Image Restoration Based on Constrained Total Least Squares
Abstract
In constrained total least squares algorithm (CTLS), the selection of a minimal algebraic set of linearly independent random variables to express the noise matrix ?C is an important task. In this paper, A fast algorithm is provided using the possibly dependent random variables set. We showed that it can be viewed as a combination of Mesarovic et al' s CTLS method and RLS method when the noise is Gaussian. Our experimental study indicated that our algorithm has better visual and objective quality, while having a much lower computation cost. Moreover, our algorithm can also handle a more general noise model.
Conference Title
2004 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING, VOL III, PROCEEDINGS
Volume
3
Copyright Statement
© 2004 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.