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Proceedings Paper

Comparison of band selection results using different class separation measures in various day and night conditions
Author(s): Dan Sheffer; Yigal Ultchin
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Paper Abstract

A comparison of the spectral bands recommended through employment of different data separation measures and the reliability and robustness of these measures was performed on artificially generated target and background IR radiance data sets. The Mahalanobis distance, Signal to Clutter Ratio, Bhattacharya distance and Informational Difference criteria were employed in order to obtain the best single and paired spectral bands for data separation between two data classes of 'targets' and 'backgrounds' in day and night conditions. The results show that for conditions in which there is a distinct temperature difference between the two data classes, all the criteria perform similarly, with only small differences in the recommended spectral bands and general performance. However, in daylight conditions with multiple types of backgrounds and targets, criteria based on the assumption of concentrated data classes (SCR, Mahalanobis) tend to provide contradictory results, while those based on general statistical principles (Bhattacharya, Informational Difference) produce unequivocal results that are relatively unaffected by data set complexity.

Paper Details

Date Published: 23 September 2003
PDF: 10 pages
Proc. SPIE 5093, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery IX, (23 September 2003); doi: 10.1117/12.497002
Show Author Affiliations
Dan Sheffer, Institute for Advanced Research and Development (Israel)
Yigal Ultchin, Institute for Advanced Research and Development (Israel)

Published in SPIE Proceedings Vol. 5093:
Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery IX
Sylvia S. Shen; Paul E. Lewis, Editor(s)

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