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Proceedings Paper

Real-time onboard hyperspectral-image compression system for a parallel push broom sensor
Author(s): Scott D. Briles
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Paper Abstract

For a dispersive hyperspectral imaging sensor, frames are continuously being generated with spatially continuous rows of differing spectral wavelengths. As the sensor advances in the direction of travel, a hyperspectral data cube can be constructed from adjacent frames. A hyperspectral sensor residing on a satellite would require either an extremely large bandwidth for the downlink or onboard data compression to transmit the majority of the data. This paper presents a compression algorithm and the implementation of the algorithm on a real-time computational architecture. The compression algorithm sues wavelet subband coding, and universal trellis code quantization. The full implementation algorithm might include differential pulse code modulation between spectral images. The computational implementation of the algorithm uses a real-time operating system and a single general-propose microprocessor upon a VME backplane. Tradeoffs between algorithm performance and computational burden are discussed. Performance of the algorithm is presented in terms root-mean-squared error and execution time. Quantitative results for the implementation of the algorithm are provided.

Paper Details

Date Published: 4 August 1997
PDF: 9 pages
Proc. SPIE 3071, Algorithms for Multispectral and Hyperspectral Imagery III, (4 August 1997); doi: 10.1117/12.280595
Show Author Affiliations
Scott D. Briles, Los Alamos National Lab. (United States)

Published in SPIE Proceedings Vol. 3071:
Algorithms for Multispectral and Hyperspectral Imagery III
A. Evan Iverson; Sylvia S. Shen, Editor(s)

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