Document Type

Article - Open Access

Publication Title

SIGSPATIAL Special

Publisher

Association for Computing Machinery

Publication Date

11-2010

Abstract/ Summary

This paper describes a 3D environmental data compression technique for oceanographic datasets. With proper point selection, our method approximates uncompressed marine data using an over-determined system of linear equations based on, but essentially different from, the Laplacian partial differential equation. Then this approximation is refined via an error metric. These two steps work alternatively until a predefined satisfying approximation is found. Using several different datasets and metrics, we demonstrate that our method has an excellent compression ratio. To further evaluate our method, we compare it with 3D-SPIHT. 3D-ODETLAP averages 20% better compression than 3D-SPIHT on our eight test datasets, from World Ocean Atlas 2005. Our method provides up to approximately six times better compression on datasets with relatively small variance. Meanwhile, with the same approximate mean error, we demonstrate a significantly smaller maximum error compared to 3D-SPIHT and provide a feature to keep the maximum error under a user-defined limit.

Publisher Statement

Green Open Access Otherwise known as "Self-Archiving" or "Posting Rights", all ACM published authors retain the right to post the pre-submitted (also known as "pre-prints"), submitted, accepted, and peer-reviewed versions of their work in any and all of the following sites: Author's Homepage Author's Institutional Repository Any Repository legally mandated by the agency or funder funding the research on which the work is based Any Non-Commercial Repository or Aggregation that does not duplicate ACM tables of contents. Non-Commercial Repositories are defined as Repositories owned by non-profit organizations that do not charge a fee to access deposited articles and that do not sell advertising or otherwise profit from serving scholarly articles

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