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Allowable depth distortion based fast mode decision and reference frame selection for 3D depth coding

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Abstract

To improve the coding efficiency and meanwhile reduce the complexity of the depth video encoder in 3D system, we present an efficient depth coding scheme based on the allowable depth distortion (ADD) in view synthesis. Firstly, we analyze the depth distortion in view synthesis and present a new ADD-based Rate Distortion (RD) optimization cost function to improve the mode/reference decision criteria. Then, we present an early mode and reference frame selection algorithm, which skips the unnecessary and complex mode and reference frame when the depth distortion is within the ADD interval. Meanwhile, the coding efficiency is improved by RD optimized mode decision and reference frame selection. The experimental results show that the proposed overall algorithm, which integrates the fast mode decision, reference frame selection and RD optimization, can reduce the depth coding complexity from 32.47 to 72.59, and 55.95 % on average over different test sequences. Meanwhile, the proposed algorithm achieves 1.34 and 1.58 dB average Bjontegaard Delta peak signal-to-noise ratio gain in terms of the view synthesis quality at low and high bit rate, respectively. In terms of the bit rate reduction, it reduces 54.66 and 49.60 % Bjontegaard Delta bit rate on average at low and high bit rate, respectively, while maintaining the same view synthesis image quality.

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References

  1. Bjontegaard G (2001) Calculation of average PSNR differences between RD-curves. ITU-T VCEG, VCEG-M33

  2. Chen Y, Hannuksela MM, Suzuki T, Hattori S (2014) Overview of the MVC+D 3D video coding standard. J Vis Commun Image Represent 25(4):679–688

    Article  Google Scholar 

  3. Hannuksela MM, Rusanovskyy D, Su W, Chen L, Li R, Aflaki P, Lan D, Joachimiak M, Li H, Gabbouj M (2013) Multiview-video-plus-depth coding based on the advanced video coding standard. IEEE Trans Image Process 22(9):3449–3548

    Article  Google Scholar 

  4. Hu S, Kwong S, Zhang Y, Kuo C-CJ (2013) Rate-distortion optimized rate control for depth map based 3D video coding. IEEE Trans Image Process 22(2):585–594

    Article  MathSciNet  Google Scholar 

  5. Kang MK, Ho YS (2012) Depth video coding using adaptive geometry based intra prediction for 3-D video systems. IEEE Trans Multimed 14(1):121–128

    Article  Google Scholar 

  6. Lee J, Wey H, Park D (2011) A Fast and efficient multiview depth image coding method based on temporal and inter-view correlations of texture images. IEEE Trans Circuits Syst Video Technol 21(12):1859–1868

    Article  Google Scholar 

  7. Liu Q, Yang Y, Ji R, Gao Y, Yu L (2012) Cross-view down/up-sampling method for multiview depth video coding. IEEE Signal Process Lett 19(5):295–298

    Article  Google Scholar 

  8. Liu X, Zhang Y, Hu S, Kwong S, Kuo CCJ, Peng Q (2015) Subjective and objective video quality assessment of 3-d synthesized view with texture/depth compression distortion. IEEE Trans Image Process 24(12):4847–4861

    Article  MathSciNet  Google Scholar 

  9. Merkle P, Muller K, Marpe D, Wiegand T (2015) Depth intra coding for 3D video based on geometric primitives. IEEE Trans Circuits Syst Video Technol. doi:10.1109/TCSVT.2015.2407791

    Google Scholar 

  10. Mora EG, Jung J, Cagnazzo M, Popescu BP (2014) Depth video coding based on intra mode inheritance from texture. APSIPA Trans Signal Inf Process 3(e1):1–13

    Article  Google Scholar 

  11. Oh BT, Oh KJ (2014) View synthesis distortion estimation for AVC- and HEVC-compatible 3-D video coding. IEEE Trans Circuits Syst Video Technol 24(6):1006–1015

    Article  Google Scholar 

  12. Oh KJ, Vetro A, Ho YS (2011) Depth coding using a boundary reconstruction filter for 3-D video systems. IEEE Trans Circuits Syst Video Technol 21(3):350–359

    Article  Google Scholar 

  13. Pan Z, Zhang Y, Kwong S (2013) Fast mode decision based on texture-depth correlation and motion prediction for multiview depth video coding. J Real-Time Image Process. doi:10.1007/s11554-013-0328-3

    Google Scholar 

  14. Pan Z, Zhang Y, Kwong S (2015) Efficient motion and disparity estimation optimization for low complexity multiview video coding. IEEE Trans Broadcast 61(2):166–176

    Article  Google Scholar 

  15. Peng Z, Yu M, Jiang G, Shao F, Zhang Y, Yang Y (2010) Fast macroblock mode selection algorithm for multiview depth video coding. Chin Opt Lett 8(2):151–154

