Surface compression using over-determined Laplacian approximation

Zhongyi Xie; W. Randolph Franklin; Barbara Cutler; Marcus A. Andrade; Metin Inanc; Daniel M. Tracy

doi:10.1117/12.741224

21 September 2007 Surface compression using over-determined Laplacian approximation

Zhongyi Xie, W. Randolph Franklin, Barbara Cutler, Marcus A. Andrade, Metin Inanc, Daniel M. Tracy

Author Affiliations +

Proceedings Volume 6697, Advanced Signal Processing Algorithms, Architectures, and Implementations XVII; 66970F (2007) https://doi.org/10.1117/12.741224
Event: Optical Engineering + Applications, 2007, San Diego, California, United States

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.

Citation Download Citation

Zhongyi Xie, W. Randolph Franklin, Barbara Cutler, Marcus A. Andrade, Metin Inanc, and Daniel M. Tracy "Surface compression using over-determined Laplacian approximation", Proc. SPIE 6697, Advanced Signal Processing Algorithms, Architectures, and Implementations XVII, 66970F (21 September 2007); https://doi.org/10.1117/12.741224

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