Share Email Print

Proceedings Paper

Three-dimensional compression of mesoscale meteorological data based on JPEG 2000
Author(s): Sergio D. Cabrera
Format Member Price Non-Member Price
PDF $17.00 $21.00

Paper Abstract

Computer modeling programs such as the Battlescale Forecast Model are capable of generating three-dimensional (3-D) Meteorological (Met) data with sufficiently fine spatial resolution to warrant a study of data compression methods for efficient storage and/or transmission of this data. This paper illustrates the potential benefits of applying lossy/irreversible data compression techniques to such Met variables as air pressure. Because of the advanced state of development of digital image compression methods such as the JPEG 2000 algorithm which is already an international standard, the approach considered and illustrated in this paper uses the two-dimensional (2-D), single-component JPEG 2000 algorithm on horizontal 2-D slices of data. Much better results are obtained by first pre-processing the 3-D data in the vertical direction by applying a one-dimensional, energy compacting, reversible linear transformation. The best possible pre-processing which involves the Karhunen-Loeve Transform which is shown to increases compression ratios for the same signal-to-noise ration (SNR) by a factor of 10 over the 2-D (no pre-processing) approach. Alternatively, for the same bit rate, the SNR is improved by up to 40 dB.

Paper Details

Date Published: 6 August 2002
PDF: 12 pages
Proc. SPIE 4741, Battlespace Digitization and Network-Centric Warfare II, (6 August 2002); doi: 10.1117/12.478718
Show Author Affiliations
Sergio D. Cabrera, Univ. of Texas/El Paso (United States)

Published in SPIE Proceedings Vol. 4741:
Battlespace Digitization and Network-Centric Warfare II
Raja Suresh; William E. Roper; William E. Roper, Editor(s)

© SPIE. Terms of Use
Back to Top
Sign in to read the full article
Create a free SPIE account to get access to
premium articles and original research
Forgot your username?