DocumentCode
3095376
Title
An iterative mixed norm image restoration algorithm
Author
Hong, Min-Cheol ; Stathaki, Tania ; Katsaggelos, Aggelos K.
Author_Institution
Dept. of Electr. Eng. & Comput. Sci., Northwestern Univ., Evanston, IL, USA
fYear
1997
fDate
21-23 Jul 1997
Firstpage
137
Lastpage
141
Abstract
In this paper, we propose an iterative mixed norm image restoration algorithm. A functional which combines the least mean squares (LMS) and the least mean fourth (LMF) functionals is proposed. A function of the kurtosis is used to determine the relative importance between the LMS and the LMF functionals. An iterative algorithm is utilized for obtaining a solution and its convergence is analyzed. Experimental results demonstrate the capability of the proposed approach
Keywords
convergence of numerical methods; functional equations; image restoration; iterative methods; least mean squares methods; LMF functionals; convergence; functional; iterative mixed norm image restoration algorithm; kurtosis; least mean fourth functionals; least mean squares; Adaptive filters; Additive noise; Algorithm design and analysis; Degradation; Gaussian distribution; Gaussian noise; Image restoration; Iterative algorithms; Least squares approximation; Signal processing algorithms;
fLanguage
English
Publisher
ieee
Conference_Titel
Higher-Order Statistics, 1997., Proceedings of the IEEE Signal Processing Workshop on
Conference_Location
Banff, Alta.
Print_ISBN
0-8186-8005-9
Type
conf
DOI
10.1109/HOST.1997.613503
Filename
613503
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