We describe a MAP-based method for constructing a high resolution image from the noisy undersampled multiframes. Using the aliasing relationship between the high resolution image and the undersampled frames, we develop the algorithms for the reconstruction problem, appropriate for the case where all images are taken under similar conditions. The Bayesian approach uses Laplacian operator to model a neighbor correlation on estimated image. The results of experiments show dramatic improvement in the spatial resolution.