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Proceedings Paper

Surface compression using over-determined Laplacian approximation
Author(s): Zhongyi Xie; W. Randolph Franklin; Barbara Cutler; Marcus A. Andrade; Metin Inanc; Daniel M. Tracy
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Paper Abstract

We describe a surface compression technique to lossily compress elevation datasets. Our approach first approximates the uncompressed terrain using an over-determined system of linear equations based on the Laplacian partial differential equation. Then the approximation is refined with respect to the uncompressed terrain using an error metric. These two steps work alternately until we find an approximation that is good enough. We then further compress the result to achieve a better overall compression ratio. We present experiments and measurements using different metrics and our method gives convincing results.

Paper Details

Date Published: 21 September 2007
PDF: 12 pages
Proc. SPIE 6697, Advanced Signal Processing Algorithms, Architectures, and Implementations XVII, 66970F (21 September 2007); doi: 10.1117/12.741224
Show Author Affiliations
Zhongyi Xie, Rensselaer Polytechnic Institute (United States)
W. Randolph Franklin, Rensselaer Polytechnic Institute (United States)
Barbara Cutler, Rensselaer Polytechnic Institute (United States)
Marcus A. Andrade, Rensselaer Polytechnic Institute (United States)
Univ. Federal de Viçosa (Brazil)
Metin Inanc, Rensselaer Polytechnic Institute (United States)
Daniel M. Tracy, Rensselaer Polytechnic Institute (United States)

Published in SPIE Proceedings Vol. 6697:
Advanced Signal Processing Algorithms, Architectures, and Implementations XVII
Franklin T. Luk, Editor(s)

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