Single Image Super-Resolution via Mixed Examples and Sparse Representation | |
Liu, Weirong1; Shi, Changhong1; Liu, Chaorong2; Liu, Jie3 | |
2017 | |
关键词 | super-resolution sparse representation mixed example selection method discriminative dictionaries |
DOI | 10.1109/ACPR.2017.110 |
页码 | 730-734 |
英文摘要 | Existing super-resolution (SR) methods can be divided into two classes: the external examples SR and the internal examples SR. Although these two types of methods have been achieved satisfactory results, such methods are limited by their inherent flaws. This paper proposes mixed example selection method for combining the external examples with the internal examples. We cluster the internal examples into K classes, and select the similar external examples for every cluster to enrich the training database. And then we learn K discriminative dictionaries for the K cluster examples. Finally, we reconstruct the low resolution images with the learned discriminative dictionaries. Experiments validate the effectiveness of the proposed method in terms of visual and quantitative assessments. |
会议录 | PROCEEDINGS 2017 4TH IAPR ASIAN CONFERENCE ON PATTERN RECOGNITION (ACPR) |
会议录出版者 | IEEE |
会议录出版地 | 345 E 47TH ST, NEW YORK, NY 10017 USA |
语种 | 英语 |
资助项目 | National Natural Science Foundation of China[61461028] ; Natural Science Foundation of Gansu Province[1508RJZA092] |
WOS研究方向 | Computer Science |
WOS记录号 | WOS:000455581900124 |
内容类型 | 会议论文 |
源URL | [http://119.78.100.223/handle/2XXMBERH/36230] |
专题 | 电气工程与信息工程学院 党委教师工作部(人事处、教师发展中心) |
通讯作者 | Liu, Weirong |
作者单位 | 1.Lanzhou Univ Technol, Coll Elect & Informat Engn, Lanzhou 730050, Gansu, Peoples R China 2.Lanzhou Univ Technol, Key Lab Gansu Adv Control Ind Proc, Lanzhou 730050, Gansu, Peoples R China 3.Lanzhou Univ Technol, Natl Demonstrat Ctr Expt Elect & Control Engn Edu, Lanzhou 730050, Gansu, Peoples R China |
推荐引用方式 GB/T 7714 | Liu, Weirong,Shi, Changhong,Liu, Chaorong,et al. Single Image Super-Resolution via Mixed Examples and Sparse Representation[C]. 见:. |
个性服务 |
查看访问统计 |
相关权益政策 |
暂无数据 |
收藏/分享 |
除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。
修改评论