Skip to main content
Log in

PixoComp: a novel video compression scheme utilizing temporal pixograms

  • Published:
Multimedia Tools and Applications Aims and scope Submit manuscript

Abstract

This paper introduces a new compression scheme that exploits temporal redundancies in video segments utilizing the pixogram concept recently introduced in the literature. By taking into consideration the correlation between video pixels along the time domain, a pixogram has the ability to transform uncorrelated spatial areas of separate video-frames into highly correlated temporal vectors, thus increasing redundancy in the transform domain. This strategy allows for higher compression ratios in video streams. The proposed compression scheme is the first compression technique that utilizes the pixogram concept in video compression, and aims to challenge the traditional trade-off associated with high compression ratios leading to reduced visual quality. Comparisons with popular compression standards demonstrate the advantage this new approach has for highly correlated video segments. Moreover, the proposed technique is more suitable to parallelization, and thus outperforms other compression techniques in terms of execution time.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10

Similar content being viewed by others

Notes

  1. https://www.alexa.com/topsites

References

  1. Baziyad M, Rabie T, Kamel I (2018) Extending steganography payload capacity using the L*a*b* color space. In: 2018 International conference on innovations in information technology (IIT’18). IEEE, pp 1–6

  2. Boyadjis B, Bergeron C, Pesquet-Popescu B, Dufaux F (2017) Extended selective encryption of h. 264/avc (cabac)-and hevc-encoded video streams. IEEE Trans Circ Syst Video Technol 27(4):892–906

    Article  Google Scholar 

  3. Deutsch P, et al. (1996) Rfc 1951 deflate compressed data format specification version 1.3. Network Working Group, 15

  4. Grois D, Marpe D, Mulayoff A, Itzhaky B, Hadar O (2013) Performance comparison of h. 265/mpeg-hevc, vp9, and h. 264/mpeg-avc encoders. In: 2013 Picture coding symposium (PCS). IEEE, pp 394–397

  5. Le LN, Nguyen ST, Nguyen NX, Dang TT (2017) A principle of adaptively grouping frames on lossless medical video compression using ideal cross-point regions. In: International conference on the development of biomedical engineering in Vietnam. Springer, pp 19–23

  6. Lewis A, Knowles G (1990) Video compression using 3d wavelet transforms. Electron Lett 26(6):396–398

    Article  Google Scholar 

  7. Martini MG, Hewage CT, Villarini B (2012) Image quality assessment based on edge preservation. Signal Process Image Commun 27(8):875–882

    Article  Google Scholar 

  8. Mukherjee D, Bankoski J, Grange A, Han J, Koleszar J, Wilkins P, Xu Y, Bultje R (2013) The latest open-source video codec vp9-an overview and preliminary results. In: Picture coding symposium (PCS), 2013. IEEE, pp 390–393

  9. Nguyen TQ, et al. (2008) Quality enhancement for motion jpeg using temporal redundancies. IEEE Trans Circ Syst Video Technol 18(5):609–619

    Article  Google Scholar 

  10. Pudlewski S, Cen N, Guan Z, Melodia T (2015) Video transmission over lossy wireless networks: a cross-layer perspective. IEEE J Selected Topics Signal Process 9(1):6–21

    Article  Google Scholar 

  11. Rabie T (2017) Color-secure digital image compression. Multimed Tools Appl 76(15):16657–16679

    Article  Google Scholar 

  12. Rabie T, Baziyad M (2017) Visual fidelity without sacrificing capacity: an adaptive Laplacian pyramid approach to information hiding. J Electron Imag 26(6):063001

    Article  Google Scholar 

  13. Rabie T, Baziyad M (2019) The pixogram: addressing high payload demands for video steganography. IEEE Access 7:21948–21962. https://doi.org/10.1109/ACCESS.2019.2898838

    Article  Google Scholar 

  14. Rabie T, Kamel I (2016) On the embedding limits of the discrete cosine transform. Multimed Tools Appl 75(10):5939–5957

    Article  Google Scholar 

  15. Rabie T, Kamel I (2017) High-capacity steganography: a global-adaptive-region discrete cosine transform approach. Multimed Tools Appl 76(5):6473–6493

    Article  Google Scholar 

  16. Rabie T, Kamel I (2017) Toward optimal embedding capacity for transform domain steganography: a quad-tree adaptive-region approach. Multimed Tools Appl 76 (6):8627–8650

    Article  Google Scholar 

  17. Rabie T, Baziyad M, Kamel I (2018) Enhanced high capacity image steganography using discrete wavelet transform and the Laplacian pyramid. Multimed Tools Appl, 1–26

  18. Rabie T, Baziyad M, Kamel I (2019) High payload steganography: surface-fitting the transform domain. In: 2019 International conference on communications, signal processing, and their applications (ICCSPA). IEEE, pp 1–6

  19. Rabie T, Kamel I, Baziyad M (2018) Maximizing embedding capacity and stego quality: curve-fitting in the transform domain. Multimed Tools Appl 77(7):8295–8326

    Article  Google Scholar 

  20. Ravi A, Rao K (2011) Performance analysis and comparison of the dirac video codec with h. 264/mpeg-4 part 10 avc. Int J Wavelets Multiresol Inform Process 9 (04):635–654

    Article  Google Scholar 

  21. Santos L, Lopez S, Callico GM, Lopez JF, Sarmiento R (2012) Performance evaluation of the h. 264/avc video coding standard for lossy hyperspectral image compression. IEEE Jof Selected Topics Appl Earth Observ Remote Sens 5 (2):451–461

    Article  Google Scholar 

  22. Servais M, De Jager G (1997) Video compression using the three dimensional discrete cosine transform (3d-dct). In: Proceedings of the 1997 South African symposium on communications and signal processing, 1997. COMSIG’97. IEEE, pp 27–32

  23. Srinivasan S, Hsu PJ, Holcomb T, Mukerjee K, Regunathan SL, Lin B, Liang J, Lee M-C, Ribas-Corbera J (2004) Windows media video 9: overview and applications. Signal Process Image Commun 19(9):851–875

    Article  Google Scholar 

  24. Tekalp AM (2015) Digital video processing. Prentice Hall Press

  25. Xiao F, et al. (2000) Dct-based video quality evaluation. Final Project for EE392J, 769

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Tamer Rabie.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Rabie, T., Baziyad, M. PixoComp: a novel video compression scheme utilizing temporal pixograms. Multimed Tools Appl 79, 13179–13196 (2020). https://doi.org/10.1007/s11042-020-08660-9

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11042-020-08660-9

Keywords

Navigation