DocumentCode
1500912
Title
Identification and restoration of noisy blurred images using the expectation-maximization algorithm
Author
Lagendijk, Reginald L. ; Biemond, Jan ; Boekee, Dick E.
Author_Institution
Dept. of Electr. Eng., Delft Univ. of Technol., Netherlands
Volume
38
Issue
7
fYear
1990
fDate
7/1/1990 12:00:00 AM
Firstpage
1180
Lastpage
1191
Abstract
A maximum-likelihood approach to the blur identification problem is presented. The expectation-maximization algorithm is proposed to optimize the nonlinear likelihood function in an efficient way. In order to improve the performance of the identification algorithm, low-order parametric image and blur models are incorporated into the identification method. The resulting iterative technique simultaneously identifies and restores noisy blurred images
Keywords
iterative methods; parameter estimation; picture processing; blur identification; blur models; expectation-maximization algorithm; image identification; image restoration; iterative technique; maximum-likelihood approach; noisy blurred images; nonlinear likelihood function; parametric image models; Autoregressive processes; Biomedical imaging; Costs; Degradation; Expectation-maximization algorithms; Filters; Image restoration; Iterative algorithms; Linear systems; Maximum likelihood estimation;
fLanguage
English
Journal_Title
Acoustics, Speech and Signal Processing, IEEE Transactions on
Publisher
ieee
ISSN
0096-3518
Type
jour
DOI
10.1109/29.57545
Filename
57545
Link To Document