Bayesian multichannel image restoration using compound Gauss-Markov random fields

@article{Molina2003BayesianMI,
  title={Bayesian multichannel image restoration using compound Gauss-Markov random fields},
  author={Rafael Molina and Javier Mateos and Aggelos K. Katsaggelos and Miguel Vega},
  journal={IEEE transactions on image processing : a publication of the IEEE Signal Processing Society},
  year={2003},
  volume={12 12},
  pages={1642-54}
}
In this paper, we develop a multichannel image restoration algorithm using compound Gauss-Markov random fields (CGMRF) models. The line process in the CGMRF allows the channels to share important information regarding the objects present in the scene. In order to estimate the underlying multichannel image, two new iterative algorithms are presented and their convergence is established. They can be considered as extensions of the classical simulated annealing and iterative conditional methods… CONTINUE READING
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References

Publications referenced by this paper.
Showing 1-10 of 30 references

Multichannel image restoration in Astronomy,”Vistas Astron

  • R. Molina, J. Mateos
  • vol. 41,
  • 1997
Highly Influential
6 Excerpts

Color imaging for digital cameras with a single CCD sensor

  • X. Zhang, Y. Obuchi, T. Kambe, N. N. Kubo, I. Suzuki
  • Proc. 26th Annu. Conf. IEEE Industrial…
  • 2000
1 Excerpt

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