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Proceedings Paper

New results from the ORASIS/NEMO compression algorithm
Author(s): Jeffrey H. Bowles; Dean Clamons; David Gillis; Peter J. Palmadesso; John A. Antoniades; Mark M. Baumback; Mark Daniel; John M. Grossmann; Daniel Haas; Jeffrey G. Skibo
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Paper Abstract

We present results from an improved ORASIS (Optical Real-time Adaptive Spectral Identification System) hyperspectral-data compression-algorithm that is being implemented on the Naval EarthMap Observer (NEMO) satellite. The algorithm is shown to produce results that are statistically improved from previous findings. To augment the statistical testing, the re-inflated data are run through analysis programs such as unsupervised classification. ORASIS compression is a series of algorithms. The first algorithm, the exemplar selector process (ESP), is a variation of Learned Vector Quantization (LVQ) that builds up a relatively small set of spectra to represent the full data set. Subsequent algorithms find approximate endmembers for the exemplar set and project the set into the space defined by the endmembers. Both the ESP and the projection process contribute to the compression of the data. The obtainable compression ratios vary with scene content and other factors but ratios between 10:1 and 30:1 are possible. The compressed data format is designed to allow direct access to individual pieces of the data without reinflation of the entire data set. Details of the hardware implementation of the Imagery On-Board Processor (IOBP) of NEMO is discussed, as well as the use of the compressed data on the ground.

Paper Details

Date Published: 27 October 1999
PDF: 9 pages
Proc. SPIE 3753, Imaging Spectrometry V, (27 October 1999);
Show Author Affiliations
Jeffrey H. Bowles, Naval Research Lab. (United States)
Dean Clamons, Naval Research Lab. (United States)
David Gillis, Naval Research Lab. (United States)
Peter J. Palmadesso, Naval Research Lab. (United States)
John A. Antoniades, Naval Research Lab. (United States)
Mark M. Baumback, Naval Research Lab. (United States)
Mark Daniel, Naval Research Lab. (United States)
John M. Grossmann, Naval Research Lab. (United States)
Daniel Haas, Naval Research Lab. (United States)
Jeffrey G. Skibo, Naval Research Lab. (United States)

Published in SPIE Proceedings Vol. 3753:
Imaging Spectrometry V
Michael R. Descour; Sylvia S. Shen, Editor(s)

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