Technology of Sliding Coding of Uneven Diagonal Sequences in Two-Dimensional Spectral Space of Transformants




dynamic sequence of video frames, completeness and integrity of video information, time delay of information delivery, bit size reduction, transformant coding, diagonals, truncated positional numbers


The requirements for the qualitative characteristics of the remote form of video interaction are substantiated. These include the following: completeness and integrity of video information; timeliness of video information delivery, which is determined by the time of delay in information delivery. This includes the time spent on processing and transmission via information and communication networks. Based on a comprehensive analysis, it is shown that there is a contradiction in the process of meeting these requirements. On the one hand, it is driven by the need to increase the capacity of information and communication networks. This is driven by the rapid growth of the information intensity of the video stream and the complexity of its processing and analysis. On the other hand, the remote form of information interaction is characterized by the use of wireless information and communication technologies based on mobile aerospace and ground-based platforms. These technologies have insufficient capabilities in terms of speed characteristics of information transmission. Hence, improving the quality of video information services using the mobile segment of an information and communication network in crisis conditions is an urgent scientific and applied problem. It is shown that the localization of the imbalance between the growth rate of information load on infocommunication networks and their bandwidth is achieved by using standardized technologies for encoding and formatting video data. At the same time, standardized technologies have vulnerabilities. This concerns the dependence of the level of bit rate reduction on the amount of psycho-visual redundancy that is reduced during the coding process. It is thoroughly proved that the elimination of this vulnerability is achieved by improving standardized platforms. For this reason, it is proposed to develop coding methods that reduce the bit volume of video frames without losing their integrity. Therefore, the purpose of the research is to develop a method for reducing the bit intensity of the dynamic video stream based on the coding of their segments in two-dimensional spectral space. Accordingly, the article substantiates the concept of interpreting a transform based on establishing the presence of a combinatorial configuration, which is determined by its structural, topological and psychovisual features. The potential advantages of taking into account the combinatorial configuration of a transform based on its reformatting according to the uneven diagonal structure are shown. The development of a technology for sliding truncated positional coding of uneven diagonal sequences in the two-dimensional spectral space of a transform is presented. The application of the created technology in the process of encoding transformed video segments for a sequence of video frames allows to reduce their bit volume by an average of 15-30%. This takes into account the dependence on the class of video frame in the local group and the level of structural and semantic information content of video segments.



Dick K., Russell L., Dosso Y., Kwamena F., Green J. (2019). Deep Learning for Critical Infrastructure Resilience. Journal of Infrastructure Systems, Vol. 25, Iss. 2, 11 p. DOI: 10.1061/(ASCE)IS.1943-555X.0000477.

Li, F., Krivenko, S., Lukin, V. (2020). Two-step providing of desired quality in lossy image compression by SPIHT. Radioelectronic and computer systems, No. 2(94), pp. 22-32. DOI: 10.32620/reks.2020.2.02.

Ji, Sh., Tong, X., Zhang, M. (2012). Image encryption schemes for JPEG and GIF formats based on 3D baker with compound chaotic sequence generator. Cornell University arXiv. doi: 10.48550/arXiv.1208.0999.

Announcing the ADVANCED ENCRYPTION STANDARD (AES). Federal Information Processing Standards Publication 197 (2001). Defense Technical Information Center.

Information technology – JPEG 2000 image coding system: Secure JPEG 2000. International Standard ISO/IEC 15444-8; ITU-T Recommendation T.807. (2007). 108 p.

School of Electronic Engineering and Computer Science. ECS605U/ECS776P – Image Processing.

Belikova N., Lekakh A., Dovbenko O., Dodukh O. (2019). Method of Increasing the Capacity of Information Threat Detection Filters in Modern Information and Communication Systems. 3rd International Conference on Advanced Information and Communications Technologies (AICT), pp 426-429. DОІ: 10.1109/AIACT.2019.8847754.

