Regularized mixed norm multichannel image restoration approach

M. Ch Hong*, T. Stathaki, A. K. Katsaggelos

*Corresponding author for this work

Research output: Contribution to conferencePaperpeer-review

Abstract

In this paper, we develop a deterministic regularized mixed norm multichannel image restoration algorithm. A functional which combines the least mean squares (LMS), the least mean fourth (LMF), and a smoothing functional using both within- and between-channel deterministic information is proposed. One parameter is defined to control the relative contribution between the LMS and the LMF norms, and a second one (regularization parameter) is defined to control the degree of smoothness of the solution. They are both updated at each iteration step. The novelty of the proposed algorithm is that no knowledge about the noise distribution for each channel is required, and the parameters are adjusted based on the partially restored image.

Original languageEnglish (US)
Pages220-223
Number of pages4
StatePublished - Dec 1 1998
EventProceedings of the 1998 9th IEEE SP Workshop on Statistical Signal and Array Processing - Portland, OR, USA
Duration: Sep 14 1998Sep 16 1998

Other

OtherProceedings of the 1998 9th IEEE SP Workshop on Statistical Signal and Array Processing
CityPortland, OR, USA
Period9/14/989/16/98

ASJC Scopus subject areas

  • Engineering(all)

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