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On the Usefulness of Combined Metrics for 3D Image Quality Assessment

  • Conference paper
Image Processing & Communications Challenges 6

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 313))

Abstract

Due to the growing popularity of 3D imaging technology which can be observed in recent years, one of the most relevant challenges for image quality assessment methods has become their extension towards reliable evaluation of stereoscopic images. Since known 2D image quality metrics are not necessarily well correlated with subjective quality scores of 3D images and the exact mechanism of the 3D quality perception is still unknown, there is a need of developing some new metrics better correlated with subjective perception of various distortions in 3D images. Since a promising direction of such research is related with the application of the combined metrics, the possibilities of their optimization for the 3D images are discussed in this paper together with experimental results obtained for the recently developed LIVE 3D Image Quality Database.

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References

  1. Okarma, K.: Colour image quality assessment using Structural Similarity index and Singular Value Decomposition. In: Bolc, L., Kulikowski, J.L., Wojciechowski, K. (eds.) ICCVG 2008. LNCS, vol. 5337, pp. 55–65. Springer, Heidelberg (2009)

    Chapter  Google Scholar 

  2. Okarma, K.: Video quality assessment using the combined full-reference approach. In: Choraś, R.S. (ed.) Image Processing and Communications Challenges 2. AISC, vol. 84, pp. 51–58. Springer, Heidelberg (2010)

    Chapter  Google Scholar 

  3. Jayaraman, D., Mittal, A., Moorthy, A.K., Bovik, A.C.: Objective image quality assessment of multiply distorted images. In: Conf. Rec. 46th Asilomar Conf. Signals, Systems and Computers, pp. 1693–1697 (2012)

    Google Scholar 

  4. Benoit, A., LeCallet, P., Campisi, P., Cousseau, R.: Quality assessment of stereoscopic images. EURASIP Journal on Image and Video Processing Article ID 659024, 13 (2008)

    Google Scholar 

  5. 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 Processing: Image Communication 28(9), 1143–1155 (2013)

    Google Scholar 

  6. 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  Google Scholar 

  7. You, J., Xing, L., Perkis, A., Wang, X.: Perceptual quality assessment for stereoscopic images based on 2D image quality metrics and disparity analysis. In: Proc. 5th Int. Workshop on Video Processing and Quality Metrics for Consumer Electronics (VPQM), pp. 61–66 (2010)

    Google Scholar 

  8. Gorley, P., Holliman, N.: Stereoscopic image quality metrics and compression. In: Proc. SPIE, vol. 6803, p. 5 (2008)

    Google Scholar 

  9. Wang, Z., Bovik, A., Sheikh, H., Simoncelli, E.: Image quality assessment: From error measurement to Structural Similarity. IEEE Trans. Image Proc. 13(4), 600–612 (2004)

    Article  Google Scholar 

  10. Hewage, C.: Reduced-reference quality metric for 3D depth map transmission. In: Proc. 4th 3DTV Conf.: The True Vision - Capture, Transmission and Display of 3D Video (3DTV-CON), pp. 1–4 (2010)

    Google Scholar 

  11. Yang, J., Hou, C., Zhou, Y., Zhang, Z., Guo, J.: Objective quality assessment method of stereo images. In: Proc. 3rd 3DTV Conf.: The True Vision - Capture, Transmission and Display of 3D Video (3DTV-CON), pp. 1–4 (2009)

    Google Scholar 

  12. Zhu, Z., Wang, Y.: Perceptual distortion metric for stereo video quality evaluation. WSEAS Trans. Signal Process. 5(7), 241–250 (2009)

    Google Scholar 

  13. Shen, L., Yang, J., Zhang, Z.: Stereo picture quality estimation based on a multiple channel HVS model. In: Proc. 2nd IEEE Int. Congress on Image and Signal Processing (CISP), pp. 1–4 (2009)

    Google Scholar 

  14. Akhter, R., Parvez Sazzad, Z., Horita, Y., Baltes, J.: No-Reference stereoscopic image quality assessment. In: Proc. SPIE. Stereoscopic Displays and Applications XXI, vol. 7524, p. 75240T (2010)

    Google Scholar 

  15. Okarma, K.: Combined full-reference image quality metric linearly correlated with subjective assessment. In: Rutkowski, L., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds.) ICAISC 2010, Part I. LNCS (LNAI), vol. 6113, pp. 539–546. Springer, Heidelberg (2010)

    Chapter  Google Scholar 

  16. Wang, Z., Simoncelli, E., Bovik, A.C.: Multi-Scale Structural Similarity for image quality assessment. In: Proc. 37th IEEE Asilomar Conf. on Signals, Systems and Computers, pp. 1398–1402 (2003)

    Google Scholar 

  17. Sheikh, H., Bovik, A.C.: Image information and visual quality. IEEE Trans. Image Process. 15(2), 430–444 (2006)

    Article  Google Scholar 

  18. Mansouri, A., Mahmoudi-Aznaveh, A., Torkamani-Azar, F., Jahanshahi, J.: Image quality assessment using the Singular Value Decomposition theorem. Opt. Rev. 16(2), 49–53 (2009)

    Article  Google Scholar 

  19. Zhang, L., Zhang, L., Mou, X., Zhang, D.: FSIM: A Feature Similarity index for image quality assessment. IEEE Trans. Image Proc. 20(8), 2378–2386 (2011)

    Article  MathSciNet  Google Scholar 

  20. Okarma, K.: Combined image similarity index. Opt. Rev. 19(5), 249–254 (2012)

    Article  Google Scholar 

  21. Liu, T.-J., Lin, W., Kuo, C.-C.J.: Image quality assessment using multi-method fusion. IEEE Trans. Image Process. 22(5), 1793–1807 (2013)

    Article  MathSciNet  Google Scholar 

  22. Okarma, K.: Extended Hybrid Image Similarity - combined full-reference image quality metric linearly correlated with subjective scores. Elektronika ir Elektrotechnika 19(10), 129–132 (2013)

    Google Scholar 

  23. Zhang, L., Zhang, L., Mou, X.: RFSIM: A feature based image quality assessment metric using Riesz transforms. In: Proc. 17th IEEE Int. Conf. Image Processing, pp. 321–324 (2010)

    Google Scholar 

  24. International Telecommunication Union: Recommendation BT.601-7 - Studio encoding parameters of digital television for standard 4:3 and wide-screen 16:9 aspect ratios (2011)

    Google Scholar 

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Authors and Affiliations

  1. Department of Signal Processing and Multimedia Engineering, Faculty of Electrical Engineering, West Pomeranian University of Technology, Szczecin, 26. Kwietnia 10, 71-126, Szczecin, Poland

    Krzysztof Okarma

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  1. Krzysztof Okarma
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Correspondence to Krzysztof Okarma .

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Editors and Affiliations

  1. Institute of Telecommunications, University of Technology & Life Sciences, Bydgoszcz, Poland

    Ryszard S. Choraś

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Okarma, K. (2015). On the Usefulness of Combined Metrics for 3D Image Quality Assessment. In: Choraś, R. (eds) Image Processing & Communications Challenges 6. Advances in Intelligent Systems and Computing, vol 313. Springer, Cham. https://doi.org/10.1007/978-3-319-10662-5_17

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  • DOI: https://doi.org/10.1007/978-3-319-10662-5_17

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-10661-8

  • Online ISBN: 978-3-319-10662-5

  • eBook Packages: EngineeringEngineering (R0)

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