Title :
3D super-resolution using generalized sampling expansion
Author :
Shekarforoush, H. ; Berthod, M. ; Zerubia, J.
Author_Institution :
Inst. Nat. de Recherche en Inf. et Autom., Sophia Antipolis, France
Abstract :
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
Keywords :
Bayes methods; Markov processes; image reconstruction; image resolution; image sampling; random processes; 3D superresolution algorithm; Bayesian framework; Lambertian surface; Markov random fields; generalized sampling expansion; generalized sampling theorem; height map; high resolution information; image reconstruction; image resolution; low resolution images; probabilistic interpretation; Bayesian methods; Cost function; Image reconstruction; Image resolution; Image sampling; Iterative algorithms; Markov random fields; Merging; Sampling methods; Surface reconstruction;
Conference_Titel :
Image Processing, 1995. Proceedings., International Conference on
Conference_Location :
Washington, DC
Print_ISBN :
0-8186-7310-9
DOI :
10.1109/ICIP.1995.537474
