Paper
21 September 1992 Bayesian defeat of camouflage
Author Affiliations +
Abstract
A new technique is shown for refining and reducing incoming camouflage data based upon the Bayesian paradigm. Innovation is displayed in use of a statistical conditioning sequence that avoids the need to form target features from the data. The result is a simplified and more accurate probabilistic indication of actual target presence. This probabilistic indication can then be incorporated into a variety of target detection scenarios or, alternately, to form the basis of a theoretically optimal Bayesian target detector. Numeric simulation is presented to show the effectiveness of the technique against simulated camouflage.
© (1992) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Rufus H. Cofer "Bayesian defeat of camouflage", Proc. SPIE 1687, Characterization, Propagation, and Simulation of Sources and Backgrounds II, (21 September 1992); https://doi.org/10.1117/12.137863
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KEYWORDS
Target recognition

Camouflage

Target detection

Computer simulations

Sensors

Silicon

Image sensors

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