А Method of Coding Video Segments in Spectral-Cluster Space with Detection of Structural Features





aerial photographs, video data compression, information reliability, structural clustering, coding in spectral-cluster space, statistical redundancy


The directions for improving the efficiency of providing remote video services using the aviation info-communication segment in the process of support and decision-making in critical infrastructure systems are substantiated. It is justified that in order to localize or eliminate problematic aspects, it is necessary to apply technologies for reducing the bit intensity of the video stream. This will reduce the information load on the network and create conditions for the involvement of redundant code structures. Accordingly, it is necessary to integrate video data compression technologies for on-board systems. The effectiveness of clustering video segments in spectral space based on the structural feature of the number of series of units in the binary description of their components is substantiated. A method of statistical coding of transformants in structural space has been developed. The basic component here is the establishment of statistical dependencies within structural clusters, taking into account: local features of spectral components in their range based on structural features in their binary description; reduced power of the statistical space and increase the level of uneven distribution of the clustered components of the transformant. On the basis of the conducted experimental studies, it is shown that the use of the created method of encoding clustered transformants allows to increase the level of reliability of aerial photographs by the indicator of the peak signal/noise ratio by an average of 50%.



JPEG Privacy & Security Abstract and Executive Summary, 2015. JPEG.org, 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. 103-115. 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. [In Ukrainian].

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

DSTU GOST 28147:2009: Information processing system. Cryptographic protection. Cryptographic transformation algorithm (GOST 28147-89) [DSTU GOST 28147:2009: Systema obrobky informatsii. Zakhyst kryptohrafichnyi. Alhorytm kryptohrafichnoho peretvorennia (HOST 28147-89)], State Committee for Technical Regulation and Consumer Policy (Derzhspozhivstandart) of Ukraine, 2008. 20 p. [In Ukrainian].

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. IEEE 2nd International Conference on Advanced Trends in Information Theory (IEEE ATIT 2020), 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.

Barannyk, V. V. and Khakhanova, A. V. (2008). Estimation of informing of binary arrays on the basis of combinatory approach [Otsinka informatyvnosti dviikovykh masyviv na osnovi kombinatornoho pidkhodu]. Information Processing Systems [Systemy obrobky informatsiyi], Vol. 6(73), pp. 11-13. [In Rus.]

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., Krasnorutsky, A., Pasynchuk, K., Babenko, Yu., Stepanko, O., Tuputsa, I. (2022). A Method for Restructuring Video Data in Compressed Coding Systems to Increase Reliability. Visnyk NTUU KPI Seriia - Radiotekhnika Radioaparatobuduvannia, Vol. 88, pp. 50-59. DOI: 10.20535/RADAP.2022.88.50-59.



How to Cite

Бараннік , В. В., Красноруцький , А. О., Колесник , В. О., Пчельніков , С. І., Бабенко , Ю. М. and Шейгас , О. М. (2022) “А Method of Coding Video Segments in Spectral-Cluster Space with Detection of Structural Features”, Visnyk NTUU KPI Seriia - Radiotekhnika Radioaparatobuduvannia, (90), pp. 21-30. doi: 10.20535/RADAP.2022.90.21-30.



Telecommunication, navigation, radar systems, radiooptics and electroacoustics

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