Design of interchannel MRF model for probabilistic multichannel image processing

  • Koo H
  • Cho N
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Abstract

In this paper, we present a novel framework that exploits an informative reference channel in the processing of another channel. We formulate the problem as a maximum a posteriori estimation problem considering a reference channel and develop a probabilistic model encoding the interchannel correlations based on Markov random fields. Interestingly, the proposed formulation results in an image-specific and region-specific linear filter for each site. The strength of filter response can also be controlled in order to transfer the structural information of a channel to the others. Experimental results on satellite image fusion and chrominance image interpolation with denoising show that our method provides improved subjective and objective performance compared with conventional approaches.

Author-supplied keywords

  • Chrominance denoising
  • Markov randiom field (MRF) model
  • chrominance interpolation
  • multichannel image processing
  • satellite image fusion

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Authors

  • Hyung Il Koo

  • Nam Ik Cho

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