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Image super-resolution framework with multi-channel constraints

  • Ci Wang*
  • , Ping Xue
  • , Weisi Lin
  • , Minmin Shen
  • *此作品的通讯作者
  • Nanyang Technological University

科研成果: 书/报告/会议事项章节会议稿件同行评审

摘要

Super-resolution reconstruction (SR) has been widely used to produce a high resolution (HR) image from several low resolution (LR) ones. In current methods, a LR image is selected as benchmark and upsampled as the initial SR estimate. This SR estimate is then degraded and compared with the adjacent LR frames for correction. Considering LR images captured from the same HR image with different translation at different instants, SR outputs by different benchmark selection should be identical, so tighter constraints can be designed to limit SR indetermination and to produce better SR images. In this paper, we propose a novel SR framework and prove its efficiency statistically using the unbiased estimation. Experimental results indicate that the proposed algorithm outperforms some existing approaches in both subjective and objective terms.

源语言英语
主期刊名Proceedings of the 2007 IEEE International Conference on Multimedia and Expo, ICME 2007
出版商IEEE Computer Society
456-459
页数4
ISBN(印刷版)1424410177, 9781424410170
DOI
出版状态已出版 - 2007
已对外发布
活动IEEE International Conference onMultimedia and Expo, ICME 2007 - Beijing, 中国
期限: 2 7月 20075 7月 2007

出版系列

姓名Proceedings of the 2007 IEEE International Conference on Multimedia and Expo, ICME 2007

会议

会议IEEE International Conference onMultimedia and Expo, ICME 2007
国家/地区中国
Beijing
时期2/07/075/07/07

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