Iterative regularized mixed norm multichannel image restoration

Min-Cheol Hong; Tania Stathaki; Aggelos K. Katsaggelos

doi:10.1117/1.1867452

1 January 2005 Iterative regularized mixed norm multichannel image restoration

Min-Cheol Hong, Tania Stathaki, Aggelos K. Katsaggelos

Author Affiliations +

Journal of Electronic Imaging, Vol. 14, Issue 1, 013004 (January 2005). https://doi.org/10.1117/1.1867452

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.

©(2005) Society of Photo-Optical Instrumentation Engineers (SPIE)

Citation Download Citation

Min-Cheol Hong, Tania Stathaki, and Aggelos K. Katsaggelos "Iterative regularized mixed norm multichannel image restoration," Journal of Electronic Imaging 14(1), 013004 (1 January 2005). https://doi.org/10.1117/1.1867452

Published: 1 January 2005

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