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Program Systems: Theory and Applications, 2023, Volume 14, Issue 2, Pages 3–26
DOI: https://doi.org/10.25209/2079-3316-2023-14-2-3-26 (Mi ps420) 		 
Artificial Intelligence, Intelligent Systems, Neural Networks

Improving quality of video stream from the unmanned aerial vehicle technical vision system

V. P. Fralenko

Ailamazyan Program Systems Institute of RAS, Ves’kovo, Russia
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DOI: https://doi.org/10.25209/2079-3316-2023-14-2-3-26
Abstract: The study contains the results of work on the software and hardware complex to improve the quality of video data obtained from unmanned aerial vehicles. Including the tasks of independent video-flow images deconvolution (motion blur removal) and stabilization of the video stream using machine learning and artificial intelligence methods. Analytical and practical results are presented that allowed to choose solutions for processing data from UAVs in real time.
Key words and phrases: UAV, deconvolution, stabilization, real time, experimental data.
Funding agency Grant number
Russian Science Foundation 21-71-10056
This work was financially supported by the Russian Science Foundation, project 21-71-10056.
Received: 11.03.2023
Accepted: 28.03.2023
Document Type: Article
UDC: 004.42: 004.896
BBC: 32.813.53
MSC: Primary 68T07; Secondary 68T40, 68U10
Language: Russian and English
Citation: V. P. Fralenko, “Improving quality of video stream from the unmanned aerial vehicle technical vision system”, Program Systems: Theory and Applications, 14:2 (2023), 3–26
Citation in format AMSBIB
\Bibitem{Fra23}
\by V.~P.~Fralenko
\paper Improving quality of video stream from the unmanned aerial vehicle technical vision system
\jour Program Systems: Theory and Applications
\yr 2023
\vol 14
\issue 2
\pages 3--26
\mathnet{http://mi.mathnet.ru/ps420}
\crossref{https://doi.org/10.25209/2079-3316-2023-14-2-3-26}
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