An Improved Super-Resolution Reconstruction Algorithm Based on Regularization

The traditional regularized super-resolution (SR) algorithms can reconstruct the high-resolution (HR) image to some extent. But the high frequency information of the image will lose seriously and the edges and details will become blurred. This paper presents an improved regularized SR algorithm. Firstly, a new interpolation algorithm is used to obtain the initial value of the HR image. Secondly, the trilateral filter is adopted as the regularization term to preserve the edge and details. Finally, the steepest descent method is taken as the iterative algorithm to gain the optimum solution. Simulated experiments are presented including the comparison with some existing reconstruction algorithms. Those results show that the proposed algorithm performs better than others. Furthermore, the edges and details of the image are well preserved.