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Sparse terrain pyramids
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Geographic Information Systems archive
Proceedings of the 16th ACM SIGSPATIAL international conference on Advances in geographic information systems table of contents
Irvine, California
SESSION: Terrain and road network algorithms table of contents
Article No. 15  
Year of Publication: 2008
ISBN:978-1-60558-323-5
Authors
Kenneth Weiss  University of Maryland, College Park, Maryland
Leila De Floriani  University of Genova, Genova, Italy
Sponsors
: Google
: Oak Ridge National Laboratory
: ESRI
Microsoft : Microsoft
Publisher
ACM  New York, NY, USA
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ABSTRACT

Bintrees based on longest edge bisection and hierarchies of diamonds are popular multiresolution techniques on regularly sampled terrain datasets. In this work, we consider Sparse Terrain Pyramids as a compact multiresolution representation for terrain datasets whose samples are a subset of those lying on a regular grid. While previous diamond-based approaches can efficiently represent meshes built on a complete grid of resolution (2k +1)2, this is not suitable when the field values are uniform in large areas or simply non-existent. We explore properties of diamonds to simplify an encoding of the implicit dependency relationship between diamonds. Additionally, we introduce a diamond clustering technique to further reduce the geometric and topological overhead of such representations. We demonstrate the coherence of our clustering technique as well as the compactness of our representation.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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Collaborative Colleagues:
Kenneth Weiss: colleagues
Leila De Floriani: colleagues