Share Email Print

Journal of Electronic Imaging

Iterative regularized mixed norm multichannel image restoration
Author(s): Min-Cheol Hong; Tania Stathaki; Aggelos K. Katsaggelos
Format Member Price Non-Member Price
PDF $20.00 $25.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

We present a regularized mixed norm multichannel image restoration algorithm. The problem of multichannel restoration using both within- and between-channel deterministic information is considered. For each channel a functional that combines the least mean squares (LMS), the least mean fourth (LMF), and a smoothing functional is proposed. We introduce a mixed norm parameter that controls the relative contribution between the LMS and the LMF, and a regularization parameter that defines the degree of smoothness of the solution, both updated at each iteration according to the noise characteristics of each channel. The novelty of the proposed algorithm is that no knowledge of the noise distribution for each channel is required, and the parameters just mentioned are adjusted based on the partially restored image.

Paper Details

Date Published: 1 January 2005
PDF: 9 pages
J. Electron. Imaging. 14(1) 013004 doi: 10.1117/1.1867452
Published in: Journal of Electronic Imaging Volume 14, Issue 1
Show Author Affiliations
Min-Cheol Hong, Soongsil Univ. (South Korea)
Tania Stathaki, Imperial College of Science Technology & Medicine (United Kingdom)
Aggelos K. Katsaggelos, Northwestern Univ. (United States)

© SPIE. Terms of Use
Back to Top