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Machine Learning Methods for the Analysis of Turbulence- and Extinction-Degraded Imagery

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Abstract

Machine learning methods improve performance of a novel atmospheric parameter estimation algorithm for characterizing local atmospheric propagation channel optical turbulence, extinction, and scattering. Results of lab experiment, field test, and wave-optics propagation simulations are presented.

© 2014 Optical Society of America

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