International Journal of Computer Science & Network Security

International Journal of Computer Science & Network Security (국제컴퓨터통신보호논문지학회)
권호 표지
DOI QR코드

DOI QR Code

Applications and Challenges of Deep Learning and Non-Deep Learning Techniques in Video Compression Approaches

  • K. Siva Kumar (CSE Department, R.V.R & J.C College of Engineering) ;
  • P. Bindhu Madhavi (Department of AI & ML, The Oxford College of Engineering) ;
  • K. Janaki (Department of CSE-AI, Faculty of Engineering, Jain Deemed to be University)
  • Received : 2023.06.05
  • Published : 2023.06.30
Download PDF
⟨ Previous Next ⟩

Abstract

A detailed survey, applications and challenges of video encoding-decoding systems is discussed in this paper. A novel architecture has also been set aside for future work in the same direction. The literature reviews span the years 1960 to the present, highlighting the benchmark methods proposed by notable academics in the field of video compression. The timeline used to illustrate the review is divided into three sections. Classical methods, conventional heuristic methods, and current deep learning algorithms are all used for video compression in these categories. The milestone contributions are discussed for each category. The methods are summarized in various tables, along with their benefits and drawbacks. The summary also includes some comments regarding specific approaches. Existing studies' shortcomings are thoroughly described, allowing potential researchers to plot a course for future research. Finally, a closing note is made, as well as future work in the same direction.

