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Bayesian depth map interpolation using edge driven Markov Random Fields

In this work we present a Bayesian interpolation procedure to perform depth map upsampling. The depth map prior is designed via an edge driven Markov Random Field. The upsampling procedure is computationally efficient and outperforms selected state of the art upsampling procedure; moreover it allows to perform depth map upsampling even without the reference high resolution luminance map.