关键词: Regularization method, image restoration, wavelet transform

Abstract:

This paper proposes a new image restoration technique, in which the resulting
regularized 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 residue
of the regularized image is theoretically analyzed by employing wavelet transform. This
paper shows that regularization operator should generally be lowstop and highpass. So this
paper chooses a lowstop and highpass operator as regularization operator, and construct
an optimization model which minimizes the mean squares residue of regularized solution
to determine regularization parameter. Although the model is random, on the condition
of 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 noise
information, it can also work and yield good restoration results.

Key words: Regularization method, image restoration, wavelet transform