In this paper, we present a method to obtain the restored image from the degrated image which applies the Gibbs distribution. Geman-Geman[1] proposed the Bayesian restoration of images based on the Simulated Annealing (SA). Their restoration method has a merit that can obtain the well-restored image. On the other hand, it has demerits which are a very slow convergence and a requirement of large computational cost, to get the Maximum A Posteriori(MAP) estimate of the original image from the degraded image. For overcoming such disadvantage of their method, we propose a deterministic rule of updating estimated gray levels of pixels and edge (line) elements based on a new energy function. Finally, we perform some simulations using real image data to show the feasibility of our method.