Data characterization for hyperspectral image compression

Rulon E. Simmons; Bernard V. Brower; John R. Schott

doi:10.1117/12.278946

19 September 1997 Data characterization for hyperspectral image compression

Rulon E. Simmons, Bernard V. Brower, John R. Schott

Proceedings Volume 3119, Multispectral Imaging for Terrestrial Applications II; (1997) https://doi.org/10.1117/12.278946
Event: Optical Science, Engineering and Instrumentation '97, 1997, San Diego, CA, United States

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.

Citation Download Citation

Rulon E. Simmons, Bernard V. Brower, and John R. Schott "Data characterization for hyperspectral image compression", Proc. SPIE 3119, Multispectral Imaging for Terrestrial Applications II, (19 September 1997); https://doi.org/10.1117/12.278946

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