MAP Based Super-resolution Image Reconstruction Method

Super-resolution image reconstruction has been one of the most active research fields in recent years. In this paper, a new super-resolution algorithm is proposed to the problem of obtaining a high-resolution image from several low-resolution images that have been sub sampled. In the image registration, the paper puts forward an improved search strategies improving registration accuracy. In the MAP algorithm, the threshold parameters of solving the optimal value, making the estimated value of the optimal high-resolution images, so that the reconstructed image is better. The results of the experiments indicate that the proposed algorithm can not only make an automatic choice of the parameter and get the high resolution reconstruction image expected, but also can preserve the edges and details of the image effectively.