Affiliation:
1. The Chinese University of Hong Kong
2. The Hong Kong University of Science and Technology
Abstract
We propose a simple but effective upsampling method for automatically enhancing the image/video resolution, while preserving the essential structural information. The main advantage of our method lies in a feedback-control framework which faithfully recovers the high-resolution image information from the input data,
without
imposing additional local structure constraints learned from other examples. This makes our method independent of the quality and number of the selected examples, which are issues typical of learning-based algorithms, while producing high-quality results without observable unsightly artifacts. Another advantage is that our method naturally extends to video upsampling, where the temporal coherence is maintained automatically. Finally, our method runs very fast. We demonstrate the effectiveness of our algorithm by experimenting with different image/video data.
Funder
Research Grants Council, University Grants Committee, Hong Kong
Publisher
Association for Computing Machinery (ACM)
Subject
Computer Graphics and Computer-Aided Design
Reference28 articles.
1. Baker S. and Kanade T. 2000. Limits on super-resolution and how to break them. In CVPR IEEE Computer Society 2372--2379. Baker S. and Kanade T. 2000. Limits on super-resolution and how to break them. In CVPR IEEE Computer Society 2372--2379.
2. Bando Y. and Nishita T. 2007. Towards digital refocusing from a single photograph. In Pacific Graphics. 10.1109/PG.2007.64 Bando Y. and Nishita T. 2007. Towards digital refocusing from a single photograph. In Pacific Graphics . 10.1109/PG.2007.64
Cited by
159 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献