    Article  Google Scholar 

  16. Schwarz H, Bartnik C, Bosse S, Brust H, Hinz T, Lakshman H, Marpe D, Merkle P, Muller K, Rhee H, Tech G, Winken M, Wiegand T (2012) 3D video coding using advanced prediction, depth modeling, and encoder control methods. In: Proc. PCS’12, Kraków, Poland 1–4

  17. Tanimoto M, Fujii T, Tehrani MP, Wildeboer M (2009) Depth Estimation Reference Software (DERS) 5.0. ISO/IEC JTC1/SC29/WG11, M16923, Xian

    Google Scholar 

  18. Tanimoto M, Fujii T, Suzuki K (2009) View Synthesis Algorithm in View Synthesis Reference Software 3.0 (VSRS3.0). ISO/IEC JTC1/SC29/WG11, M16090, Lausanne

    Google Scholar 

  19. Wang X, Kwong S, Yuan H, Zhang Y, Pan Z (2015) View synthesis distortion model based frame level rate control optimization for multiview depth video coding. Signal Process 112:189–198

    Article  Google Scholar 

  20. Yang Y, Zhang J, He Z, Gao M (2014) Depth map super-resolution via local and non-local priors. J Electron Imaging 23(2):023019

    Article  Google Scholar 

  21. Yang Y, Gao M, Zhang J, Zha Z, Wang Z (2015) Depth map super-resolution using stereo-vision-assisted model. Neurocomputing 149(part C):1396–1406

    Article  Google Scholar 

  22. Yang Y, Liu Q, Liu H, Yu L, Wang F (2015) Dense image synthesis via energy minimization for three-dimensional video. Signal Process. doi:10.1016/j.sigpro.2014.07.020

    Google Scholar 

  23. Yoon DH, Ho YS (2011) Fast mode decision algorithm for depth coding in 3D video systems using H.264/AVC. Proc PSIVT’11 2:25–35

    Google Scholar 

  24. Yuan H, Chang Y, Huo J, Yang F, Lu Z (2011) Model based joint bit allocation between texture videos and depth maps for 3D video coding. IEEE Trans Circuits Syst Video Technol 21(4):485–497

    Article  Google Scholar 

  25. Zamarin M, Forchhammer S (2014) Edge-preserving intra mode for efficient depth map coding based on H.264/AVC. Signal Process Image Commun 29(7):711–724

    Article  Google Scholar 

  26. Zhang Y, Kwong S, Jiang G, Wang X (2011) Efficient multi-reference frame selection algorithm for hierarchical B frames in multiview video coding. IEEE Trans Broadcast 57(1):15–24

    Article  Google Scholar 

  27. Zhang Y, Kwong S, Xu L, Hu S, Jiang G, Kuo C-CJ (2013) regional bit allocation and rate distortion optimization for multiview depth video coding with view synthesis distortion model. IEEE Trans Image Process 22(9):3497–3512

    Article  Google Scholar 

  28. Zhang Y, Kwong S, Xu L, Jiang G (2013) DIRECT mode early decision optimization based on rate distortion cost property and inter-view correlation. IEEE Trans Broadcast 59(2):390–398

    Article  Google Scholar 

  29. Zhang Y, Kwong S, Hu S, Kuo CCJ (2014) Efficient multiview depth coding optimization based on allowable depth distortion in view synthesis. IEEE Trans Image Process 23(11):4879–92

    Article  MathSciNet  Google Scholar 

  30. Zhao Y, Zhu C, Chen Z, Yu L (2011) Depth no-synthesis-error model for view synthesis in 3-D video. IEEE Trans Image Process 20(8):2221–2228

    Article  MathSciNet  Google Scholar 

  31. Zhu L, Zhang Y, Wang X, Kwong S (2015) View synthesis distortion elimination filter for mutliview depth coding in 3D video system. Multimed Tools Appl 74(15):5935–5954

    Article  Google Scholar 

Download references

Acknowledgments

This work was partly supported by Natural Science Foundation of China (NSFC) (Grant Nos. 61471348 61102088 61401132 and 61501246), in part by Shenzhen Overseas High-Caliber Personnel Innovation and Entrepreneurship Project under Grant KQCX20140520154115027, and in part by Guangdong Special Support Program for Youth Science and Technology Innovation Talents under Grant 2014TQ01X345.

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Correspondence to Yun Zhang.

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Zhang, Y., Pan, Z., Zhou, Y. et al. Allowable depth distortion based fast mode decision and reference frame selection for 3D depth coding. Multimed Tools Appl 76, 1101–1120 (2017). https://doi.org/10.1007/s11042-015-3109-0

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  • DOI: https://doi.org/10.1007/s11042-015-3109-0

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