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.
| Original language | English (US) |
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| Pages | 137-141 |
| Number of pages | 5 |
| State | Published - Jan 1 1997 |
| Event | Proceedings of the 1997 IEEE Signal Processing Workshop on Higher-Order Statistics, SPW-HOS - Banff, Can Duration: Jul 21 1997 → Jul 23 1997 |
Other
| Other | Proceedings of the 1997 IEEE Signal Processing Workshop on Higher-Order Statistics, SPW-HOS |
|---|---|
| City | Banff, Can |
| Period | 7/21/97 → 7/23/97 |
ASJC Scopus subject areas
- Signal Processing