- Title
- An Attention-Based Approach for Single Image Super Resolution
- Creator
- Liu, Yuan; Wang, Yuancheng; Li, Nan; Cheng, Xu; Zhang, Yifeng; Huang, Yongming; Lu, Guojun
- Date
- 2018
- Type
- Text; Conference proceedings; Conference paper
- Identifier
- http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/167617
- Identifier
- vital:13696
- Identifier
-
https://doi.org/10.1109/ICPR.2018.8545760
- Identifier
- ISBN:978-1-5386-3788-3
- Abstract
- The main challenge of single image super resolution (SISR) is the recovery of high frequency details such as tiny textures. However, most of the state-of-the-art methods lack specific modules to identify high frequency areas, causing the output image to be blurred. We propose an attention-based approach to give a discrimination between texture areas and smooth areas. After the positions of high frequency details are located, high frequency compensation is carried out. This approach can incorporate with previously proposed SISR networks. By providing high frequency enhancement, better performance and visual effect are achieved. We also propose our own SISR network composed of DenseRes blocks. The block provides an effective way to combine the low level features and high level features. Extensive benchmark evaluation shows that our proposed method achieves significant improvement over the state-of-the-art works in SISR.
- Publisher
- IEEE
- Relation
- 2018 24th International Conference on Pattern Recognition, ICPR 2018; Beijing, China; 20th-24th August 2018 Vol. 2018, p. 2777-2784
- Rights
- Copyright © 2018 IEEE.
- Rights
- This metadata is freely available under a CCO license
- Subject
- Image resolution; Optical resolving power; Image super
- Full Text
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