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Fast 3D-HEVC inter mode decision algorithm based on the texture correlation of viewpoints

  • Jing Chen
  • Bohan Wang
  • Jie Liao
  • Canhui Cai
Article
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Abstract

To reduce the computational complexity of 3D-HEVC, a fast inter mode decision algorithm based on texture correlation of adjacent viewpoints is proposed (FMD_inter). By studying the statistical probability of inter prediction mode distributions in 3D-HEVC coding scheme, the mode of dependent view is highly correlated with the base one, which enables the early mode decision. Moreover, by analyzing the relationship between video texture and the inter prediction mode, selectively skip checking symmetric motion partition (SMP) mode and asymmetric motion partition (AMP) mode according to the texture features of coding unit is reasonable. The proposed algorithm is able to achieve a reduction of computational complexity by 18.71% on average, while maintaining the coding efficiency. The subjective quality of the synthesized views also shows the effectiveness of the algorithm.

Keywords

3D-HEVC Inter prediction Video compression Skip mode 

Notes

Acknowledgements

This work was partially supported by National Natural Science Foundation of China (Grant Nos. 61802136 and 61871434), Natural Science Foundation of Fujian Province (Grant Nos. 2017 J05103 and 2016 J01308), Fujian-100 Talented People Program, High-level Talent Innovation Program of Quanzhou City (Grant No. 2017G027), Promotion Program for Young and Middle-aged Teacher in Science and Technology Research of Huaqiao University (Grant No. ZQN-YX403), High-Level Talent Project Foundation of Huaqiao University (Grant Nos. 16BS709, 14BS201 and 14BS204).

References

  1. 1.
    3D-HEVC reference software (2018) https://hevc.hhi.fraunhofer.de/svn/svn_3DVCSoftware/. Accessed 8 Nov 2018
  2. 2.
    Bjontegaard G (2001) Calculation of average PSNR differences between RD-curves. Doc. VCEG-M33 ITU-T Q6/16, 2–4Google Scholar
  3. 3.
    Chen Y, Hannuksela MM, Suzuki T, Hattori S (2014) Overview of the MVC + D 3D video coding standard. J Vis Commun Image Represent 24(4):679–688CrossRefGoogle Scholar
  4. 4.
    Chen Y, Tech G, Wegner K, Yea S (2015) Test model 11 of 3D-HEVC and MV-HEVC. In: Joint Collaborative Team on 3D Video Coding Extension (JCT-3V) Document JCT3V-K1003, 11th Meeting, GenevaGoogle Scholar
  5. 5.
    Chen J, Wang BH, Zeng HQ, Cai CH, Ma KK (2017) Sum-of-Gradient based fast intra coding in 3D-HEVC for depth map sequence (SOG-FDIC). J Vis Commun Image Represent 48:329–339CrossRefGoogle Scholar
  6. 6.
    Chi G, Jin X, Dai Q (2015) A fast coding algorithm based on inter-view correlations for 3D-HEVC. In: Visual Communications and Image Processing Conference (VCIP), 374–377Google Scholar
  7. 7.
    Fehn C (2004) Depth-image-based rendering (DIBR) compression and transmission for a new approach on 3D-TV. Proc SPIE Stereoscopic Displays and Virtual Reality Systems XI(5291):93Google Scholar
  8. 8.
    Hsia CH, Chiang JS, Li HT, Lin CS, Chou KY (2016) A 3D endoscopic imaging system with content-adaptive filtering and hierarchical similarity analysis. IEEE Sensors J 16(11):4521–4530CrossRefGoogle Scholar
  9. 9.
    Jaballah S, Larabi M, Tahar JB (2018) Low complexity intra prediction mode decision for 3D-HEVC depth coding. Signal Processing-Image Communication 67:34–47CrossRefGoogle Scholar
  10. 10.
    JCT-VC (2011) Call for proposals on 3D video coding technology, GenevaGoogle Scholar
  11. 11.
    Lie WN, Lu YH (2015) Fast encoding of 3D color-plus-depth video based on 3D-HEVC. IEEE International Conference on Image Processing (ICIP), 2685–2689Google Scholar
  12. 12.
    Lin JL, Chen YW, Chang YL, An J, Zhang K, Huang YW, Lei S (2018) Advanced texture and depth coding in 3D-HEVC. J Vis Commun Image Represent 50:83–92CrossRefGoogle Scholar
  13. 13.
    Muller K, Vetro A (2014) Common test conditions of 3DV core experimentsGoogle Scholar
  14. 14.
    Park CS (2015) Edge-based intra mode selection for depth-map coding in 3D-HEVC. IEEE Trans Image Process 24(1):155–162MathSciNetCrossRefGoogle Scholar
  15. 15.
    Shen L, Li K, Feng G, An P, Liu Z (2018) Efficient intra mode selection for depth-map coding utilizing spatiotemporal, inter-component and inter-view correlations in 3D-HEVC. IEEE Trans Image Process 9(27):4195–4206MathSciNetCrossRefGoogle Scholar
  16. 16.
    Song YX, Jia KB (2015) Early merge mode decision for texture coding in 3D-HEVC. J Vis Commun Image Represent 33(C):60–68CrossRefGoogle Scholar
  17. 17.
    Tan SC, Ma SW, Wang SS (2017) Inter-view dependency-based rate control for 3D-HEVC. IEEE Transactions on Circuits and Systems for video Technology 2(27):337–351CrossRefGoogle Scholar
  18. 18.
    Tohidypour HR, Pourazad MT, Nasiopoulos P (2016) Online-Learning-Based complexity reduction scheme for 3D-HEVC. IEEE Transactions on Circuits & Systems for Video Technology 26:1–1CrossRefGoogle Scholar
  19. 19.
    Vetro A, Wiegand T, Sullivan GJ (2011) Overview of the stereo and Multiview video coding extensions of the H.264/MPEG-4 AVC standard. Proceeding of IEEE 99(4):626–642CrossRefGoogle Scholar
  20. 20.
    Zhang HB, Fu CH, Chan YL (2016) Probability-based depth intra mode skipping strategy and novel VSO metric for DMM decision in 3D-HEVC. IEEE Transactions on Circuits & Systems for Video Technology 99:1–1Google Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  • Jing Chen
    • 1
    • 2
  • Bohan Wang
    • 1
    • 2
  • Jie Liao
    • 1
    • 2
  • Canhui Cai
    • 1
    • 2
  1. 1.School of Information Science and EnginneringHuaqiao UniversityXiamenChina
  2. 2.Xiamen Key Laboratory of Mobile Multimedia CommunicationsXiamenChina

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