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

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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.

About the authors

Vitaly Petrovich Fralenko

Ailamazyan Program Systems Institute of RAS

Author for correspondence.
Email: alarmod@pereslavl.ru
ORCID iD: 0000-0003-0123-3773
PhD, Leading Researcher at RCMS Ailamazyan Program Systems Institute. The field of scientific interests: intellectual data analysis and images recognition, artificial intelligence and decision making, parallel-conveyor computing, network security, diagnosis of complex technical systems, graphic interfaces.

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