Share Email Print
cover

Proceedings Paper

Geometrical interpretation of the adaptive coherence estimator for hyperspectral target detection
Author(s): Shahar Bar; Ori Bass; Alon Volfman; Tomer Dallal; Stanley R. Rotman
Format Member Price Non-Member Price
PDF $14.40 $18.00

Paper Abstract

A hyperspectral cube consists of a set of images taken at numerous wavelengths. Hyperspectral image data analysis uses each material’s distinctive patterns of reflection, absorption and emission of electromagnetic energy at specific wavelengths for classification or detection tasks. Because of the size of the hyperspectral cube, data reduction is definitely advantageous; when doing this, one wishes to maintain high performances with the least number of bands. Obviously in such a case, the choice of the bands will be critical. In this paper, we will consider one particular algorithm, the adaptive coherence estimator (ACE) for the detection of point targets. We give a quantitative interpretation of the dependence of the algorithm on the number and identity of the bands that have been chosen. Results on simulated data will be presented.

Paper Details

Date Published: 18 May 2013
PDF: 8 pages
Proc. SPIE 8743, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XIX, 87430K (18 May 2013); doi: 10.1117/12.2006472
Show Author Affiliations
Shahar Bar, Ben-Gurion Univ. of the Negev (Israel)
Ori Bass, Ben-Gurion Univ. of the Negev (Israel)
Alon Volfman, Ben-Gurion Univ. of the Negev (Israel)
Tomer Dallal, Ben-Gurion Univ. of the Negev (Israel)
Stanley R. Rotman, Ben-Gurion Univ. of the Negev (Israel)


Published in SPIE Proceedings Vol. 8743:
Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XIX
Sylvia S. Shen; Paul E. Lewis, Editor(s)

© SPIE. Terms of Use
Back to Top