Adaptively Choosing Regularization Operator by Using an Evolutionary Algorithm in Image Restoration

A new technique is proposed to choose regularization operator adaptively in order to get good image restoration Theoretical analysis and experiment indicate that the restoration is good when the residue energy distribution of restored image is uniform The uniformity is measured by minimizing the dispersion of every subband of the residue from the average energy which is a function of regularization operator Evolutionary algorithm is employed to solve the minimization problem, so as to choose regularization operator adaptively, while other optimal algorithms are helpless to do that Experiment results show that the regularization operator selected by using the new technique is good for image restoration