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GPGPU Based Estimation of the Combined Video Quality Metric

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Part of the book series: Advances in Intelligent and Soft Computing ((AINSC,volume 102))

Summary

In this paper some possibilities of using the GPGPU programming techniques for a fast estimation of the recently proposed combined video quality metric are discussed. Such metric consists of three state-of-the-art image quality assessment metrics applied using frame-by-frame analysis with appropriate weighting coefficients. Since this combined metric is better correlated with subjective quality scores than each of its components, especially for the contaminations typical for the wireless transmission of compressed video data, the next step is related to its efficient implementation useful for real-time applications. In the paper an efficient implementation of the estimated combined metric is presented together with the verification of its linear correlation with subjective video quality evaluations performed using the LIVE Wireless Video Quality Assessment Database containing 160 video files with four types of distortions and their Differential Mean Opinion Score (DMOS) values.

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References

  1. Wang, Z., Bovik, A.: A universal image quality index. IEEE Signal Proc. Letters 9(3), 81–84 (2002)

    Article  Google Scholar 

  2. Eskicioglu, A.: Quality measurement for monochrome compressed images in the past 25 years. In: Proc. Int. Conf. Acoust. Speech Signal Proc., pp. 1907–1910 (2000)

    Google Scholar 

  3. 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 

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

    Google Scholar 

  5. Okarma, K.: Two-dimensional windowing in the Structural Similarity index for the colour image quality assessment. In: Jiang, X., Petkov, N. (eds.) CAIP 2009. LNCS, vol. 5702, pp. 501–508. Springer, Heidelberg (2009)

    Chapter  Google Scholar 

  6. Sheikh, H.R., Bovik, A., de Veciana, G.: An information fidelity criterion for image quality assessment using natural scene statistics. IEEE Trans. Image Proc. 14(12), 2117–2128 (2005)

    Article  Google Scholar 

  7. Sheikh, H.R., Bovik, A.: Image information and visual quality. IEEE Trans. Image Proc. 15(2), 430–444 (2006)

    Article  Google Scholar 

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

    Chapter  Google Scholar 

  9. Moorthy, A.K., Seshadrinathan, K., Soundararajan, R., Bovik, A.: Wireless video quality assessment: A study of subjective scores and objective algorithms. IEEE Trans. Circuits and Systems for Video Technology 20(4), 513–516 (2010)

    Article  Google Scholar 

  10. Moorthy, A.K., Seshadrinathan, K., Soundararajan, R., Bovik, A.: LIVE Wireless Video Quality Assessment Database (2009), http://live.ece.utexas.edu/research/quality/live_wireless_video.html

  11. 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., et al. (eds.) ICAISC 2010. LNCS(LNAI), vol. 6113, pp. 539–546. Springer, Heidelberg (2010)

    Chapter  Google Scholar 

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

    Article  Google Scholar 

  13. Shnayderman, A., Gusev, A., Eskicioglu, A.: A multidimensional image quality measure using Singular Value Decomposition. In: Proc. SPIE Image Quality and Syst. Perf., vol. 5294(1), pp. 82–92 (2003)

    Google Scholar 

  14. Shnayderman, A., Gusev, A., Eskicioglu, A.: An SVD-based gray-scale image quality measure for local and global assessment. IEEE Trans. Image Proc. 15(2), 422–429 (2006)

    Article  Google Scholar 

  15. Mahmoudi-Aznaveh, A., Mansouri, A., Torkamani-Azar, F., Eslami, M.: Image quality measurement besides distortion type classifying. Optical Review 16(1), 30–34 (2009)

    Article  Google Scholar 

  16. 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 

  17. Okarma, K.: Colour image quality assessment using the combined full-reference metric. In: Burduk, R., Kurzyński, M., Woźniak, M., Żołnierek, A., et al. (eds.) Computer Recognition Systems 4. Advances in Intelligent and Soft Computing, vol. 95, pp. 287–296. Springer, Heidelberg (2011)

    Chapter  Google Scholar 

  18. Mazurek, P., Okarma, K.: An efficient estimation of the Structural Similarity index using the GPGPU programming techniques. Measurement Automation and Monitoring (PAK) 56(7), 668–670 (2010)

    Google Scholar 

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Okarma, K., Mazurek, P. (2011). GPGPU Based Estimation of the Combined Video Quality Metric. In: Choraś, R.S. (eds) Image Processing and Communications Challenges 3. Advances in Intelligent and Soft Computing, vol 102. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23154-4_32

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  • DOI: https://doi.org/10.1007/978-3-642-23154-4_32

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-23153-7

  • Online ISBN: 978-3-642-23154-4

  • eBook Packages: EngineeringEngineering (R0)

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