Abstract: In this work we introduce Markov cross entropic priors in the Bayesian restoration and fusion of laser range images. These cross entropic priors are used to model smoothness of the surfaces and linearity of the discontinuities. The priors are defined over a pair of coupled Markov random fields representing the corresponding pixel and line processes. Gibbsian maximum a posteriori estimates are then found using simulated annealing. Range image data are discussed, and results are presented for synthetic range images. !16
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