Image super-resolution with adaptive regularization sparse representation
基于稀疏表示的自适应图像超分辨率重建算法

Conduct research on the existence and uniqueness of sparse resolution in super-resolution image reconstruction and the relationship of edge feature and smoothing noise of super-resolution image. In order to solve these problems, this paper proposed the mean of adaptive regularization. Combining with joint over-complete dictionary, it realized dynamically adjust the regularization parameter. Through super-resolution image reconstruction experiment, it demonstrates that this algorithm is working efficiently and balances edge features and smoothing noise well, which has high PSNR compared with the traditional algorithm.