Image chain assessment for feature extraction

Rufus H. Cofer; Samuel Peter Kozaitis

doi:10.1117/12.487029

8 August 2003 Imagery chain assessment for feature extraction

Proceedings Volume 5108, Visual Information Processing XII; (2003) https://doi.org/10.1117/12.487029
Event: AeroSense 2003, 2003, Orlando, Florida, United States

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.

Citation Download Citation

Rufus H. Cofer and Samuel Peter Kozaitis "Imagery chain assessment for feature extraction", Proc. SPIE 5108, Visual Information Processing XII, (8 August 2003); https://doi.org/10.1117/12.487029

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