Robust Mosaicking of Stereo Digital Elevation Models from the Ames Stereo Pipeline
- Author:
- Nefian, Ara Victor
- Published:
- October 29, 2010.
- Physical Description:
- 1 electronic document
- Additional Creators:
- Kim, Tae Min and Moratto, Zachary M.
- Access Online:
- hdl.handle.net
- Restrictions on Access:
- Unclassified, Unlimited, Publicly available.
- Summary:
- Robust estimation method is proposed to combine multiple observations and create consistent, accurate, dense Digital Elevation Models (DEMs) from lunar orbital imagery. The NASA Ames Intelligent Robotics Group (IRG) aims to produce higher-quality terrain reconstructions of the Moon from Apollo Metric Camera (AMC) data than is currently possible. In particular, IRG makes use of a stereo vision process, the Ames Stereo Pipeline (ASP), to automatically generate DEMs from consecutive AMC image pairs. However, the DEMs currently produced by the ASP often contain errors and inconsistencies due to image noise, shadows, etc. The proposed method addresses this problem by making use of multiple observations and by considering their goodness of fit to improve both the accuracy and robustness of the estimate. The stepwise regression method is applied to estimate the relaxed weight of each observation.
- Collection:
- NASA Technical Reports Server (NTRS) Collection.
- Note:
- Document ID: 20110013377., ARC-E-DAA-TN2436., and International Symposium on Visual Computing; 30 Nov. - Dec. 2, 2009; Las Vegas, NV; United States.
- Terms of Use and Reproduction:
- Copyright, Distribution under U.S. Government purpose rights.
- Access Online:
- hdl.handle.net
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