Low-Rank Total Variation for Multi-frame Image Super-resolution
Jun-Bao ZHAO, Xiao-Yan CHEN, Shengjin Wang · DEStech Transactions on Computer Science and Engineering · 2017
The methods based on regularization are the mainstream of super resolution research due to the characteristics of natural images. Even most of them are based on the total variation (TV) method, the characteristics of natural images cannot be expressed completely by this way. According to low rank property of natural image statistics, a new algorithm is proposed to restore more high-frequency details by combining both of them. Compare to other methods, experimental results show that the proposed algorithm can achieve a better reconstruction quality.