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

Vitaly P. Fralenko

Program Systems:
Theory and Applications

ISSN 2079-3316

12+

Bilingual electronic scientific Electronic scientific journal of the Ailamazyan Program System Institute of the Ailamazyan PSI of PSI of Russian Academy of Science of RAS

Volume 14 (2023) . Issue 2 (57) . Paper No. 1 (427)

Artificial intelligence and machine learning

Research Article

DOI

10.25209/2079-3316-2023-14-2-3-26

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

Vitaly Petrovich Fralenko

	Ailamazyan Program Systems Institute of RAS, Ves'kovo, Russia
	alarmod@pereslavl.ru

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. (Linked article texts in Russian and in English).

Keywords: UAV, deconvolution, stabilization, real time, experimental data

MSC-2020

68T07; 68T40, 68U10 MSC-2020 68-XX: Computer science
MSC-2020 68Txx: Artificial intelligence
MSC-2020 68T07: Artificial neural networks and deep learning
MSC-2020 68T07: Artificial neural networks and deep learning
MSC-2020 68Txx: Artificial intelligence
MSC-2020 68T40: Artificial intelligence for robotics

MSC-2020 68-XX: Computer science
MSC-2020 68Txx: Artificial intelligence
MSC-2020 68T07: Artificial neural networks and deep learning
MSC-2020 68T07: Artificial neural networks and deep learning
MSC-2020 68Txx: Artificial intelligence
MSC-2020 68T40: Artificial intelligence for robotics

Acknowledgments: This work was financially supported by the Russian Science Foundation, project 21-71-10056

For citation: Vitaly P. Fralenko. Improving quality of video stream from the unmanned aerial vehicle technical vision system. Program Systems: Theory and Applications, 2023, 14:2, pp. 3–26. (In Russ., in Engl.). https://psta.psiras.ru/2023/2_3-26.

Full text of article (PDF): https://psta.psiras.ru/read/psta2023_2_3-26.pdf.

The article was submitted 11.03.2023; approved after reviewing 23.03.2023; accepted for publication 28.03.2023; published online 07.07.2023.

2023

Editorial address: Ailamazyan Program Systems Institute of the Russian Academy of Sciences, Peter the First Street 4«a», Veskovo village, Pereslavl area, Yaroslavl region, 152021 Russia; Phone: +7(4852) 695-228; E-mail: ; Website: http://psta.psiras.ru