Nothing Special   »   [go: up one dir, main page]
Skip to main content
Springer Nature Link
Log in

Quality evaluation of DIBR 3D images based on blind watermarking

  • Regular Paper
  • Published:
Multimedia Systems Aims and scope Submit manuscript

Abstract

The quality evaluation of stereoscopic images is becoming increasingly important in 3D multimedia applications. Watermarking-based quality evaluation has been a promising technology for 3D content quality evaluation. In this work, we propose a novel quality evaluation scheme for depth-image-based rendering (DIBR) 3D images. The scheme utilizes the watermarking technique to evaluate the quality of watermarked images under various distortions. In this scheme, the watermark is embedded into the selected coefficients of dual-tree complex wavelet transform sub-bands of the center view. The virtual left and right views are synthesized from the watermarked center view and the associated depth map using the DIBR technique at the receiver side. The watermark can be detected from the three views individually, and the quality of these views under various attacks can be estimated by examining the degradation of corresponding extracted watermarks. In addition, the quality evaluation is made possible by checking the generated mapping curve, which maps the normalized correlation of the extracted watermark to the quality measure of the watermarked image under distortions. There is a high correlation between the estimated quality and the calculated quality. The experimental results demonstrate that the proposed scheme has good performance of quality evaluation for DIBR 3D images under JPEG compression, JPEG 2000 compression, Gaussian noise, and Gaussian blur. Moreover, our proposed scheme exhibits superiority over other related methods in terms of evaluation accuracy.

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

Similar content being viewed by others

References

  1. Wang, Z., Bovik, A.C., Sheikh, H.R., Simoncelli, E.P.: Image quality assessment: from error visibility to structural similarity. IEEE Trans. Image Process. 13(4), 600–612 (2004)

    Article  Google Scholar 

  2. Sheikh, H.R., Sabir, M.F., Bovik, A.C.: A statistical evaluation of recent full reference image quality assessment algorithms. IEEE Trans. Image Process. 15(11), 3441–3452 (2006)

    Article  Google Scholar 

  3. Wang, Z., Simoncelli, E.P.: Reduced-reference image quality assessment using a wavelet domain natural image statistic model. In: Proceedings of SPIE conference on human vision and electronic imaging, vol. 5666, pp. 149–159 (2005)

  4. Li, Q., Wang, Z.: Reduced-reference image quality assessment using divisive normalization-based image representation. IEEE J. Sel. Topics Signal Process. 3(2), 201–211 (2009)

    Google Scholar 

  5. Wang, Z., Sheikh, H.R., Bovik, A.C.: No-reference perceptual quality assessment of JPEG compressed images. In: Proceedings of IEEE International Conference on Image Processing, vol. 1, pp 477–480 (2002)

  6. Mittal, A., Moorthy, A.K., Bovik, A.C.: No-reference image quality assessment in the spatial domain. IEEE Trans. Image Process. 21(12), 4695–4708 (2012)

    Article  MathSciNet  MATH  Google Scholar 

  7. Saad, M.A., Bovik, A.C., Charrier, C.: Blind image quality assessment: a natural scene statistics approach in the DCT domain. IEEE Trans. Image Process. 21(8), 3339–3352 (2012)

    Article  MathSciNet  MATH  Google Scholar 

  8. Wang, S., Zheng, D., Zhao, J., Tam, W.J., Speranaza, F.: Adaptive watermarking and tree structure based image quality estimation. IEEE Trans. Multimed. 16(2), 311–325 (2014)

    Article  Google Scholar 

  9. Campisi, P., Carli, M., Giunta, G., Neri, A.: Blind quality assessment system for multimedia communications using tracing watermarking. IEEE Trans. Signal Process. 51(4), 996–1002 (2003)

    Article  MathSciNet  MATH  Google Scholar 

  10. Wang, S., Zheng, D., Zhao, J., Tam, W.J., Speranaza, F.: A digital watermarking and perceptual model based video quality measurement. In: Proceedings of IEEE International Instrumentation and Measurement Technology Conference, pp. 1729-1734 (2005)

