TY - GEN
T1 - Geometrical interpretation of the adaptive coherence estimator for hyperspectral target detection
AU - Bar, Shahar
AU - Bass, Ori
AU - Volfman, Alon
AU - Dallal, Tomer
AU - Rotman, Stanley R.
PY - 2013/8/12
Y1 - 2013/8/12
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=84881143083&partnerID=8YFLogxK
U2 - 10.1117/12.2006472
DO - 10.1117/12.2006472
M3 - Conference contribution
AN - SCOPUS:84881143083
SN - 9780819495341
T3 - Proceedings of SPIE - The International Society for Optical Engineering
BT - Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XIX
T2 - Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XIX
Y2 - 29 April 2013 through 2 May 2013
ER -