A METHOD TO APPROACH OPTIMAL RESTORATION IN IMAGE RESTORATION PROBLEMS WITHOUT NOISE ENERGY INFORMATION

摘要

This paper proposes a new image restoration technique, in which the resultingregularized image approximates the optimal solution steadily. The affect of the regular-ization operator and parameter on the lower band and upper band energy of the residueof the regularized image is theoretically analyzed by employing wavelet transform. Thispaper shows that regularization operator should generally be lowstop and highpass. So thispaper chooses a lowstop and highpass operator as regularization operator, and constructan optimization model which minimizes the mean squares residue of reg ularized solutionto determine regularization parameter. Although the model is random, on the conditionof this paper, it can be solved and yields regularization parameter and regularized solu-tion. Otherwise, the technique has a mechanism to predict noise energy. So, without noiseinformation, it can also work and yield good restoration results.