  11. Wang, S., Zheng, D., Zhao, J., Tam, W.J., Speranaza, F.: An image quality evaluation method based on digital watermarking. IEEE Trans. Circ. Syst. Video Technol. 17(1), 98–105 (2007)

    Article  Google Scholar 

  12. Chen, M.J., Cormack, L.K., Bovik, A.C.: No-reference quality assessment of natural stereopairs. IEEE Trans. Image Process. 22(9), 3379–3391 (2013)

    Article  MathSciNet  MATH  Google Scholar 

  13. Lin, Y.H., Wu, J.L.: Quality assessment of stereoscopic 3D image compression by binocular integration behaviors. IEEE Trans. Image Process. 23(4), 1527–1542 (2014)

    Article  MathSciNet  MATH  Google Scholar 

  14. Chen, L., Zhao, J.: Quality assessment of stereoscopic 3D images based on local and global visual characteristics. In: Proceedings of IEEE International Conference on Multimedia and Expo, pp. 61–66 (2017)

  15. Fehn, C.: Depth-image-based rendering (DIBR), compression and transmission for a new approach on 3D-TV. In: Proceedings of SPIE Conference on Stereoscopic Displays and Virtual Reality Systems XI, vol. 5291, pp. 93–104 (2004)

  16. Chen, L., Zhao, J.: Robust contourlet-based watermarking for depth-image-based rendering 3D images. In: Proceedings of IEEE International Symposium on Broadband Multimedia Systems and Broadcasting, pp. 1–4 (2016)

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

    Article  MathSciNet  MATH  Google Scholar 

  18. Battisti, F., Bosc, E., Carli, M., Callet, P.L., Perugia, S.: Objective image quality assessment of 3D synthesized views. Signal Process. Image Commun. 30, 78–88 (2015)

    Article  Google Scholar 

  19. Chen, L., Zhao, J.: Watermarking based quality assessment for DIBR 3D images. In: Proceedings of IEEE International Conference on Smart Data, pp. 810–814 (2016)

  20. Farias, M., Carli, M., Mitra, S.: Objective video quality metric based on data hiding. IEEE Trans. Consum. Electron. 51(3), 983–992 (2005)

    Article  Google Scholar 

  21. Nezhadarya, E., Wang, Z., Ward, R.: Image quality monitoring using spread spectrum watermarking. In: Proceedings of IEEE International Conference on Image Processing, pp. 2233–2236 (2009)

  22. Altous, S., Samee, M.K., Gotze, J.: Reduced reference image quality assessment for JPEG distoriton. In: Proceedings of IEEE International Symposium on ELMAR, pp. 431–436 (2011)

  23. Benoit, A., Callet, P.L., Campisi, P., Cousseau, R.: Using disparity for quality assessment of stereoscopic images. In: Proceedings of IEEE International Conference on Image Processing, pp. 389–392 (2008)

  24. You, J., Xing, L., Perkis, A., Wang, X.: Perceptual quality assessment for stereoscopic images based on 2D image quality metrics and disparity analysis. In: Proceedings of International Workshop on Video Processing, Quality Metrics and Consumer Electronics, pp. 61–66 (2010)

  25. Zhu, Z., Yang, Y.: Perceputal distortion meric for stero video quality evaluation. WSEAS Trans. Signal Process. 5(7), 241–250 (2009)

    Google Scholar 

  26. Hewage, C.T.E.R., Martini, M.G.: Reduced-reference quality metric for 3D depth map transmission. In: Proceedings of 3DTV Conference: The True Vision - Capture, Transmission and Display of 3D Video, pp. 1–4 (2010)

  27. Chen, M.J., Su, C.C., Kwon, D.K., Cormack, L.K., Bovik, A.C.: Full-reference quality assessment of stereopairs accounting for rivalry. Signal Process. Image Commun. 28(9), 1143–1155 (2013)

    Article  Google Scholar 

  28. Wang, J., Rehman, A., Zeng, K., Wang, S., Wang, Z.: Quality prediction of asymmetrically distorted stereoscopic 3D images. IEEE Trans. Image Process. 24(11), 3400–3414 (2015)

