The theory of image degraded model and maximum a posteriori probability (MAP) are introduced in brief. Then the defect of the MAP, the constraints of the Gibbs term (the second term of the objective function) to pixels with different gradients unbalanced are analysed. Based on this defect, a modified MAP algorithm for reconstruction is presented. The gradient matrix gotten from the interpolated image of the low-resolution image to modify the Gibbs term is used, so that the constraints are balanced to some extent. Then the updated MAP objective function is minimized by conjugate gradient method and the modified algorithm is simulated. The results show that, compared with the original MAP algorithm, the modified MAP algorithm can keep details well, and control noise (generated in reconstruction process) greatly in the reconstruction, and the image quality is improved obviously. Meanwhile, the modified MAP algorithm is steady and convergent in solving the problem.