Title :
Optimal determination of regularization parameters and the stabilizing operator
Author :
Leung, C.M. ; Lu, W.-S.
Author_Institution :
Dept. of Electr. & Comput. Eng., Victoria Univ., BC, Canada
Abstract :
The aim of image restoration is to make an estimate of a degraded image as good as possible. The Tikhonov (1964) regularization approach has long been utilized for restoring images that are contaminated by noise and are blurred due for example to camera defocusing or linear motion. It is posed as a least-squares approximation problem in the l 2 space that provides a parameterized tradeoff between accuracy and smoothness of the restored image. Several methods of choosing the regularization parameter and the stabilizing operator are proposed via optimization approach
Keywords :
image restoration; least squares approximations; optimisation; stability; Tikhonov regularization approach; blurred images; camera defocusing; degraded image; image restoration; least-squares approximation problem; linear motion; noise contaminated image; optimization approach; regularization parameters; stabilizing operator; Additive white noise; Cameras; Constraint optimization; Degradation; Ear; Frequency locked loops; Image restoration; Laplace equations; Optimization methods; Pollution measurement;
Conference_Titel :
Communications, Computers, and Signal Processing, 1995. Proceedings., IEEE Pacific Rim Conference on
Conference_Location :
Victoria, BC
Print_ISBN :
0-7803-2553-2
DOI :
10.1109/PACRIM.1995.519554
