3D super-resolution using generalized sampling expansion

A 3D super-resolution algorithm is proposed below, based on a probabilistic interpretation of the ndimensional version of Papoulis' generalized sampling theorem. The algorithm is devised for recovering the albedo and the height map of a Lambertian surface in a Bayesian framework, using Markov Random Fields for modeling the a priori knowledge.

• Type: Conference
• Year: 1995
• Where: ICIP
• Authors: Hassan Shekarforoush, Marc Berthod, Josiane Zerubia
• Keywords: ICIP 1995, Image Processing, Markov Random Fields, Priori Knowledge, Probabilistic Interpretation