Paper Info
Title
3D Lunar Terrain Reconstruction from Apollo Images
Abstract
Generating accurate three dimensional planetary models is becoming increasingly important as NASA plans manned missions to return to the Moon in the next decade. This paper describes a 3D surface reconstruction system called the Ames Stereo Pipeline that is designed to produce such models automatically by processing orbital stereo imagery. We discuss two important core aspects of this system: (1) refinement of satellite station positions and pose estimates through least squares bundle adjustment; and (2) a stochastic plane fitting algorithm that generalizes the Lucas-Kanade method for optimal matching between stereo pair images.. These techniques allow us to automatically produce seamless, highly accurate digital elevation models from multiple stereo image pairs while significantly reducing the influence of image noise. Our technique is demonstrated on a set of 71 high resolution scanned images from the Apollo 15 mission.
Year
DOI
Venue
2009
10.1007/978-3-642-10331-5_66
ISVC (1)
Keywords
Field
DocType
apollo images,orbital stereo imagery,image noise,stereo pair image,ames stereo pipeline,lucas-kanade method,accurate digital elevation model,important core aspect,scanned image,multiple stereo image pair,surface reconstruction system,lunar terrain reconstruction,pose estimation,surface reconstruction,high resolution,three dimensional,bundle adjustment,lucas kanade,stochastic processes,least square,terrain,digital elevation model,algorithms
Least squares,Surface reconstruction,Computer vision,Satellite,Optimal matching,Bundle adjustment,Computer science,Terrain,Digital elevation model,Image noise,Artificial intelligence
Conference
Volume
ISSN
Citations 
5875
0302-9743
6
PageRank 
References 
Authors
0.56
10
6
Name
Order
Citations
PageRank
Michael J. Broxton160.56
Ara V. Nefian275156.08
Zachary Moratto371.94
Taemn Kim438228.18
Michael Lundy560.56
Aleksandr V. Segal6492.57