3D super-resolution using generalized sampling expansion
Hassan Shekarforoush, Marc-Antoine Berthod, Josiane B. Zerubia · Proceedings - International Conference on Image Processing · 2002
Using a set of low resolution images it is possible to reconstruct high resolution information by merging low resolution data on a finer grid. A 3D super-resolution algorithm is proposed, based on a probabilistic interpretation of the n-dimensional version of Papoulis' (1977) 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.