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8 August 2003 Imagery chain assessment for feature extraction
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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.
© (2003) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Rufus H. Cofer and Samuel Peter Kozaitis "Imagery chain assessment for feature extraction", Proc. SPIE 5108, Visual Information Processing XII, (8 August 2003);

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