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SSIM-based Error Resilient Video Coding Over Packet-Switched Networks

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Abstract

The visual quality is a critical factor in prediction video coding over packet-switched networks. However, the traditional MSE-based error resilient video coding cannot correlate well with the perceptual characteristics of the human visual system (HVS). This paper proposes a structural similarity (SSIM) based error resilient video coding scheme to improve the visual quality of compressed videos over packet-switched networks. In the proposed scheme, a SSIM-based end-to-end distortion model is developed to estimate the perceptual distortion due to quantization, error concealment, and error propagation. Based on this model, an adaptive mode selection strategy is presented to enhance the communication robustness of compressed videos. Experiments show that the proposed scheme significantly improves the visual quality for H.264/AVC video coding over packet-switched networks.

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References

  1. Zhang, R., Regunathan, S. L., & Rose, K. (2000). Video coding with optimal inter/intra-mode switching for packet loss resilience. IEEE Journal on Selected Areas in Communications, 18, 966–976.

    Article  Google Scholar 

  2. Wang, Y., Wu, Z. Y., & Boyce, J. M. (2006). Modeling of transmission-loss-induced distortion in decoded video. IEEE Transaction on Circuits System Video Technology, 16, 716–732.

    Article  Google Scholar 

  3. Zhou, Y., Hou, C. P., Xiang, W., & Wu, F. (2011). Channel distortion modeling for multi-view video transmission over packet-switched networks. IEEE Transaction on Circuits System Video Technology, 21, 1679–1692.

    Article  Google Scholar 

  4. He, Z. H., Cai, J. F., & Chen, C. W. (2002). Joint source channel rate-distortion analysis for adaptive mode selection and rate control in wireless video coding. IEEE Transaction on Circuits System Video Technology, 12, 511–523.

    Article  Google Scholar 

  5. Xue, Z., Loo, K. K., Cosmas, J., Tun, M., & Yip, P. Y. (2010). Error-resilient scheme for wavelet video coding using automatic ROI detection and Wyner-Ziv coding over packet erasure channel. IEEE Transaction on Broadcasting, 56, 481–493.

    Article  Google Scholar 

  6. Dissanayake, M. B., Worrall, S., & Fernando, W. A. C. (2011). Error resilience for multi-view video using redundant macroblock coding. In IEEE International Conference on Industrial and Information Systems (ICIIS) (pp. 472–476). New York: IEEE Press.

    Google Scholar 

  7. Xiao, J. M., Tillo, T., Lin, C. Y., & Zhao, Y. (2011). Joint redundant motion vector and intra macroblock refreshment for video transmission. EURASIP Journal on Image and Video Processing, 12.

  8. Psannis, K. E., & Ishibashi, Y. (2009). Efficient error resilient algorithm for H.264/AVC: mobility management in wireless video streaming. Springer Telecommunication Systems Journal, 41, 65–76.

    Article  Google Scholar 

  9. Katz, B., Greenberg, S., Yarkoni, N., & Giladi, R. (2007). New error-resilient scheme based on FMO and dynamic redundant slices allocation for wireless video transmission. IEEE Transaction on Broadcasting, 53, 308–319.

    Article  Google Scholar 

  10. Zhang, Y. X., Zhu, C., & Yap, K. H. (2008). A joint source–channel video coding scheme based on distributed source coding. IEEE Transaction on Multimedia, 10, 1648–1656.

    Article  Google Scholar 

  11. Zhang, Y. S., Xiong, H. K., He, Z. H., & Yu, S. Y. (2011). An error resilient video coding scheme using embedded Wyner-Ziv description with decoder side non-stationary distortion modeling. IEEE Transaction on Circuits System Video Technology, 21, 498–512.

    Article  Google Scholar 

  12. Chen, H. H., Huang, Y. H., Su, P. Y., & Ou, T. S. (2010). Improving video coding quality by perceptual rate-distortion optimization. In IEEE International Conference on Multimedia and Expo (ICME) (pp. 1287–1292). New York: IEEE Press.

    Google Scholar 

  13. Ou, T. S., Huang, Y. H., & Chen, H. H. (2011). SSIM-based perceptual rate control for video coding. IEEE Transaction on Circuits System Video Technology, 21, 682–691.

    Article  Google Scholar 

  14. Wang, S. Q., Rehman, A., Wang, Z., Ma, S., & Gao, W. (2012). SSIM-motivated rate distortion optimization for video coding. IEEE Transaction on Circuits System Video Technology, 22, 516–529.

    Article  Google Scholar 

  15. Wang, Z., Bovik, A. C., Sheikh, H. R., & Simoncelli, E. P. (2004). Image quality assessment: from error visibility to structural similarity. IEEE Transaction on Image Processing, 13, 600–612.

    Article  Google Scholar 

  16. Zhang, L., Peng, Q., & Wu, X. (2012). SSIM-based perceptual error-resilient video coding for H.264/AVC. Pacific-Rim Conference on Multimedia (PCM), 7674, 263–272.

    Google Scholar 

  17. Seshadrinathan, K., Soundararajan, R., Bovik, A. C., & Cormack, L. K. (2010). Study of subjective and objective quality assessment of video. IEEE Transaction on Image Processing, 19, 1427–1441.

    Article  MathSciNet  Google Scholar 

  18. Xiph.org Video Test Media. Available: http://media.xiph.org/video/derf/.

  19. Wiegand, T., & Girod, B. (2001). Lagrange multiplier selection in hybrid video coder control. In IEEE International Conference on Image Processing (ICIP) (pp. 542–545). New York: IEEE Press.

    Google Scholar 

  20. JVT Reference Software. Available: http://bs.hhi.de/~suehring/tml.download.

  21. Wenger, S. Error Patterns for Internet Experiments. Available: ftp://ftp.imtc-files.org/jvt-experts/9910_Red/Q15-I16r1.zip.

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Acknowledgments

This work described in this paper was supported by the NSFC (Grant No. 60972111, 61036008, 61071184), Research Funds for the Doctoral Program of Higher Education of China (No. 20100184120009), Program for Sichuan Provincial Science Fund for Distinguished Young Scholars (No. 2012JQ0029, 2013JQ00), and the Fundamental Research Funds for the Central Universities (Project no. SWJTU09CX032, SWJTU10CX08).

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Correspondence to Lei Zhang.

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Zhang, L., Peng, Q., Wu, X. et al. SSIM-based Error Resilient Video Coding Over Packet-Switched Networks. J Sign Process Syst 74, 103–113 (2014). https://doi.org/10.1007/s11265-013-0747-1

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  • DOI: https://doi.org/10.1007/s11265-013-0747-1

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