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Proceedings Paper

Image chain assessment for feature extraction
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Paper Abstract

It is shown that the image chain has important effects upon the quality of feature extraction. Exact analytic ROC results are given for the case where arbitrary multivariate normal imagery is passed to a Bayesian feature detector designed for multivariate normal imagery with a diagonal covariance matrix. Plots are provided to allow direct visual inspection of many of the more readly apparent effects. Also shown is an analytic tradeoff that says doubling background contrast is equal to halving sensor to scene distance or sensor noise. It is also shown that the results provide a lower bound to the ROC of a Bayesian feature detector designed for arbitrary multivariate normal distributions.

Paper Details

Date Published: 8 August 2003
PDF: 8 pages
Proc. SPIE 5108, Visual Information Processing XII, (8 August 2003); doi: 10.1117/12.487029
Show Author Affiliations
Rufus H. Cofer, Florida Institute of Technology (United States)
Samuel Peter Kozaitis, Florida Institute of Technology (United States)

Published in SPIE Proceedings Vol. 5108:
Visual Information Processing XII
Zeno J. Geradts; Zia-ur Rahman; Lenny I. Rudin; Robert A. Schowengerdt; Stephen E. Reichenbach, Editor(s)

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