Accelerating Convergence of Iterative Image Restoration Algorithms

Iterative methods are often used for applications in science and engineering to solve very large scale linear systems. Efficiency of an iterative method depends on the amount of computation needed per iteration, as well as on the number of iterations needed to reconstruct the desired approximate solution. Convergence speed can be accelerated using a technique called preconditioning. Although preconditioning is used in many applications, its use in image restoration has been limited. This paper describes a technique for preconditioning iterative image restoration algorithms. A particular conjugate gradient type iterative method with Tikhonov regularization is used to illustrate the effectiveness of the preconditioning scheme. Discussion of MATLAB software implementing the methods is also provided.