2D leapfrog algorithm for optimal surface reconstruction
Lyle Noakes, Ryszard Kozera · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1999
In this paper we present an iterative algorithm computing a global optimum for a large system of linear equations enforcing the so-called integrability condition for a given noisy non-integrable vector field. The algorithm will be applied to Photometric Stereo shape reconstruction. The scheme in question (a 2-D Leap-Frog Algorithm) relies neither on a prior knowledge of boundary conditions nor on other global constraints imposed on the so-far derived gradient integration techniques for noise-contaminated data. The proposed algorithm is an improvement of the recently developed Lawn-Mowing Algorithm, which computes a suboptimal solution to the above mentioned problem. The backbone of the proposed algorithm is a generalization of the 1-D Leap-Frog Algorithm derived for finding geodesic joining two points on a Riemannian manifold. The discussion is supplemented by examples illustrating the performance of the 2-D Leap-Frog Algorithm.© (1999) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.