Video Segments Stamping Method Saving Their Reliability in the Spectral-Cluster Space




remote video service, timeliness and reliability of video information, compression of aerial images, structural clusters, number of series of units, spectral space


An analysis of the peculiarities of the organization of video information support for critical infrastructure management systems is carried out. It is shown that the requirements for the completeness, timeliness and reliability of the delivery of video information are growing. The growth of demand for the organization of remote video services using technological platforms based on unmanned aerial systems (UAVs) is shown. At the same time, it requires compliance with the requirements of a number of international standards, which are put forward for the quality of providing video information. In turn, such requirements encourage the use of telecommunication systems (TCS) with the necessary level of information transmission speed. There is an imbalance for systems providing remote video services using wireless TCS on aviation platforms. It refers to the lagging of the rate of growth of TCS productivity in terms of data transfer rate relative to the rate of growth of the bit intensity of video information streams that are formed on board the UAVs. The article shows that the consequences of imbalance are the appearance of significant time delays in the process of video information delivery. Accordingly, there are losses: relevance (adequacy) of video information regarding the current state of monitoring objects; the reliability of video information. These destructions are the reason for the disruption of the decision-making process in critical infrastructure systems. Therefore, there is an urgent need to solve a scientific and applied problem, which concerns the improvement of the quality of providing remote video services using telecommunication technologies on the platform UAVs. A set of technological solutions is used to solve this problem. The main component here is the application of technologies for reducing the bit intensity of the video stream. At the same time, as shown in the article, in the process of developing such technologies, it is necessary to resolve the contradiction. It consists in the fact that the amount of psychovisual redundancy of video images is used both to localize the destructive effect of channel errors on the reliability of video images and to reduce their bit volume. Therefore, there is a contradiction between the requirements for ensuring the authenticity of video images and their timely delivery. Therefore, the implementation of remote video services using onboard TCS in the presence of interference puts forward additional requirements for technologies to reduce the bit volume of video data. Therefore, the purpose of the article is to create methods for compressing video images to reduce their bit volume while ensuring the required reliability. On the basis of a comprehensive analysis, directions for improvement of coding methods are substantiated. They concern the following aspects. First. Identification of new regularities, the consideration of which will create conditions for additional reduction of the bit volume of video segments without introducing losses regarding the reliability of the information. It will allow us to localize the destructive effect of channel errors in the process of reconstruction of video images with damaged codegrams of their compact description. Second. Form code constructions using the mode of uniform or locally uniform code formation. In accordance with this, the efficiency of encoding transformed video segments in the cluster space is substantiated. At the same time, clustering is carried out according to such a feature as the number of series of units in the binary description of their components. It is claimed that conditions are created for the clustered transformant to further reduce the amount of redundancy without a loss of information. A method of video segment compression has been developed to ensure their reliability in the spectral-cluster space. This technology is based on the principle of the duality of transformant components. It consists in the fact that the clustered component can simultaneously be considered as an element of the statistical space of the cluster and a valid structural cluster element. That is, as one of the permissible permutations with repetitions with a certain number of series of units. According to the results of experimental studies, it can be stated that when using the created method for the given levels, an increase in the level of compression compared to existing methods is achieved by an average of 40%.



JPEG Privacy & Security Abstract and Executive Summary, 2015., accessed 7.04.2021.

Barannik, V., Sidchenko S., Barannik N., Barannik V. (2021). Development of the method for encoding service data in cryptocompression image representation systems. Eastern-European Journal of Enterprise Technologies, Vol. 3, No. 9(111), pp. 112-124. DOI: 10.15587/1729-4061.2021.235521.

DSTU 7624:2014: Information Technology. Cryptographic protection of information. Symmetric block transformation algorithm [DSTU 7624:2014: Informatsiini tekhnolohii. Kryptohrafichnyi zakhyst informatsii. Alhorytm symetrychnoho blokovoho peretvorennia]. Ministry of Economic Development of Ukraine, 2015. 39 p.

Data Encryption Standard (DES), Federal Information Processing Standards Publication 46-3, 1999. 26 p.

Barannik V., Barannik N., Ignatyev O., Khimenko V. (2021). Method of indirect information hiding in the process of video compression. Radioelectronic and Computer Systems, №. 4, pp. 119–131. DOI: 10.32620/reks.2021.4.10.

Rivest, R., Shamir, A., Adleman, L. (1978). A method for obtaining digital signatures and public-key cryptosystems. Communications of the ACM, Vol. 21, Iss. 2, pp. 120-126. DOI: 10.1145/359340.359342.

Chen, T.-H., Wu, Ch.-S. (2011). Efficient multi-secret image sharing based on Boolean operation. Signal Processing, Vol. 91, Iss. 1, pp. 90-97. DOI: 10.1016/j.sigpro.2010.06.012.

Barannik, V., Shulgin, S., Krasnorutsky, A., Slobodyanyuk, O., Gurzhii, P., Korolyova, N. (2020). Methodological Fundamentals of Deciphering Coding of Aerophotography Segments on Special Equipment of Unmanned Complex. IEEE 2 nd International Conference on Advanced Trends in Information Theory (IEEE ATIT 2020), pp. 38-43. DOI: 10.1109/ATIT50783.2020.9349257.

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.

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.

Naor, M., Shamir, A. (1994). Visual Cryptography. Proceedings of the Advances in Cryptology. EUROCRYPT’94. Lecture Notes in Computer Science, Vol. 950, pp. 1–12. DOI: 10.1007/bfb0053419.

