Main Article Content

Oleksandr Tymochko
Volodymyr Larin
Maksym Kolmykov
Oleksander Timochko
Vladislava Pavlenko


It is known that human eyes are less sensitive to color, than to their brightness. In the RGB color space, all three components are considered equally important, and they are usually stored with the same resolution. However, you can display a color image more efficiently, separating the brightness from color information and presenting it with a higher resolution than color. RGB space is well suited for computer graphics, because it uses these three components for color formation. However, RGB space is not very effective when it comes to real images. The fact is that to save the color of an image, you need to know and store all three components of the RGB, and if one of them is missing, it will greatly distort the visual image representation. Also, when processing images in RGB space, it is not always convenient to perform any pixel conversion, because, in this case, it will be necessary to list all three values of the RGB component and write back. This greatly reduces the performance of various image processing algorithms. For these and other reasons, many video standards use brightness and two signals that carry information about the red and blue components of the signal, as a color model other than RGB. The most famous among such spaces is YCbCr.

Article Details

Information systems research
Author Biographies

Oleksandr Tymochko, Ivan Kozhedub Kharkiv National Air Force University, Kharkiv

Doctor of Technical Sciences, Professor, Department Professor

Volodymyr Larin, Ivan Kozhedub Kharkiv National Air Force University, Kharkiv

Candidate of Technical Sciences, Associate Professor of Mathematical and Software ACS Department

Maksym Kolmykov, Ivan Kozhedub Kharkiv National Air Force University, Kharkiv

Candidate of Technical Sciences, Senior Researcher, doctoral student, Air Force Science center

Oleksander Timochko, Kreditech Holding, Hamburg

Expert Quality Assurance Engineer

Vladislava Pavlenko, V. N. Karazin Kharkiv National University, Kharkiv



Yevseiev, S., Ahmed Abdalla, Osiievskyi, S., Larin, V. and Lytvynenko, M. (2020), “Development of an advanced method of video information resource compression in navigation and traffic control systems”, EUREKA: Physics and Engineering, No. 5, pp. 31–42, DOI:

Mashtalir, S., Mikhnova, O. and Stolbovyi, M. (2018), “Sequence Matching for Content-Based Video Retrieval”, Proceedings of the 2018 IEEE 2nd International Conference on Data Stream Mining and Processing, DSMP, art. no. 8478597, pp. 549–553, DOI:

Ruban, I., Smelyakov, K., Vitalii, M., Dmitry, P. and Bolohova, N. (2018), “Method of neural network recognition of ground-based air objects”, Proceedings of 2018 IEEE 9th International Conference on Dependable Systems, Services and Technologies, DESSERT, pp. 589-592.

Sumtsov, D. Osiievskyi, S. and Lebediev, V. (2018), “Development of a method for the experimental estimation of multimedia data flow rate in a computer network”, Eastern-European Journal of Enterprise Technologies, Vol. 2, Is. 2-92, pp. 56-64, DOI:

Pavlenko, M., Kolmykov, M., Tymochko, O., Khmelevskiy, S. and Larin, V. (2020), “Conceptual Basis of Cascading Differential Masking Technology”, 2020 IEEE 11th International Conference on Dependable Systems, Services and Technologies (DESSERT), DOI:

Hubbard, T. and Bor, R. (2016), Aviation Mental Health: Psychological Implications for Air Transportation, Routledge, London, 376 p.

Tyurin, V., Martyniuk, O., Mirnenko, V., Open’ko, P. and Korenivska, I. (2019), “General Approach to Counter Unmanned Aerial Vehicles”, 2019 IEEE 5th International Conference Actual Problems of Unmanned Aerial Vehicles Developments (APUAVD), DOI:

Mistry, D., Modi, P., Deokule, K., Patel, A., Patki, H. and Abuzaghleh, O. (2016), “Network traffic measurement and analysis”, 2016 IEEE Long Island Systems, Applications and Technology Conference (LISAT), DOI:

Tkachov, V.M., Tokariev V.V., Radchenko V.O. and Lebediev V.O. (2017), “The Problem of Big Data Transmission in the Mobile "Multi-Copter – Sensor Network" System”, Control, Navigation and Communication Systems, Is. 2, pp. 154–157.

