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A comparative study of lossless compression algorithms on MODIS data
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Paper Abstract

This paper reports a comparative study of lossless compression algorithms for MODIS data. MODIS, The Moderate Resolution Imaging Spectroradiometer, is a 36 band Visible and IR multispectral imager aboard the Terra and Aqua satellites, having spatial resolution ranging from 0.250 to 1 kilometer and spectral resolution ranging from 0.405 -0.420 to 4.482-4.549 microns. MODIS data rates are 10.6 Mbps (peak daytime); and 6.1 Mbps (orbital average). Faced with such an enormous volume of data on a current generation imager, this study provides a comparison of current compression algorithms as a baseline for future work. The Hierarchical Data Format (HDF) is standard format selected for data archiving and distribution within the Earth Observing System Data and Information System (EOSDIS). Currently this system handles over one terabyte of data daily, and this volume continues to increase over time. With growing satellite Earth science multispectral imager volume data compression, it becomes increasingly important to evaluate which compression algorithms are most appropriate for data management in transmission and archiving. This comparative compression study uses a wide range standard implementations of the leading lossless compression algorithms. Examples include image compression algorithms such as PNG and JPEG2000, and widely-used file compression formats such as BZIP2 and 7z. This study includes a comparison with the Consultative Committee for Space Data Systems (CCSDS) most recent recommended compression standard. by a significant margin.

Paper Details

Date Published: 19 September 2007
PDF: 10 pages
Proc. SPIE 6683, Satellite Data Compression, Communications, and Archiving III, 66830F (19 September 2007); doi: 10.1117/12.736771
Show Author Affiliations
Srikanth Gottipati, CCNY, NOAA/CREST (United States)
Jamal Goddard, CCNY, NOAA/CREST (United States)
Michael Grossberg, CCNY, NOAA/CREST (United States)
Irina Gladkova, CCNY, NOAA/CREST (United States)

Published in SPIE Proceedings Vol. 6683:
Satellite Data Compression, Communications, and Archiving III
Roger W. Heymann; Bormin Huang; Irina Gladkova, Editor(s)

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