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
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)
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)
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)
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)
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)
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)
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)
Gorley, P., Holliman, N.: Stereoscopic image quality metrics and compression. In: Proc. SPIE, vol. 6803, p. 5 (2008)
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)
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)
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)
Zhu, Z., Wang, Y.: Perceptual distortion metric for stereo video quality evaluation. WSEAS Trans. Signal Process. 5(7), 241–250 (2009)
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)
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)
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)
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)
Sheikh, H., Bovik, A.C.: Image information and visual quality. IEEE Trans. Image Process. 15(2), 430–444 (2006)
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)
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)
Okarma, K.: Combined image similarity index. Opt. Rev. 19(5), 249–254 (2012)
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)
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)
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)
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)
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Okarma, K. (2015). On the Usefulness of Combined Metrics for 3D Image Quality Assessment. In: ChoraÅ›, 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
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