Optimal reconstruction of approximate planar surfaces using photometric stereo

Photometric stereo can be used to obtain a fast and noncontact surface reconstruction of Lambertian surfaces. Despite several published works concerning the uncertainties and optimal light configurations of photometric stereo, no solutions for optimal surface reconstruction from noisy real images have been proposed. In this paper, optimal surface reconstruction methods for approximate planar textured surfaces using photometric stereo are derived, given that the statistics of imaging errors are measurable. Simulated and real surfaces are experimentally studied, and the results validate that the proposed approaches improve the surface reconstruction especially for the high-frequency height variations.