An iterative method for the evaluation of the regularization parameter in regularized image restoration

Abstract

Regularized restoration is one of the powerful image restoration techniques because it preserves image details with a high degree of fidelity in the restored image. The main problem encountered in regularized image restoration is the evaluation of the regularization parameter. There are several methods for the evaluation of this parameter which require knowledge of the noise variance in the degraded image. After evaluating this parameter, regularized restoration is implemented by applying a regularization filter on the degraded image. In this paper, we propose a new iterative method for the evaluation of this parameter. This method depends on the maximization of the power in the restored image by the coincidence of the passband of the regularization filter with the frequency band in which, most of the image power exists. The suggested method doesn’t require a priori knowledge of the noise variance. Results show that the estimated value of the regularization parameter leads to a minimum mean square restoration error.