Sub-pixel Bayesian estimation of albedo and height |
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Authors: | Hassan Shekarforoush Marc Berthod Josiane Zerubia Michael Werman |
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Affiliation: | (1) INRIA, 2004 Route des Lucioles, 06902 Sophia Antipolis Cedex, France;(2) Institute of Computer Science, Hebrew University of Jerusalem, 91904 Jerusalem, Israel |
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Abstract: | 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.This project was partially supported by AFIRST (l'Association Franco-Israelienne pour la Recherche en Science et en Technologie). |
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