Mistry, D., Modi, P., Deokule, K., Patel, A., Patki, H. and Abuzaghleh, O. (2016), “Network traffic measurement and analysis”, 2016 IEEE Long Island Systems (LISAT), DOI:

Kharchenko N., Tristan, A. and Kharchenko N. (2014), “The Problem Aspect of Control of Bit Speed of the Video Stream in Telecommunication Networks”, International Conference TCSET’2014 [“Modern problems of radio engineering, telecommunications, and computer science”], Lviv-Slavske, Ukraine, February 25 – March 1, 2014, pp. 533–534.

Donets, V., Kuchuk, N. and Shmatkov, S. (2018), “Development of software of e-learning information system synthesis modeling process”, Advanced Information Systems, Vol. 2, No 2, pp. 117–121, DOI:

Wang, S., Zhang, X., Liu, X., Zhang, J., Ma, S. and Gao, W. (2017), “Utility-Driven Adaptive Preprocessing for Screen Content Video Compression”, IEEE Transactions on Multimedia, 19 (3), art. no. 7736114, pp. 660-667.

Pavlenko, M., Timochko, A., Korolyuk, N. and Gusak, M. (2014), “Hybrid model of knowledge for situation recognition in airspace”, Automatic Control and Computer Sciences, Vol. 48, Is. 5, pp. 257-263.

Taylor, S.E. (2015), Health psychology, McGraw-Hill Education, New York, 430 р.

Popovskiy, V.V., Saburova, S.O., Oliynik, V.F., Losev, Yu.I. and Ageev, D.V. (2006), Matematichni osnovi teoriyi telekomunikatsiynih system, SMIT, Kharkiv, 564 р.

Pavlenko, M.A. (2012), “Metody i procedury otbora operatorov ASU pri ispol'zovanii intellektual'nyh sistem podderzhki prinyatiya reshenij”, Zbіrnik naukovih prac HUPS, No. 4 (33), pp. 171–177.

Kharchenko, V. and Mukhina, M. (2014), “Correlation-extreme visual navigation of unmanned aircraft systems based on speed-up robust features”, Aviation, Vol. 18, Is. 2, pp. 80–85, DOI:

Brown, T.A. (2015), Confirmatory factor analysis for applied research, Guilford Press, New York, 462 р.

Gonzales, R.C. and Woods, R.E. (2002), Digital image processing, Prentice Inc. Upper Saddle River, New Jersey, 779 p.

Ericsson, K.A., Charness, N., Feltovich, P.J. and Hoffman, R.R. (2018), The Cambridge handbook of expertise and expert performance, Cambridge University Press, New York, 918 р.

Wickens, C.D. (2015), Engineering psychology and human performance, Psychology Press, New York, 544 р.

Li, L. (2015), “The UAV intelligent inspection of transmission lines”, Proceedings of the 2015 International Conference on Advances in Mechanical Engineering and Industrial Informatics, DOI:

Carter M.W. and Price, C.C. (2017), Operations research: a practical introduction, Boca Raton, CRC Press, FL, 416 р.

Fletcher, R. (2017), Practical methods of optimization, John Wiley & Sons, New York, 456 р.

Larin, V., Yeromina, N., Petrov, S., Tantsiura, A. and Iasechko, M (2018), “Formation of reference images and decision function in radiometric correlation-extremal navigation systems”, Eastern-European Journal of Enterprise Technologies, Vol. 4, Is. 9, pp. 27-35, DOI:

Qassim, H., Verma, A. and Feinzimer, D. (2018), “Compressed residual-VGG16 CNN model for big data places image recognition”, 2018 IEEE 8th Annual Computing and Communication Workshop and Conference (CCWC), DOI:

Merlac, V., Smatkov, S., Kuchuk, N. and Nechausov A. (2018), “Resourses Distribution Method of University e-learning on the Hypercovergent platform”, Сonf. Proc. of 2018 IEEE 9th International Conference on Dependable Systems, Service and Technologies. DESSERT’2018, Ukraine, Kyiv, May 24-27, pp. 136-140, DOI: 10.1109/DESSERT.2018.8409114

Larin, V., Yerema, D. and Bolotska, Y. (2019), “The reasoning of necessity enhancing video privacy in conditions of providing the quality of the video information service provided in virtual infocommunication systems”, Sistemi ozbroennya i viyskova tehnika, Vol, 2(35), pp. 158–162.