Keywords

References

  1. Image and Video Compression for Multimedia Engineering (Fundamentals, Algorithms, and Standards), Yun Q. Shi New Jersey Institute of Technology Newark, NJ, Huifang Sun Mitsubishi Electric Information Technology Center America Advanced Television Laboratory New Providence, NJ ,by CRC Press LLC, ©2000.
  2. A Practical Guide to Video and Audio Compression from Sprockets and Raster's to Macro blocks, Cliff Wootton, Copyright © Elsevier Inc, 2005.
  3. H.264 and MPEG-4 Video Compression Video Coding for Next-generation Multimedia, Iain E. G. Richardson, The Robert Gordon University, Aberdeen, UK, John Wiley & Sons Ltd, The Atrium, Southern Gate, Chichester, West Sussex PO19 8SQ, England,2003.
  4. J. Loper, "A method for time compression of instructional television materials," Journal of the SMPTE, vol. 73, no. 9, pp. 753-755, 1964. https://doi.org/10.5594/J07169
  5. P. E. Drapkin, "Video data compression," IEEE Transactions on Aerospace and Electronic Systems, vol. AES-2, no. 4, pp. 392-400, 1966. https://doi.org/10.1109/TAES.1966.4501869
  6. G. P. Richards and W. T. Bisignani, "Redundancy reduction applied to coarse-fine encoded video," Proceedings of the IEEE, vol. 55, no. 10, pp. 1707-1717, 1967.
  7. J. Kliger and J. Munushian, "Signal compression traveling-wave tube devices," in 1957 International Electron Devices Meeting, 1957, pp. 113-113.
  8. D. Hochman, "Application of redundancy reduction to television bandwidth compression," Proceedings of the IEEE, vol. 55, no. 3, pp. 263-266, 1967. https://doi.org/10.1109/PROC.1967.5480
  9. R. Kutz and J. Sciulli, "The performance of an adaptive image data compression system in the presence of noise," IEEE Transactions on Information Theory, vol. 14, no. 2, pp. 273-279, 1968. https://doi.org/10.1109/TIT.1968.1054134
  10. D. Seitzer, "An experimental approach to video bandwidth compression by multiplexing," IEEE Transactions on Communication Technology, vol. 17, no. 5, pp. 564-568, 1969. https://doi.org/10.1109/TCOM.1969.1090126
  11. M. Oliver, "An adaptive delta modulator with overshoot suppression for video signals," IEEE Transactions on Communications, vol. 21, no. 3, pp. 243-247, 1973. https://doi.org/10.1109/TCOM.1973.1091633
  12. N. Scheinberg, "A composite ntsc color video bandwidth compressor," IEEE Transactions on Communications, vol. 32, no. 12, pp. 1331-1335, 1984. https://doi.org/10.1109/TCOM.1984.1096000
  13. K. Prabhu, "A predictor switching scheme for dpcm coding of video signals," IEEE Transactions on Communications, vol. 33, no. 4, pp. 373-379, 1985. https://doi.org/10.1109/TCOM.1985.1096304
  14. D. Healy, "Digital video bandwidth compression using block truncation coding," IEEE Transactions on Communications, vol. 29, no. 12, pp. 1809-1817, 1981. https://doi.org/10.1109/TCOM.1981.1094938
  15. J. Arnold and M. Cavenor, "Improvements to the constant area quantization bandwidth compression scheme," IEEE Trans on Communications, vol. 29, no. 12, pp. 1818-1823, 1981. https://doi.org/10.1109/TCOM.1981.1094939
  16. R. J. Majid Rabbani, "An overview of the jpeg2000 still image compression standard," ELSEVIER Signal Processing: Image Communication, vol. 17, no. 1, pp. 3-48, and 2002. https://doi.org/10.1016/S0923-5965(01)00024-8
  17. W. H. G. J. Sullivan, "Overview of the high efficiency video coding (hevc) standard," IEEE Transactions on Circuits and Systems for Video Technology, vol. 22, no. 12, pp. 1649-1668-48, 2012.
  18. G. B. A. L. T. Wiegand, "Overview of the h.264/avc video coding standard," IEEE Trans on Circuits and Systems for Video Technology, vol. 13, no. 7, pp. 560-576, 2003. https://doi.org/10.1109/TCSVT.2003.815165
  19. Beong-Jo Kim, Zixiang Xiong, and W. A. Pearlman, "Low bit-rate scalable video coding with 3-d set partitioning in hierarchical trees (3-d spiht)," IEEE Transactions on Circuits and Systems for Video Technology, vol. 10, no. 8, pp. 1374-1387, 2000. https://doi.org/10.1109/76.889025
  20. H. Cheng, "Partial encryption of compressed images and videos," IEEE Transactions on Signal Processing, vol. 48, no. 8, pp. 2439-2451, 2000. https://doi.org/10.1109/78.852023
  21. Xiaoyan Sun, "Drift-free switching of compressed video bit streams at predictive frames," IEEE Transactions on Circuits and Systems for Video Technology, vol. 16, no. 5, 2006.
  22. M. Tiwari , "Selection of long-term reference frames in dual-frame video coding using simulated annealing," IEEE Signal Processing Letters, vol. 15, pp. 249-252, 2008. https://doi.org/10.1109/LSP.2007.914928
  23. Y. Gao, "H.264/advanced video coding (avc) backward-compatible bit-depth scalable coding," IEEE Transactions on Circuits and Systems for Video Technology, vol. 19, no. 4, pp. 500-510, 2009. https://doi.org/10.1109/TCSVT.2009.2014018
  24. H.Chen, "Compression of Bayer-pattern video sequences using adjusted chroma sub sampling," IEEE Transactions on Circuits and Systems for Video Technology, vol. 19, no. 12, pp. 1891-1896, 2009. https://doi.org/10.1109/TCSVT.2009.2031370
  25. J. Zhang, "Context adaptive Lagrange multiplier (calm) for rate-distortion optimal motion estimation in video coding," IEEE Transactions on Circuits and Systems for Video Technology, vol. 20, no. 6, pp. 820-828, 2010. https://doi.org/10.1109/TCSVT.2010.2045915
  26. H. Nam, "Low complexity content-aware video retargeting for mobile devices," IEEE Transactions on Consumer Electronics, vol. 56, no. 1, pp. 182-189, 2010. https://doi.org/10.1109/TCE.2010.5439143
  27. X. Peng, "Directional filtering transform for image/intra-frame compression," IEEE Transactions on Image Processing, vol. 19, no. 11, pp. 2935-2946, 2010. https://doi.org/10.1109/TIP.2010.2049242
  28. Alan Jacob, "Deep Learning Approach to Video Compression", 2019 (IBSSC).
  29. Guo Lu1, "DVC: An End-to-end Deep Video Compression Framework", Proceedings of the IEEE,2019.
  30. P. K. C-Y W, "Video compression through image interpolation," in 15th European Conference on Computer Vision, 2018, pp. 8-14.
  31. G. V. W. J. D. C. L. P. Van, "Performance analysis of machine learning for arbitrary downsizing of pre-encoded hevc video," IEEE Transactions on Consumer Electronics, vol. 61, no. 4, pp. 507-5115, 2015. https://doi.org/10.1109/TCE.2015.7389806
  32. X. W. H. Y. Z. P. Y. Zhang, "Machine learning-based coding unit depth decisions for flexible complexity allocation in high efficiency video coding," IEEE Transactions on Image Processing, vol. 24, no. 7, pp. 2225-2238, 2015. https://doi.org/10.1109/TIP.2015.2417498
  33. Z. M. F. Duanmu and Y. Wang, "Fast mode and partition decision using machine learning for intra-frame coding in hevc screen content coding extension," IEEE Journal on Emerging and Selected Topics in Circuits and Systems, vol. 6, no. 4, pp. 517-531, 2016. https://doi.org/10.1109/JETCAS.2016.2597698
  34. Chen, "Deep coder: A deep neural network-based video compression," in 2017 IEEE - VCIP, 2017, pp. 1-4.
  35. S. L. J. R. X. G. F. Jiang, W. Tao and D. Zhao, "An end-to-end compression framework based on convolutional neural networks," IEEE Transactions on Circuits and Systems for Video Technology, vol. 28, no. 10, pp. 3007-3018, 2018. https://doi.org/10.1109/TCSVT.2017.2734838
  36. S. K. X. W. L. Zhu, "Fuzzy svm based coding unit decision in hevc," IEEE Transactions on Broadcasting, 2018.
  37. Li, "Learning a CNN for image compact-resolution," IEEE Trans on Image Processing, vol. 28, no. 3, 2019.
  38. Q. J. C. F. P. H. W. W. W. Gao, "Data-driven rate control for rate-distortion optimization in hevc based on simplified effective initial qp learning," IEEE Transactions on Broadcasting, vol. 65, no. 1, pp. 94-108, 2019. https://doi.org/10.1109/TBC.2018.2865647