| Zernike-Moment-Based Image Super Resolution | |
| Gao, Xinbo1; Wang, Qian1; Li, Xuelong2; Tao, Dacheng3; Zhang, Kaibing1 | |
| 作者部门 | 光学影像分析与学习中心 |
| 2011-10-01 | |
| 发表期刊 | IEEE TRANSACTIONS ON IMAGE PROCESSING
 |
| ISSN | 1057-7149 |
| 卷号 | 20期号:10页码:2738-2747 |
| 产权排序 | 2 |
| 摘要 | Multiframe super-resolution (SR) reconstruction aims to produce a high-resolution (HR) image using a set of low-resolution (LR) images. In the process of reconstruction, fuzzy registration usually plays a critical role. It mainly focuses on the correlation between pixels of the candidate and the reference images to reconstruct each pixel by averaging all its neighboring pixels. Therefore, the fuzzy-registration-based SR performs well and has been widely applied in practice. However, if some objects appear or disappear among LR images or different angle rotations exist among them, the correlation between corresponding pixels becomes weak. Thus, it will be difficult to use LR images effectively in the process of SR reconstruction. Moreover, if the LR images are noised, the reconstruction quality will be affected seriously. To address or at least reduce these problems, this paper presents a novel SR method based on the Zernike moment, to make the most of possible details in each LR image for high-quality SR reconstruction. Experimental results show that the proposed method outperforms existing methods in terms of robustness and visual effects. |
| 文章类型 | Article |
| 关键词 | Fuzzy Motion Estimation Image Super Resolution (Sr) Zernike Moment |
| 学科领域 | 信号与模式识别 |
| WOS标题词 | Science & Technology ; Technology |
| DOI | 10.1109/TIP.2011.2134859 |
| 收录类别 | SCI ; EI |
| 关键词[WOS] | SUPERRESOLUTION IMAGE ; RECONSTRUCTION ; RESTORATION ; RECOGNITION ; ALGORITHMS ; NOISY |
| 语种 | 英语 |
| WOS研究方向 | Computer Science ; Engineering |
| WOS类目 | Computer Science, Artificial Intelligence ; Engineering, Electrical & Electronic |
| WOS记录号 | WOS:000295008100004 |
| 引用统计 | |
| 文献类型 | 期刊论文 |
| 条目标识符 | http://ir.opt.ac.cn/handle/181661/14378 |
| 专题 | 光谱成像技术研究室 |
| 作者单位 | 1.Xidian Univ, Sch Elect Engn, Xian 710071, Peoples R China 2.Chinese Acad Sci, Ctr OPT IMagery Anal & Learning OPTIMAL, State Key Lab Transient Opt & Photon, Xian Inst Opt & Precis Mech, Xian 710119, Peoples R China 3.Univ Technol Sydney, Fac Engn & Informat Technol, Ctr Quantum Computat & Intelligent Syst, Sydney, NSW 2007, Australia |
| 推荐引用方式 GB/T 7714 | Gao, Xinbo,Wang, Qian,Li, Xuelong,et al. Zernike-Moment-Based Image Super Resolution[J]. IEEE TRANSACTIONS ON IMAGE PROCESSING,2011,20(10):2738-2747. |
| APA | Gao, Xinbo,Wang, Qian,Li, Xuelong,Tao, Dacheng,&Zhang, Kaibing.(2011).Zernike-Moment-Based Image Super Resolution.IEEE TRANSACTIONS ON IMAGE PROCESSING,20(10),2738-2747. |
| MLA | Gao, Xinbo,et al."Zernike-Moment-Based Image Super Resolution".IEEE TRANSACTIONS ON IMAGE PROCESSING 20.10(2011):2738-2747. |
| 条目包含的文件 | ||||||
| 文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
| Zernike-Moment-Based（2167KB） | 期刊论文 | 出版稿 | 限制开放 | CC BY-NC-SA | 请求全文 | |
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