Skip to main content
Springer Nature Link
Log in

SSIM-based joint-bit allocation for 3D video coding

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

Abstract

The quality of a 3D video display depends on virtual view synthesis process which is affected by the bit allocation criterion. The performance of a bit allocation algorithm is dependent on various encoding parameters like quantization parameter, motion vector, mode selection, and so on. Rate-distortion optimization (RDO) is used to efficiently allocate bits with minimum distortion. In 3D video, rate-distortion (RD) property of synthesized view is used to assign bits between texture video and depth map. Existing literature on bit allocation methods use mean square error (MSE) as distortion metric which is not suitable for measuring perceptual quality. In this paper, we propose structural similarity (SSIM)-based joint bit allocation scheme to enhance visual quality of 3D video. Perceptual quality of a synthesized view depends on texture and depth map quality. Thus, SSIM-based RDO is performed on both texture and depth map where SSIM is used as distortion metric in mode decision and motion estimation. SSIM-based distortion model for synthesized view is determined experimentally. As SSIM cannot be related to quantization step, SSIM-MSE relation is used to convert distortion model in terms of MSE. The Lagrange multiplier method is used to solve the bit allocation problem. The proposed algorithm is implemented using 3DV-ATM as well as HEVC. RD curves show reduction in bitrate with an improvement in SSIM of synthesized view.

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

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

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
Fig. 12
Fig. 13
Fig. 14
Fig. 15
Fig. 16

Similar content being viewed by others

References

  1. 3DV-ATM Reference Software 3DV-ATMv5.lr2. Available at: http://mpeg3dv.nokiaresearch.com/svn/mpeg3dv/tags/3DV-ATMv5.1r2/, [Online; accessed on 06-January-2017]

  2. Bjontegaard G Calculation of average PSNR differences between RD - curves. ITU-TQ.6/SG16 VCEG 13th Meeting, Available at: http://wftp3.itu.int/av-arch/video-site/0104_Aus/

  3. Chen HH, Huang YH, Su PY, Ou TS (2010) Improving video coding quality by perceptual rate-distortion optimization. In: IEEE international conference on multimedia and expo (ICME), 2010. IEEE, pp 1287–1292

  4. Chen Z, Lin W, Ngan KN (2010) Perceptual video coding: challenges and approaches. In: Proceedings of IEEE international conference on multimedia and expo (ICME), pp 784–789

  5. Cui Z, Gan Z, Zhu X (2011) Structural similarity optimal MB layer rate control for H. 264. In: Proceedings of IEEE international conference on wireless communications and signal processing (WCSP), pp 1–5

  6. Fehn C (2003) A 3D-TV approach using depth-Image-Based Rendering (DIBR). In: Proceedings of VIIP, vol 3

  7. Fehn C (2004) Depth-image-based rendering (DIBR), compression, and transmission for a new approach on 3D-TV. In: Electronic imaging 2004. International Society for Optics and Photonics, pp 93– 104

  8. Fujii Laborotory, Nagoya University. Available at: http://www.fujii.nuee.nagoya-u.ac.jp/multiview-data/, [Online; accessed on 06-January-2017]

  9. Harshalatha Y, Biswas PK (2016) Rate distortion optimization using SSIM for 3D video coding. In: International conference on pattern recognition (ICPR)

  10. HM Reference Software HTM-16.2. Available at: https://hevc.hhi.fraunhofer.de/trac/3d-hevc/browser/3DVCSoftware/tags/HTM-16.2, [Online; accessed on 05-September-2017]. https://hevc.hhi.fraunhofer.de/trac/3d-hevc/browser3DVCSoftware/tags

  11. Huang YH, Ou TS, Chen HH (2010) Perceptual-based coding mode decision. In: Proceedings of IEEE international symposium on circuits and systems (ISCAS), pp 393–396

  12. Huang YH, Ou TS, Su PY, Chen HH (2010) Perceptual rate-distortion optimization using structural similarity index as quality metric. IEEE Trans Circuits Syst Video Technol 20(11):1614– 1624

    Article  Google Scholar 

  13. Liu Y, Huang Q, Ma S, Zhao D, Gao W (2009) Joint video/depth rate allocation for 3D video coding based on view synthesis distortion model. Signal Process Image Commun 24(8):666–681

    Article  Google Scholar 

  14. Mai ZY, Yang CL, Po LM, Xie SL (2005) A new rate-distortion optimization using structural information in H. 264 I-Frame Encoder. In: Advanced concepts for intelligent vision systems. Springer, pp 435– 441

  15. Morvan Y, Farin D (2007) Joint depth/texture bit-allocation for multi-view video compression. In: Picture coding symposium (PCS)