Miano J. (1999). Compressed image file formats: JPEG, PNG, GIF, XBM, BMP. ACM Press/Addison-Wesley Publishing Co., 264 p.

Joint Photographic Experts Group (JPEG). Information technology – digital compression and coding of continuous-tone still images: Requirements and guidelines. ISO/IEC 10918-1:1994, ITU/CCITT Recommendation T.81. (1992–2017). 182 p.

Wong, K., Tanaka, K. (2010). DCT based scalable scrambling method with reversible data hiding functionality. 4th International Symposium on Communications, Control and Signal Processing (ISCCSP), pp. 1-4. DOI: 10.1109/ISCCSP.2010.5463307.

Cisco Visual Networking Index: Global Mobile Data Traffic Forecast Update, 2017–2022. (2019). Cisco. 33 p.

Cisco Annual Internet Report (2018–2023). (2020). Cisco. 35 p.

Komolov, D., Zhurbynskyy, D., Kulitsa, O. (2015). Selective Method For Hiding Of Video Information Resource In Telecommunication Systems Based On Encryption Of Energy-Significant Blocks Of Reference I-Frame. 1st International Conference on Advanced Information and Communication Technologies (AICT'2015), pp. 80-83.

Wong, K.-W. (2009). Image Encryption Using Chaotic Maps. In: Kocarev, L., Galias, Z., Lian, S. (eds) Intelligent Computing Based on Chaos. Studies in Computational Intelligence, Vol. 184. Springer. doi: 10.1007/978-3-540-95972-4_16.

Rippel O. and Bourdev L. (2017). Real-Time Adaptive Image Compression. Proceedings of the 34th International Conference on Machine Learning, Vol. 70, pages 2922-2930.

Yang Y., Zhu B., Li S., Yu N. (2007). Efficient and Syntax-Compliant JPEG 2000 Encryption Preserving Original Fine Granularity of Scalability. EURASIP Journal on Information Security, Vol. 2007, Iss. 1, 13 p. DOI:10.1186/1687-417X-2007-056365.

Ieremeiev, O., Lukin, V., Okarma, K. (2020). Combined visual quality metric of remote sensing images based on neural network. Radioelectronic and computer systems, No. 4, pp. 4-15. DOI: 10.32620/reks.2020.4.01.

Latif, A., Mehrnahad Z. (2019). A Novel Image Encryption Scheme Based on Reversible Cellular Automata. Journal of Electronic & Information Systems, Vol. 1, Iss. 1, pp. 18-25. DOI: 10.30564/jeisr.v1i1.1078.

Barannik V. (2022). Technology of Structural-Binomial Coding to Increase the Efficiency of the Functioning of Computer Systems. 2022 IEEE 4th International Conference on Advanced Trends in Information Theory (ATIT), Kyiv, Ukraine, pp. 96-100, doi: 10.1109/ATIT58178.2022.10024205.

Tverdokhlib V., Zakomorna K., Dvukhglavov D., Oleksin O., Zhuikov D., Kryvonos V. (2021). Technology Increasing Capacity Protected Channel Delivery Video Data Telecommunication Systems Critical Infrastructure. IEEE 3rd International Conference on Advanced Trends in Information Theory (ATIT), Kyiv, Ukraine, pp. 57-60. DOI: 10.1109/ATIT54053.2021.9678736.

Barannik V., Hahanova A., Slobodyanyuk A. (2009). Architectural presentation of isotopic levels of relief of images. 2009 ІЕЕЕ 10th International Conference on Experience of Designing and Application of CAD Systems in Microelectronics (CADSM): proceedings, Lviv, Ukraine, pp. 385–387.

Issa, O.; Shanableh, T. (2023). Static Video Summarization Using Video Coding Features with Frame-Level Temporal Subsampling and Deep Learning. Applied Sciences, Vol. 13, Iss. 10, 6065. doi: 10.3390/app13106065.

