Tohru ISHIZAKA and Junji MAEDA

Department of Computer Science and Systems Engineering, Muroran Institute of Technology, Muroran, 050 Japan

(Accepted October 5, 1994)

In this paper, we describe blur identification and restoration of noisy degraded images. The point-spread function (PSF) can be characterized by the quantity of blur. Thus the blur identification problem can be solved as a parameter estimation problem. The estimation method is a generalized cross-validation (GCV) criterion that is known as a powerful measure that can be used to choose the optimal regularization parameter without a priori knowledge about noise. We use the iterative damped-least squares (DLS) algorithm which is based on the principle of damped least-squares for restoring noisy degraded images.

Key words : blur identification, image restoration, GCV, damped least-squares method, PSF