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Neumann-Pearson-optimized algorithms for estimating white Gaussian pulse noise on images

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Abstract

Statistically optimal algorithms using the Neumann-Pearson criterion for estimating the spatial position of pulse noise with a white Gaussian brightness distribution on images have been synthesized, consisting of minimizing the pass-noise probability at a given false-alarm probability and the false-alarm probability at a fixed pass level. Results are presented for numerical studies of the synthesized algorithms, indicating their advantages over known nonoptimal algorithms.

© 2009 Optical Society of America

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