Methods for choosing the regularization parameter and estimating the noise variance in image restoration and their relation

Author

Galatsanos, Nikolas P. ; Katsaggelos, Aggelos K.

Author_Institution

Dept. of Electr. & Comput. Eng., Illinois Inst. of Technol., Chicago, IL, USA

Volume

1

Issue

3

fYear

1992

fDate

7/1/1992 12:00:00 AM

Firstpage

322

Lastpage

336

Abstract

The application of regularization to ill-conditioned problems necessitates the choice of a regularization parameter which trades fidelity to the data with smoothness of the solution. The value of the regularization parameter depends on the variance of the noise in the data. The problem of choosing the regularization parameter and estimating the noise variance in image restoration is examined. An error analysis based on an objective mean-square-error (MSE) criterion is used to motivate regularization. Two approaches for choosing the regularization parameter and estimating the noise variance are proposed. The proposed and existing methods are compared and their relationship to linear minimum-mean-square-error filtering is examined. Experiments are presented that verify the theoretical results

Keywords

noise; parameter estimation; picture processing; error analysis; image restoration; linear minimum-mean-square-error filtering; noise variance estimation; regularization parameter; Additive noise; Degradation; Eigenvalues and eigenfunctions; Equations; Error analysis; Filtering; Image restoration; Mean square error methods; Nonlinear filters; Parameter estimation;

fLanguage

English

Journal_Title

Image Processing, IEEE Transactions on

Publisher

ieee

ISSN

1057-7149

Type

jour

DOI

10.1109/83.148606

Filename

148606