关键词: 超分辨率, 锚定邻域回归, 图像重建, 残差

Abstract: This paper presents a new multi-dictionary learning algorithm for the problem of single super-resolution for the common dictionary-based SR algorithm ignoring the structure of the image, and some high-frequency information in the image reconstruction process. Firstly, the dominant direction of each image patch should be computed before clustering, then training dictionaries. Next, the residual image patches which computed by the dictionaries can be used to get residual dictionaries. Last, adjusted anchored neighborhood regression is used to reconstruct image, experimental results show that the algorithm has a better result both on visual effect and objective compared with other methods.

Key words: super-resolution, anchored neighborhood regression, image reconstruction, residual