Image Super Resolution Based on Gradient Constrained POCS Method

A gradient constraint set based on edge detection is proposed to solve the problem of edge blurring in traditional projections onto convex sets (POCS) images reconstruction. Using the complete edge information of the original low-resolution(LR) image, the edge gradient constraint is applied to the reconstructed image, and the high-frequency information of the reconstructed image is retained to solve the problem of blurring the reconstructed image edge. And this paper uses the resolution test card to carry out simulation experiments, quantitative evaluation of the reconstructed image with respect to the LR images to improve the actual resolution of multiple. Simulation results show that the proposed method can reduce the edge blur of the reconstructed image, and the actual resolution is greatly improved compared with the traditional convex set projection method.