In this paper we introduce a new MAP-based super-resolution method

which can effectively preserve image edges by using an improved directional image prior model.The proposed image prior model

which we refer to as a weighted directional Markov image prior model

utilizes different weights for different directional smoothness measures of the edge pixels.Definitely

larger weights are chosen for smooth measures along the edge in order to penalize them to a larger extent and smaller weights are chosen for smooth measures across the edge for a less penalization.Thus

the edges of the reconstructed HR image can be effectively persevered.The proposed algorithm is tested on different series of images.The experimental results indicate that the proposed algorithm has considerable effectiveness in terms of both objective measurements and visual evaluation.