Bayesian multichannel image restoration using compound Gauss-Markov random fields.
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. Experimental results with color images demonstrate the effectiveness of the proposed approaches.
Molina
Rafael
R
Departamento de Ciencias de la Computación e I.A. Universidad de Granada, 18071 Granada, Spain. rms@decsai.ugr.es
Mateos
Javier
J
Katsaggelos
Aggelos K
AK
Vega
Miguel
M