    Article  MathSciNet  MATH  Google Scholar 

  29. Zhang, L., Tam, W.J.: Stereoscopic image generation based on depth images for 3D TV. IEEE Trans. Broadcast. 51(2), 191–199 (2005)

    Article  Google Scholar 

  30. Zhang, L., Vazquez, C., Knorr, S.: 3D-TV content creation: automatic 2D-to-3D video conversion. IEEE Trans. Broadcast. 57(2), 372–383 (2011)

    Article  Google Scholar 

  31. Lee, P.J.: Effendi: nongeometric distortion smoothing approach for depth map preprocessing. IEEE Trans. Multimed. 13(2), 246–254 (2011)

    Article  Google Scholar 

  32. Loo, P., Kingsburry, N.: Digital watermarking using complex wavelets. In: Proceedings of IEEE International Conference on Image Processing, pp. 29–32 (2000)

  33. Selesnick, I.W., Baraniuk, R.G., Kingsburry, N.G.: The dual-tree complex wavelet transform. IEEE Signal Process. Mag. 22(6), 123–151 (2005)

    Article  Google Scholar 

  34. Kim, H.D., Lee, J.W., Oh, T.W., Lee, H.K.: DT-CWT watermarking for DIBR 3D images. IEEE Trans. Broadcast. 58(4), 533–543 (2012)

    Article  Google Scholar 

  35. Asikuzzaman, M., Alam, M.J., Lambert, A.J., Pickering, M.R.: A blind watermarking scheme for depth-image-based rendered 3D video using the dual-tree complex wavelet transform. In: Proceedings of IEEE International Conference on Image Processing, pp. 5497–5501 (2014)

  36. Tam, W.J., Speranza, F., Yano, S., Shimono, K., Ono, H.: Stereoscopic 3D-TV: visual comfort. IEEE Trans. Broadcast. 57(2), 335–346 (2011)

    Article  Google Scholar 

  37. Coria, L.E., Pickering, M.R., Nasiopoulos, P., Ward, R.K.: A video watermarking scheme based on the dual-tree complex wavelet transform. IEEE Trans. Inf. Forensics Secur. 3(3), 466–474 (2008)

    Article  Google Scholar 

  38. Malvar, H.S., Florencio, D.A.F.: Improved spread spectrum: a new modulation techinque for robust watermarking. IEEE Trans. Signal Process. 51(4), 898–905 (2003)

    Article  MathSciNet  MATH  Google Scholar 

  39. Hirschmuller, H., Scharstein, D.: Evaluation of cost functions for stereo matching. In: Proceedings of IEEE International Conference on Computer Vision and Pattern Recognition, pp. 1–8 (2007)

  40. Moorthy, A.K., Su, C.C., Mittal, A., Bovik, A.C.: Subjective evaluation of stereoscopic image quality. Signal Process. Image Commun. 28(8), 870–883 (2012)

    Article  Google Scholar 

  41. Lin, Y.H., Wu, J.L.: A digital blind watermarking for depth-image-based rendering 3D images. IEEE Trans. Broadcast. 57(2), 602–611 (2011)

    Article  Google Scholar 

  42. Chen, L., Zhao, J.: Robust contourlet-based blind watermarking for depth-image-based rendering 3D images. Signal Process. Image Commun. 54, 56–65 (2017)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Multimedia Communications Research Laboratory, School of Electrical Engineering and Computer Science, University of Ottawa, 800 King Edward Ave., Ottawa, ON, K1N 6N5, Canada

    Lei Chen & Jiying Zhao

Authors
  1. Lei Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Jiying Zhao
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Jiying Zhao.

Additional information

Communicated by P. Pala.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Chen, L., Zhao, J. Quality evaluation of DIBR 3D images based on blind watermarking. Multimedia Systems 25, 195–211 (2019). https://doi.org/10.1007/s00530-018-0596-7

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00530-018-0596-7

Keywords

Search

Navigation