An Adaptive Regularization Image Super-resolution Reconstruction Algorithm

Because of the traditional regularization parameters in the regularization method is fixed, in reconstruction images are not good to keep details such as image edge and texture information. In view of these shortcomings is proposed in this paper a bilateral total variation based on adaptive regularization image super-resolution algorithm, through changing regularized parameter to control the data fidelity term in the objective function and the proportion of regularization. Experimental results show that compared with the traditional reconstruction method in this paper, the method to the determination of adaptive regularization parameter, find the optimal solution, and in the region of the edge and texture details such as embodies better reconstruction effect.