A Regularized Mixed Norm Multi-Channel Image Restoration Algorithm 


Vol. 29,  No. 2, pp. 272-282, Feb.  2004


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  Abstract

This paper introduces a regularized mixed norm multi-channel image restoration algorithm using both within- and between- channel deterministic information. For each channel a functional which 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 defining the degree of smoothness of the solution, where both parameters are updated at each iteration according to the noise characteristics of each channel. The novelty or the proposed algorithm is that no knowledge of the noise distribution for each channel is required and that the parameters mentioned above are adjusted based on the partially restored image.

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  Cite this article

[IEEE Style]

M. Hong, Y. Shin, W. C. Lee, "A Regularized Mixed Norm Multi-Channel Image Restoration Algorithm," The Journal of Korean Institute of Communications and Information Sciences, vol. 29, no. 2, pp. 272-282, 2004. DOI: .

[ACM Style]

Min-Cheol Hong, Yoan Shin, and Won Chul Lee. 2004. A Regularized Mixed Norm Multi-Channel Image Restoration Algorithm. The Journal of Korean Institute of Communications and Information Sciences, 29, 2, (2004), 272-282. DOI: .

[KICS Style]

Min-Cheol Hong, Yoan Shin, Won Chul Lee, "A Regularized Mixed Norm Multi-Channel Image Restoration Algorithm," The Journal of Korean Institute of Communications and Information Sciences, vol. 29, no. 2, pp. 272-282, 2. 2004.

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pISSN : 1226 - 4717
eISSN : 2287 - 3880