1995 Volume 1995 Pages 101-106
In this paper, we propose a method of image restoration based on the simulated annealing(SA) [1],[2], and the wavelet representation(WR)[3]. In the past two decades, there has been much research activity in developing image processing for restoration of two-dimensional noisy images based upon statistical methods. Geman-Geman proposed the Baysian restoration of images based on simulated annealing(SA)[2]. But their restoration method has very slow convergence for getting the MAP(Maximum A Posteiriori) estimate and requires a very large computational cost. To overcome such shortage of their method, we propose here a new method that restores a degraded image based on the Gibbs distribution and the WR. In this method, we compute a WR of a degraded image and obtain the MAP estimate from the WR.