Gonzalez R., Woods R. (2018). Digital Image Processing. Pearson, 1168 p.

Salomon D. (2007). Data Compression: The Complete Reference. Springer, 1092 p.

Gore A, Gupta S. (2015). Full reference image quality metrics for JPEG compressed images. AEU – International Journal of Electronics and Communications, Vol. 69, Iss. 2, pp. 604–608. DOI: 10.1016/j.aeue.2014.09.002.

Cogranne R. (2018). Determining JPEG Image Standard Quality Factor from the Quantization Tables, 6 p. Cornell University.

Li, Y.; Zhu, H.; He, L.; Wang, D.; Shi, J.; Wang, J. (2023). Video Super-Resolution with Regional Focus for Recurrent Network. Applied Sciences, Vol. 13, Iss.1, 526. doi: 10.3390/app13010526.

Auer S., Bliem A., Engel D., et al. (2013). Bitstream-based JPEG Encryption in Real-time. International Journal of Digital Crime and Forensics, Vol. 5, No. 3. DOI: 10.4018/jdcf.2013070101.

Minemura K., Moayed Z., Wong K., et al. (2012). JPEG image scrambling without expansion in bitstream size. 2012 19th IEEE International Conference on Image Processing, pp. 261–264. DOI: 10.1109/ICIP.2012.6466845.

Barannik D. and Barannik V. (2022). Steganographic Coding Technology for Hiding Information in Infocommunication Systems of Critical Infrastructure. 2022 IEEE 4th International Conference on Advanced Trends in Information Theory (ATIT), pp. 88-91, doi: 10.1109/ATIT58178.2022.10024185.

Issa, O.; Shanableh, T. (2023). Video-Based Recognition of Human Activity Using Novel Feature Extraction Techniques. Applied Sciences, Vol. 13, Iss. 11, 6856. doi: 10.3390/app13116856.

Barannik V., Barannik N., Ignatyev О., Khimenko V. (2021). Method of indirect information hiding in the process of video compression. Radioelectronic and Computer Systems, No. 4, pp. 119–131. doi: 10.32620/reks.2021.4.

Barannik V., Shulgin S., Barannik N., and Barannik V. (2022). Method of Coding Subbands of Non-Homogeneous Spectrum of Video Segments in Uneven Diagonal Space. 2022 IEEE 4th International Conference on Advanced Trends in Information Theory (ATIT), pp. 72-75, doi: 10.1109/ATIT58178.2022.10024236.

Bidwe, R. V.; Mishra, S.; Patil, S.; et al. (2022). Deep Learning Approaches for Video Compression: A Bibliometric Analysis. Big Data Cogn. Comput., Vol. 6, Iss. 2, 44. doi: 10.3390/bdcc6020044.

Brand, F.; Seiler, J.; Kaup, A. (2021). Intra-frame coding using a conditional autoencoder. IEEE Journal of Selected Topics in Signal Processing, Vol. 15, Iss. 2, pp. 354–365. doi: 10.1109/JSTSP.2020.3034768.

Shulgin S., Barannik V., Barannik N. (2022). Dynamic Coding Method of Video Segments Stream by Specifying Structural Changes. 2022 IEEE 4th International Conference on Advanced Trends in Information Theory (ATIT), pp. 76-79, doi: 10.1109/ATIT58178.2022.10024179.



How to Cite

Бараннік , В. В., Шульгін , С. С., Бабенко , Ю. М., Онищенко , Р. С., Ревва , К. В., Белікова , Т. В. and Ігнатьєв , О. О. (2023) “Technology of Sliding Coding of Uneven Diagonal Sequences in Two-Dimensional Spectral Space of Transformants”, Visnyk NTUU KPI Seriia - Radiotekhnika Radioaparatobuduvannia, (94), pp. 13-23. doi: 10.20535/RADAP.2023.94.13-23.



Telecommunication, navigation, radar systems, radiooptics and electroacoustics