Acta Optica Sinica, Volume. 37, Issue 3, 318006(2017)
Single Image Super-Resolution Restoration Algorithm from External Example to Internal Self-Similarity
Single image super-resolution (SR) restoration is an ill-posed inverse problem, in which regularization restriction is done with image priori knowledge. One single image SR method is proposed which simultaneously taking external example and internal self-similarity into account. Here the external knowledge is learned by convolutional neural network from external low-resolution-high-resolution image pairs, while the internal prior is utilized by cluster and low-rank approximation. The experimental results show that the proposed method outperforms many other existing super-resolution methods in recovery effect and robustness.
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Zheng Xiangtao, Yuan Yuan, Lu Xiaoqiang. Single Image Super-Resolution Restoration Algorithm from External Example to Internal Self-Similarity[J]. Acta Optica Sinica, 2017, 37(3): 318006
Received: Oct. 8, 2016
Accepted: --
Published Online: Mar. 8, 2017
The Author Email: Xiangtao Zheng (zhengxiangtao@opt.cn)