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Proceedings Paper

Hyperspectral analysis and target detection system for the Adaptive Spectral Reconnaissance Program (ASRP)
Author(s): John M. Grossmann; Jeffrey H. Bowles; Daniel Haas; John A. Antoniades; Mitchell R. Grunes; Peter J. Palmadesso; David Gillis; Kwok Yeung Tsang; Mark M. Baumback; Mark Daniel; John Fisher; Ioana A. Triandaf
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Paper Abstract

A multiprocessor version of the ORASIS hyperspectral analysis program has been implemented in support of the ASRP. In brief, the long-term technical objectives of the ASRP are to demonstrate the feasibility and military utility of real-time target detection from uncrewed air vehicles using hyperspectral data. This paper presents a preliminary assessment of ORASIS performance and describes the ORASIS development effort designed to meet the ASRP goals. Real-time performance of the analysis program and its potential effectiveness as a target detection method are demonstrated.

Paper Details

Date Published: 2 July 1998
PDF: 12 pages
Proc. SPIE 3372, Algorithms for Multispectral and Hyperspectral Imagery IV, (2 July 1998); doi: 10.1117/12.312591
Show Author Affiliations
John M. Grossmann, Naval Research Lab. (United States)
Jeffrey H. Bowles, Naval Research Lab. (United States)
Daniel Haas, Naval Research Lab. (United States)
John A. Antoniades, Naval Research Lab. (United States)
Mitchell R. Grunes, Falcon Research Inc. (United States)
Peter J. Palmadesso, Naval Research Lab. (United States)
David Gillis, National Research Council Associate (United States)
Kwok Yeung Tsang, Science Applications International Corp. (United States)
Mark M. Baumback, Naval Research Lab. (United States)
Mark Daniel, Science Applications International Corp. (United States)
John Fisher, Naval Research Lab. (United States)
Ioana A. Triandaf, Naval Research Lab. (United States)


Published in SPIE Proceedings Vol. 3372:
Algorithms for Multispectral and Hyperspectral Imagery IV
Sylvia S. Shen; Michael R. Descour, Editor(s)

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