  16. Muller K, Merkle P, Wiegand T (2011) 3-D video representation using depth maps. Proc IEEE 99(4):643–656

    Article  Google Scholar 

  17. Muller K, Schwarz H, Marpe D, Bartnik C, Bosse S, Brust H, Hinz T, Lakshman H, Merkle P, Rhee H et al (2013) 3D high efficiency video coding for multi-view video and depth data

  18. Oh BT, Lee J, Park DS (2013) Fast joint bit-allocation between texture and depth maps for 3D video coding. In: IEEE international conference on consumer electronics (ICCE). IEEE, pp 193– 194

  19. Qi J, Li X, Su F, Tu Q, Men A (2013) Efficient rate-distortion optimization for HEVC using SSIM and motion homogeneity. In: Picture coding symposium (PCS), 2013. IEEE, pp 217–220

  20. Shao F, Jiang GY, Yu M, Li FC (2011) View synthesis distortion model optimization for bit allocation in three-dimensional video coding. Opt Eng 50 (12):120502–120502

    Article  Google Scholar 

  21. Shao F, Jiang G, Lin W, Yu M, Dai Q (2013) Joint bit allocation and rate control for coding multi-view video plus depth based 3D video. IEEE Trans Multimed 15(8):1843–1854

    Article  Google Scholar 

  22. Sullivan GJ, Ohm J, Han WJ, Wiegand T (2012) Overview of the high efficiency video coding (HEVC) standard. IEEE Trans Circuits Syst Video Technol 22 (12):1649–1668

    Article  Google Scholar 

  23. Tian D, Lai PL, Lopez P, Gomila C (2009) View synthesis techniques for 3D video. In: Proceedings of the SPIE applications of digital image processing XXXII, vol 7443, pp 74,430T–74,430T

  24. Urey H, Chellappan KV, Erden E, Surman P (2011) State of the art in stereoscopic and autostereoscopic displays. Proc IEEE 99(4):540–555

    Article  Google Scholar 

  25. View Synthesis Reference Software VSRS3.5. Available at: ftp://ftp.merl.com/pub/avetro/3dv-cfp/software/, [Online; accessed on 06-January-2017]

  26. Wang Z, Bovik AC, Sheikh HR, Simoncelli EP (2004) Image quality assessment: from error visibility to structural similarity. IEEE Trans Image Process 13 (4):600–612

    Article  Google Scholar 

  27. Wang Y, Jiang T, Ma S, Gao W (2012) Spatio-temporal ssim index for video quality assessment. In: Visual communications and image processing (VCIP), 2012 IEEE. IEEE, pp 1–6

  28. Yang C, An P, Shen L (2016) Adaptive bit allocation for 3D video coding. In: Circuits, systems, and signal processing, pp 1–23

  29. Yeo C, Tan HL, Tan YH (2013) On rate distortion optimization using SSIM. IEEE Trans Circuits Syst Video Technol 23(7):1170–1181

    Article  Google Scholar 

  30. Yuan H, Chang Y, Li M, Yang F (2010) Model based bit allocation between texture images and depth maps. In: International conference on computer and communication technologies in agriculture engineering (CCTAE), vol 3. IEEE, pp 380–383

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

    Article  Google Scholar 

  32. Zhu G, Jiang G, Yu M, Li F, Shao F, Peng Z (2012) Joint video/depth bit allocation for 3D video coding based on distortion of synthesized view. In: IEEE international symposium on broadband multimedia systems and broadcasting (BMSB). IEEE, pp 1–6

  33. Zitnick CL, Kang SB, Uyttendaele M, Winder S, Szeliski Rs (2004) High-quality video view interpolation using a layered representation. In: ACM transactions on graphics (TOG), vol 23. ACM, pp 600–608

Download references

Author information

Authors and Affiliations

  1. Department of Electronics and Electrical Communication Engineering, Indian Institute of Technology Kharagpur, Kharagpur, 721302, India

    Harshalatha Y & Prabir Kumar Biswas

Authors
  1. Harshalatha Y
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Prabir Kumar Biswas
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Harshalatha Y.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Y, H., Biswas, P. SSIM-based joint-bit allocation for 3D video coding. Multimed Tools Appl 77, 19051–19069 (2018). https://doi.org/10.1007/s11042-017-5327-0

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11042-017-5327-0

Keywords

Search

Navigation

pFad - Phonifier reborn

Pfad - The Proxy pFad of © 2024 Garber Painting. All rights reserved.

Note: This service is not intended for secure transactions such as banking, social media, email, or purchasing. Use at your own risk. We assume no liability whatsoever for broken pages.


Alternative Proxies:

Alternative Proxy

pFad Proxy

pFad v3 Proxy

pFad v4 Proxy