Skip to main content
SpringerLink
Log in

Optimal sequence reordering for low delay screen content coding

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

Abstract

Screen content denotes images generated by computers, which consists of texts, graphics and synthetic images. Conventional encoding strategies developed for natural content, which are premised on the strong temporal relevance, may not work well for screen content. This is because the irregular motion of objects results in the weak temporal relevance in screen content, which also makes the selection of reference pictures not optimal. This paper proposes an optimal picture reordering scheme for screen content coding to enhance the temporal relevance of screen content. In our scheme, a concept of inter-picture correlation is introduced to help formulate the temporal relevance problem, and a model of permutation is proposed to produce the new order of the pictures. To further improve the coding efficiency, a reference picture selecting algorithm is also proposed. Better compression performance can then be achieved. Compared with SCC extension of HEVC, on average, 2.82% bit rate saving can be achieved by reordering the pictures and 4.40% bit saving is achieved by further utilizing the reference pictures selection algorithm.

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

Access this article

Log in via an institution

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

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11

Similar content being viewed by others

References

  1. Bjontegaard G (2008) Improvements of the bd-psnr model. In: ITU-T SG16/Q6, 35th VCEG Meeting, Berlin, Germany, July, 2008

  2. Bross B, Han W J, Sullivan G J, Ohm JR, Wiegand T (2012) High efficiency video coding (hevc) text specification draft 9. document JCTVC-K1003, JCT-VC

  3. Charikar M S (2002) Similarity estimation techniques from rounding algorithms. In: Proceedings of the thiry-fourth annual ACM symposium on theory of computing, pp 380–388

  4. Chen C, Han J, Xu Y, Bankoski J (2016) A staircase transform coding scheme for screen content video coding. In: 2016 IEEE International Conference on Image Processing (ICIP). IEEE, pp 2365–2369

  5. Flynn D, Marpe D, Naccari M, Nguyen T, Rosewarne C, Sharman K, Sole J, Xu J (2015) Overview of the range extensions for the hevc standard: tools, profiles, and performance. IEEE Trans Circuits Syst Video Technol 26(1):4–19

    Article  Google Scholar 

  6. Hevc test model(hm). https://hevc.hhi.fraunhofer.de/trac/hevc/browser (2012)

  7. Lan C, Xu J, Wu F (2011) Compression of compound images by combining several strategies. In: 2011 IEEE 13th International workshop on multimedia signal processing. IEEE, pp 1–6

  8. Li B, Xu J (2014) Hash-based motion search. document JCTVC-Q0245 JCT-VC

  9. Li B, Xu J, Wu F (2014) A unified framework of hash-based matching for screen content coding. In: 2014 IEEE Visual communications and image processing conference. IEEE, pp 530–533

  10. Manju V N, Fred A L (2019) An efficient multi balanced cuckoo search k-means technique for segmentation and compression of compound images. Multimed Tools Applic 78(11):14897–14915

    Article  Google Scholar 

  11. Ohm J-R, Sullivan G J, Schwarz H, Tan T K, Wiegand T (2012) Comparison of the coding efficiency of video coding standards—including high efficiency video coding (hevc). IEEE Trans Circ Syst Video Technol 22(12):1669–1684

    Article  Google Scholar 

  12. Sullivan G J, Topiwala P N, Luthra A (2004) The h. 264/avc advanced video coding standard: overview and introduction to the fidelity range extensions. In: Applications of digital image processing XXVII, vol 5558. International Society for Optics and Photonics, pp 454–474

  13. Sullivan G J, Ohm J-R, Han W-J, Wiegand T (2012) Overview of the high efficiency video coding (hevc) standard. IEEE Trans Circ Syst Video Technol 22(12):1649–1668

    Article  Google Scholar 

  14. Wang S, Ma L, Fang Y, Lin W, Ma S, Gao W (2016) Just noticeable difference estimation for screen content images. IEEE Trans Image Process 25(8):3838–3851

    MathSciNet  Google Scholar 

  15. Xiao W, Li B, Xu J (2016) Bottom-up hash value calculation and validity check. Document JCTVC-W0078 JCT-VC

  16. Xiao W, Li B, Xu J, Shi G, Wu F (2016) Weighted rate-distortion optimization for screen content coding. IEEE Trans Circuits Syst Video Technol 28(2):499–512

    Article  Google Scholar 

  17. Xiao W, Shi G, Li B, Xu J, Wu F (2016) Fast hash-based inter-block matching for screen content coding. IEEE Trans Circuits Syst Video Technol 28(5):1169–1182

    Article  Google Scholar 

  18. Xu J, Joshi R, Cohen R A (2015) Overview of the emerging hevc screen content coding extension. IEEE Trans Circuits Syst Video Technol 26 (1):50–62

    Article  Google Scholar 

  19. Zhang H, Zhou Q, Shi N, Yang F, Feng X, Ma Z (2016) Fast intra mode decision and block matching for hevc screen content compression. In: 2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, pp 1377–1381

  20. Zhu W, Ding W, Xiong R, Shi Y, Yin B (2012) Compound image compression by multi-stage prediction. In: 2012 Visual communications and image processing. IEEE, pp 1–6

  21. Zhu W, Ding W, Xu J, Shi Y, Yin B (2014) 2-d dictionary based video coding for screen contents. In: 2014 Data compression conference. IEEE, pp 43–52

  22. Zhu W, Ding W, Xu J, Shi Y, Yin B (2015) Hash-based block matching for screen content coding. IEEE Trans Multimed 17(7):935–944

    Article  Google Scholar 

Download references

Acknowledgments

This work was supported by the National Key R&D Program of China (No. 2021ZD0111902), National Natural Science Foundation of China(61976011, 62272016, U21B2038, U1937207), the Common Program of Beijing Municipal Commission of Education under Grant KM202010005013, the Opening Project of Beijing Key Laboratory of Internet Culture and Digital Dissemination Research, and by the Special Academic Collaborative Research Projects between BJUT and NTUT(NTUT-BJUT-111-02).

Author information

Authors and Affiliations

  1. Beijing Institute of Artificial Intelligence, Faculty of Information Technology, Beijing University of Technology, Beijing, 100124, China

    Yunhui Shi, Yuansong Wang, Jin Wang, Wenpeng Ding & Baocai Yin

Authors
  1. Yunhui Shi
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Yuansong Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Jin Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Wenpeng Ding
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Baocai Yin
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Jin Wang.

Additional information

Publisher’s note

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

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Shi, Y., Wang, Y., Wang, J. et al. Optimal sequence reordering for low delay screen content coding. Multimed Tools Appl 83, 635–654 (2024). https://doi.org/10.1007/s11042-023-15345-6

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11042-023-15345-6

Keywords

Search

Navigation