Skip to main content
SpringerLink
Log in

Efficient inter-prediction depth coding algorithm based on depth map segmentation for 3D-HEVC

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

Abstract

The 3D extension of High Efficiency Video Coding (3D-HEVC) is the latest international 3D video coding standard, which enhances the compression efficiency of 3D videos with multi-view plus depth (MVD) format. However, it is at the cost of increasing coding complexity. Therefore, this paper proposes a fast inter-prediction algorithm based on depth segmentation for the depth coding of 3D-HEVC to reduce the coding complexity of the depth map. We aim to reduce the coding time by efficiently utilizing the properties of the depth map. First, the proposed algorithm divides a depth map into background, middle ground and foreground, based on automatic thresholding technique. Then, we adjust the search range according to the classification of the coding tree unit (CTU). In addition, an early termination decision by utilizing the correlation of spatial, temporal, and inter-view neighboring CTUs and a fast prediction unit mode decision are also proposed to reduce coding time. The experimental results show that the proposed algorithm can reduce the depth coding time and still maintain good video quality.

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.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15
Fig. 16
Fig. 17
Fig. 18
Fig. 19
Fig. 20

Similar content being viewed by others

References

  1. 3D-HEVC Reference Software Version HTM 15.1. Available online at https://hevc.hhi.fraunhofer.de/svn/svn_3DVCSoftware/tags/HTM-15.1/

  2. Bjontegaard G (2001) Calculation of average PSNR differences between RD curves. ITU-T SG16/Q6 Document VCEG-M33

  3. Bjontegaard G (2008) Improvements of the BD-PSNR model. ITU-T SG16/Q6 Document VCEG-AI11, Berlin

  4. Chen Y, Tech G, Wegner K, Yea S (2015) Test model 11 of 3D-HEVC and MV-HEVC. JCT-3V of ITU-T SG 16 WP 3 and ISO/IEC JTC 1/SC 29/WG 11, document JCT3V-K1003, Geneva

  5. Chen M, Yang Y, Zhang Q, Zhao X, Huang X, Gan Y (2016) Low complexity depth mode decision for HEVC-based 3D video coding. Optik 127(11):4758–4767

    Article  Google Scholar 

  6. Chen B, Yangy Z, Huangz S, Dux X, Cui Z, Bhimaniy J, Xiey X, Mi N (2017) Cyber-physical system enabled nearby traffic flow modelling for autonomous vehicles. In: Proceedings of 2017 IEEE 36th International Performance Computing and Communications Conference (IPCCC), San Diego

  7. Chi GS, Jin X, Dai QH (2014) A fast coding algorithm based on inter-view correlations for 3D-HEVC. In: Proceedings of 2014 IEEE International Conference on Visual Communications and Image Processing (VCIP), Valletta, pp 374–377

  8. Cho H, Lee H, Lee S (2014) Radial bright channel prior for single image vignetting correction. In: Proceedings of 2014 European Conference on Computer Vision (ECCV), Springer, Cham, pp 189–202

  9. Ding M, Fan G (2015) Multilayer joint gait-pose manifolds for human gait motion modeling. IEEE Trans Cybern 45(11):2413–2424

    Article  Google Scholar 

  10. Ding M, Fan G (2016) Articulated and generalized gaussian kernel correlation for human pose estimation. IEEE Trans Image Process 25(2):776–789

    Article  MathSciNet  Google Scholar 

  11. Fehn C (2004) Depth-Image-Based Rendering (DIBR), compression, and transmission for a new approach on 3D-TV. In: Proceedings of SPIE Stereoscopic Displays and Virtual Reality Systems XI 529:93–104

  12. Goldman DB (2010) Vignette and exposure calibration and compensation. IEEE Trans Pattern Anal Mach Intell 32(12):2276–2288

    Article  Google Scholar 

  13. Lin JL, Chen YW, Huang YW, Lei SM (2013) Motion vector coding in the HEVC standard. IEEE J Sel Topics Signal Process 7(6):957–968

    Article  Google Scholar 

  14. Merkle P, Smolic A, Müller K, Wiegand T (2007) Multi-view video plus depth representation and coding. In: Proceedings of 2007 IEEE International Conference on Image Processing 1:I-203–I-204

  15. Otsu N (1979) A threshold selection method from gray level histograms. IEEE Trans Syst, Man, Cybern, Syst 9(1):62–66

    Article  Google Scholar 

  16. Samii A, Althoff T (2011) Iterative learning: leveraging the computer as an on-demand expert artist. CS281A Statistical Learning Theory (Michael Jordan and Martin Wainwright) and CS294–69 Image Manipulation and Computational Photography (Maneesh Agrawala), University of California, Berkeley, 1–11

  17. Shen L, Liu Z, Zhang X, Zhao W, Zhang ZY (2013) An effective CU size decision method for HEVC encoders. IEEE Trans Multimedia 15(2):465–470

