Video super-resolution with 3D adaptive normalized convolution
文献类型：期刊论文
| 作者 | Zhang, Kaibing2; Mu, Guangwu2; Yuan, Yuan1 ; Gao, Xinbo2; Tao, Dacheng3,4
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| 刊名 | neurocomputing
 |
| 出版日期 | 2012-10-01 |
| 卷号 | 94页码:140-151 |
| 关键词 | Normalized convolution (NC) Motion estimation Video super-resolution (SR) |
| ISSN号 | 0925-2312 |
| 产权排序 | 2 |
| 合作状况 | 国际 |
| 英文摘要 | the classic multi-image-based super-resolution (sr) methods typically take global motion pattern to produce one or multiple high-resolution (hr) versions from a set of low-resolution (lr) images. however, due to the influence of aliasing and noise, it is difficult to obtain highly accurate registration with sub-pixel accuracy. moreover, in practical applications, the global motion pattern is rarely found in the real lr inputs. in this paper, to surmount or at least reduce the aforementioned problems, we develop a novel sr framework for video sequence by extending the traditional 2-dimentional (2d) normalized convolution (nc) to 3-dimentional (3d) case. in the proposed framework, to bypass explicit motion estimation, we estimate a target pixel by taking a weighted average of pixels from its neighborhood. we further up-scale the input video sequence in temporal dimension based on the extended 3d nc and hence more video frames can be generated. fundamental experiments demonstrate the effectiveness of the proposed sr framework both quantitatively and perceptually. (c) 2012 elsevier b.v. all rights reserved. |
| WOS标题词 | science & technology ; technology |
| 类目[WOS] | computer science, artificial intelligence |
| 研究领域[WOS] | computer science |
| 关键词[WOS] | high-resolution image ; reconstruction algorithm ; motion estimation ; regression |
| 收录类别 | SCI ; EI |
| 语种 | 英语 |
| WOS记录号 | WOS:000307087000014 |
| 公开日期 | 2012-09-03 |
| 源URL | [http://ir.opt.ac.cn/handle/181661/20265]  |
| 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 OPTIMAL, Xian 710119, Peoples R China 2.Xidian Univ, Sch Elect Engn, Xian 710071, Peoples R China 3.Univ Technol Sydney, Ctr Quantum Computat & Intelligent Syst, Sydney, NSW 2007, Australia 4.Univ Technol Sydney, Fac Engn & Informat Technol, Sydney, NSW 2007, Australia |
| 推荐引用方式 GB/T 7714 | Zhang, Kaibing,Mu, Guangwu,Yuan, Yuan,et al. Video super-resolution with 3D adaptive normalized convolution[J]. neurocomputing,2012,94:140-151. |
| APA | Zhang, Kaibing,Mu, Guangwu,Yuan, Yuan,Gao, Xinbo,&Tao, Dacheng.(2012).Video super-resolution with 3D adaptive normalized convolution.neurocomputing,94,140-151. |
| MLA | Zhang, Kaibing,et al."Video super-resolution with 3D adaptive normalized convolution".neurocomputing 94(2012):140-151. |
入库方式： OAI收割
来源：西安光学精密机械研究所
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