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Proceedings Paper

Data characterization for hyperspectral image compression
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Paper Abstract

By their very nature, hyperspectral imagers collect much more data per pixel than more traditional imaging systems. With bandwidth limitations on the communications channels and storage space, intelligent system design, band selection, and/or data compression will be very important. In two recent government-funded studies (completed in Dec. 1996), Kodak developed two preliminary compression options for hyperspectral imaging. As part of these studies, the band-to- band data correlation structures for both AVIRIS and HYDICE hyperspectral imaging systems were evaluated. Some surprising results were noted that have important implications to system designers.

Paper Details

Date Published: 19 September 1997
PDF: 12 pages
Proc. SPIE 3119, Multispectral Imaging for Terrestrial Applications II, (19 September 1997); doi: 10.1117/12.278946
Show Author Affiliations
Rulon E. Simmons, Eastman Kodak Co. (United States)
Bernard V. Brower, Eastman Kodak Co. (United States)
John R. Schott, Rochester Institute of Technology (United States)

Published in SPIE Proceedings Vol. 3119:
Multispectral Imaging for Terrestrial Applications II
Joan B. Lurie; Thomas Delaney, Editor(s)

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