Sub-pixel bayesian estimation of albedo and height

Hassan Shekarforoush*, Marc Berthod, Josiane Zerubia, Michael Werman

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

31 Scopus citations


Given a set of low resolution camera images of a Lambertian surface, it is possible to reconstruct high resolution luminance and height information, when the relative displacements of the image frames are known. We have proposed iterative algorithms for recovering high resolution albedo with the knowledge of high resolution height and vice versa. The problem of surface reconstruction has been tackled in a Bayesian framework and has been formulated as one of minimizing an error function. Markov Random Fields (MRF) have been employed to characterize the a priori constraints on the solution space. As for the surface height, we have attempted a direct computation without refering to surface orientations, while increasing the resolution by camera jittering.

Original languageAmerican English
Pages (from-to)289-300
Number of pages12
JournalInternational Journal of Computer Vision
Issue number3
StatePublished - 1996


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