  18. Shen L, Zhang Z (2014) Efficient depth coding in 3D video to minimize coding bitrate and complexity. Multimed Tools Appl 72(2):1639–1652

    Article  Google Scholar 

  19. Sullivan GJ, Ohm JR, Han WJ, Wiegand T (2012) Overview of the High Efficiency Video Coding (HEVC) standard. IEEE Trans Circuits Syst Video Technol 22(12):1649–1668

  20. Tech G, Chen Y, Müller K, Ohm JR, Vetro A, Wang YK (2016) Overview of the multiview and 3D extensions of High Efficiency Video Coding. IEEE Trans Circuits Syst Video Technol 26(11):35–49

  21. Wiegand T, Sullivan GJ, Bjontegaard G,  Luthra A (2003) Overview of the H.264/AVC video coding standard. IEEE Trans Circuits Syst Video Technol 13(7):560–576

  22. Wu YD, Chen MJ, Lin KM (2015) Efficient coding unit and prediction unit decision for HEVC encoder. In: Proceedings of 2015 National Symposium on Telecommunications (NST)

  23. Yan C, Xie H, Chen J, Zha Z, Hao X, Zhang Y, Dai Q (2018) An effective uyghur text detector for complex background images. IEEE Trans. Multimedia. Early Access

  24. Yan C, Xie H, Liu S, Yin J, Zhang Y, Dai Q (2018) Effective uyghur language text detection in complex background images for traffic prompt identification. IEEE Trans Intell Transp Syst 19(1):220–229

    Article  Google Scholar 

  25. Yan C, Xie H, Yang D, Yin J, Zhang Y, Dai Q (2018) Supervised hash coding with deep neural network for environment perception of intelligent vehicles. IEEE Trans Intell Transp Syst 19(1):284–295

    Article  Google Scholar 

  26. Yan C, Zhang Y, J X, Dai F, Li L, Dai Q, F W (2014) A highly parallel framework for HEVC coding unit partitioning tree decision on many-core processors. IEEE Signal Process Lett 21(5):573–576

    Article  Google Scholar 

  27. Yan C, Zhang Y, J X, Dai F, Zhang J, Dai Q (2014) Feng Wu, Efficient parallel framework for HEVC motion estimation on many-core processors. IEEE Trans Circuits Syst Video Technol 24(12):2077–2089

    Article  Google Scholar 

  28. Zhang X, Constable M, Chan KL (2017) Transfer of vignetting effect from paintings to photographs. In: Proceedings of 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), New Orleans, pp 1957-1961

  29. Zhang Q, Li N, Gan Y (2014) Low complexity mode decision for 3D-HEVC. Sci World J 2014:1–12

  30. Zhang Y, Pan Z, Zhou Y, Zhu L (2017) Allowable depth distortion based fast mode decision and reference frame selection for 3D depth coding. Multimed Tools Appl 76(1):1101–1120

    Article  Google Scholar 

  31. Zhang N, Zhao D, Chen YW, Lin JL, Gao W (2014) Fast encoder decision for texture coding in 3D-HEVC. Signal Process-Image 29(9):951–961

    Article  Google Scholar 

  32. Zheng Y, Lin S, Kang SB, Xiao R, Gee JC, Kambhamettu C (2013) Single-image vignetting correction from gradient distribution symmetries. IEEE Trans Pattern Anal Mach Intell 35(6):1480–1494

Download references

Acknowledgements

The authors would like to thank the Ministry of Science and Technology, Taiwan, R.O.C. for financially supporting this research under contract NO. MOST 103-2221-E-259-009-MY3, MOST 107-2218-E-003-003-, MOST 107-2218-E-110-004-, MOST 105-2221-E-110-094-MY3, MOST 106-2221-E-110-083-MY2 and MOST 105-2221-E-259-016-MY3.

Author information

Authors and Affiliations

  1. Department of Electrical Engineering, National Dong Hwa University, Hualien, Taiwan

    Yi-Wen Liao, Mei-Juan Chen, Jie-Ru Lin & Chih-Wei Chen

  2. Department of Electrical Engineering, National Taiwan Normal University, Taipei, Taiwan

    Chia-Hung Yeh

  3. Department of Electrical Engineering, National Sun Yat-Sen University, Kaohsiung, Taiwan

    Chia-Hung Yeh

Authors
  1. Yi-Wen Liao
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Mei-Juan Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Chia-Hung Yeh
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Jie-Ru Lin
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Chih-Wei Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Chia-Hung Yeh.

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

Liao, YW., Chen, MJ., Yeh, CH. et al. Efficient inter-prediction depth coding algorithm based on depth map segmentation for 3D-HEVC. Multimed Tools Appl 78, 10181–10205 (2019). https://doi.org/10.1007/s11042-018-6547-7

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11042-018-6547-7

Keywords

Search

Navigation