Orthographic stereo correlator on the terrain model for Apollo metric images

Authors:
Taemin Kim;Kyle Husmann;Zachary Moratto;Ara V. Nefian
Affiliations:
NASA Ames Research Center, Moffett Field, CA;NASA Ames Research Center, Moffett Field, CA;NASA Ames Research Center, Moffett Field, CA;NASA Ames Research Center, Moffett Field, CA and Carnegie Mellon University
Venue:
ISVC'11 Proceedings of the 7th international conference on Advances in visual computing - Volume Part I
Year:
2011

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Abstract

A stereo correlation method on the object domain is proposed to generate the accurate and dense Digital Elevation Models (DEMs) from lunar orbital imagery. The NASA Ames Intelligent Robotics Group (IRG) aims to produce high-quality terrain reconstructions of the Moon from Apollo Metric Camera (AMC) data. In particular, IRG makes use of a stereo vision process, the Ames Stereo Pipeline (ASP), to automatically generate DEMs from consecutive AMC image pairs. Given camera parameters of an image pair from bundle adjustment in ASP, a correlation window is defined on the terrain with the predefined surface normal of a post rather than image domain. The squared error of back-projected images on the local terrain is minimized with respect to the post elevation. This single dimensional optimization is solved efficiently and improves the accuracy of the elevation estimate.