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This article is cited in 3 scientific papers (total in 3 papers)
IMAGE PROCESSING, PATTERN RECOGNITION
An algorithm for segmentation of aerosol inhomogeneities
P. A. Filimonova, M. L. Belovb, Yu. V. Fedotovb, S. E. Ivanovb, V. A. Gorodnichevb a Graduate school of Bauman Moscow State Technical University, Moscow, Russia
b Research Institute of Radioelectronics and Laser Technologies of Bauman Moscow State Technical University, Moscow, Russia
Abstract:
We have developed an algorithm for segmentation of aerosol inhomogeneities in the registered field of lidar signal fluctuations in the atmosphere in the "Range – Time" coordinates that is based on a sliding window of a two-dimensional autocorrelation function. The obtained algorithm allows us to robustly detect aerosol inhomogeneities, which can be used in practical applications to study aerosol fields in the atmosphere and improve the accuracy of estimating the speed and direction of winds. The developed method was applied for obtaining a histogram of aerosol inhomogeneity-size distribution from 355-nm elastic lidar measurements data in the surface layer.
Keywords:
digital image processing, lidar, aerosol inhomogeneities, surface laye.
Received: 14.03.2018 Accepted: 12.05.2018
Citation:
P. A. Filimonov, M. L. Belov, Yu. V. Fedotov, S. E. Ivanov, V. A. Gorodnichev, “An algorithm for segmentation of aerosol inhomogeneities”, Computer Optics, 42:6 (2018), 1062–1067
Linking options:
https://www.mathnet.ru/eng/co592 https://www.mathnet.ru/eng/co/v42/i6/p1062
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