Double Sparsity Regularized Manifold Learning[J]. ieee transactions on circuits and systems for video technology,2013,23(12):2022-2033. |
| APA | Lu, Xiaoqiang,Yuan, Yuan,&Yan, Pingkun.(2013).Image Super-Resolution via Double Sparsity Regularized Manifold Learning.ieee transactions on circuits and systems for video technology,23(12),2022-2033. |
| MLA | Lu, Xiaoqiang,et al."Image Super-Resolution via Double Sparsity Regularized Manifold Learning".ieee transactions on circuits and systems for video technology 23.12(2013):2022-2033. |
入库方式： OAI收割
来源：西安光学精密机械研究所
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