Wu, Yu., Agaian, S., Noonan, J. (2012). Sudoku Associated Two Dimensional Bijections for Image Scrambling. IEEE Transactions on multimedia, available at: Cornell University arXiv, 30 p. doi: 10.48550/arXiv.1207.5856.

Tsai, Ch.-L., Chen, Ch.-J., Hsu, W.-L. (2012). Multi-morphological image data hiding based on the application of Rubik's cubic algorithm. IEEE International Carnahan Conference on Security Technology (ICCST), pp. 135-139. DOI: 10.1109/CCST.2012.6393548.

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, pp. 333–354, Springer. DOI: 10.1007/978-3-540-95972-4_16.

Cheng, P., Yang, H., Wei, P., Zhang, W. (2015). A fast image encryption algorithm based on chaotic map and lookup table. Nonlinear Dynamics, Vol. 79, Iss. 3, pp. 2121-2131. DOI: 10.1007/s11071-014-1798-y.

Guesmi, R., Farah, M. A. B., Kachouri, A., Samet, M. (2016). A novel chaos-based image encryption using DNA sequence operation and Secure Hash Algorithm SHA-2. Nonlinear Dynamics, Vol. 83, Iss. 3, pp. 1123-1136. DOI: 10.1007/s11071-015-2392-7.

Kurihara, K., Watanabe O., Kiya, H. (2016). An encryption-then-compression system for JPEG XR standard. IEEE International Symposium on Broadband Multimedia Systems and Broadcasting (BMSB), pp. 1-5. DOI: 10.1109/BMSB.2016.7521997.

Sharma, R., Bollavarapu, S. (2015). Data Security using Compression and Cryptography Techniques. International Journal of Computer Applications, Vol. 117, No. 14, pp. 15-18. DOI: 10.5120/20621-3342.

Zhou, J., Liu, X., Au, O. C., Tang, Y. Y. (2014). Designing an Efficient Image Encryption-Then-Compression System via Prediction Error Clustering and Random Permutation. IEEE Transactions on Information Forensics and Security, Vol. 9, No. 1, pp. 39-50. DOI: 10.1109/TIFS.2013.2291625.

Dufaux, F., Ebrahimi, T. (2006). Toward a Secure JPEG. Applications of Digital Image Processing XXIX, Vol. 6312, pp. 1–8. DOI: 10.1117/12.686963.

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

Wu, Y., Noonan, J. P., Agaian, S. ( 2011). NPCR and UACI Randomness Tests for Image Encryption. Cyber Journals: Multidisciplinary Journals in Science and Technology, Journal of Selected Areas in Telecommunications (JSAT), Vol. 2, pp. 31-38. DOI: 10.4236/jss.2015.33005.

Farajallah, M. (2015). Chaos-based crypto and joint crypto-compression systems for images and videos. HAL science ouverte.

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.

Yang, Y., Zhu, B., Li, S., Yu, N. (2008). Efficient and Syntax-Compliant JPEG 2000 Encryption Preserving Original Fine Granularity of Scalability. EURASIP Journal on Information Security, Vol. 2007, pp. 126-139. DOI: 10.1155/2007/56365.

Watanabe, O., Uchida, A., Fukuhara, T., Kiya, H. (2015). An Encryption-then-Compression system for JPEG 2000 standard. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 1226-1230, DOI: 10.1109/ICASSP.2015.7178165.

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

Phatak, A. A. (2016). Non-format Compliant Scalable RSA-based JPEG Encryption Algorithm. International Journal of Image, Graphics and Signal Processing, Vol. 8, No. 6, pp. 64–71. DOI: 10.5815/ijigsp.2016.06.08.

Belikova, T. (2020). Decoding Method of Information-Psychological Destructions in the Phonetic Space of Information Resources. 2020 IEEE 2nd International Conference on Advanced Trends in Information Theory (ATIT), pp. 87–91. DOI: 10.1109/ATIT50783.2020.9349300.

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.

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.

Barannik, V., Krasnorutsky, A., Kolesnik, V., Barannik, V., Pchelnicov, S., Zeleny, P. (2022). Method of compression and ensuring the fidelity of video images in infocommunication networks. Radioelectronic and Computer Systems, No. 4(104), pp. 129-142. DOI: 10.32620/reks.2022.4.10.

Barannik, V., Krasnorutsky, A., Ryabukha, Y., Onyshchenko, R., Shulgin, S., Slobodyanyuk, O. (2021). Marker Information Coding for Structural Clustering of Spectral Space. ІЕЕЕ 3nd Іntеrnаtіоnаl Cоnfеrеncе оn Аdvаncеd Trеnds іn Іnfоrmаtіоn Thеоrу (АTІT 2021), рр. 46-51. DOI: 10.1109/ATIT54053.2021.9678538.

Barannik V. V., Krasnorutsky А. O., Kolesnyk V. O., Pchelnikov S. I, Babenko Yu. M., Sheigas O. M. (2022). А Method of Coding Video Segments in Spectral-Cluster Space with Detection of Structural Features. Visnyk NTUU KPI Seriia - Radiotekhnika Radioaparatobuduvannia, Vol. 90, pp. 21-30. DOI: 10.20535/RADAP.2022.90.21-30.



How to Cite

Бараннік, . В. В., Красноруцкий, А. О., Колесник , В. О., Сушко , А. Л., Єлісєєв , Є. С. and Федоровський , О. В. (2023) “Video Segments Stamping Method Saving Their Reliability in the Spectral-Cluster Space: ”, Visnyk NTUU KPI Seriia - Radiotekhnika Radioaparatobuduvannia, (92), pp. 41-53. doi: 10.20535/RADAP.2023.92.41-53.



Telecommunication, navigation, radar systems, radiooptics and electroacoustics