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International Conference on Computer Vision and Graphics

ICCVG 2014: Computer Vision and Graphics pp 57–65Cite as

Component Weight Tuning of SSIM Image Quality Assessment Measure

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Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 8671))

Abstract

The article describes a method for a parameter tuning for a family of image quality assessment methods based on the concept of SSIM. The method employs curve fitting to model SSIM-MOS relationship then uses inverse relationship to calculate intended measure values and finally the log-log regressive model to estimate parameters for components constituting the measure. The regression was implemented by minimizing of least squares (L2) and least absolute deviation (L1). The results were verified against well tested reference databases.

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References

  1. Charrier, C., Knoblauch, K., Maloney, L.T., Bovik, A.C., Moorthy, A.K.: Optimizing multiscale ssim for compression via mlds. IEEE Transactions on Image Processing 21(12), 4682–4694 (2012)

    Article  MathSciNet  Google Scholar 

  2. D’Errico, J.: Optimization tips and tricks (May 2011), http://www.mathworks.com/matlabcentral/fileexchange/8553

  3. Kandadai, S., Hardin, J., Creusere, C.: Audio quality assessment using the mean structural similarity measure. In: IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2008, pp. 221–224 (2008), 00024

    Google Scholar 

  4. Larson, E.C., Chandler, D.M.: Most apparent distortion: full-reference image quality assessment and the role of strategy. Journal of Electronic Imaging 19(1) (2010)

    Google Scholar 

  5. Lissner, I., Preiss, J., Urban, P., Lichtenauer, M.S., Zolliker, P.: Image-difference prediction: From grayscale to color. IEEE Transactions on Image Processing 22(2), 435–446 (2013)

    Article  MathSciNet  Google Scholar 

  6. Moorthy, A.K., Bovik, A.C.: Perceptually significant spatial pooling techniques for image quality assessment. In: Proc. SPIE 7240, Human Vision and Electronic Imaging XIV, vol. 7240, pp. 724012–724012–11 (2009), 00029

    Google Scholar 

  7. Ponomarenko, N., Lukin, V., Zelensky, A., Egiazarian, K., Carli, M., Battisti, F.: Tid2008 a database for evaluation of full reference visual quality assessment metrics. Advances of Modern Radioelectronics 10(4), 30–45 (2009)

    Google Scholar 

  8. Rice, J.A.: Mathematical statistics and data analysis, 3rd edn. Duxbury advanced series. Thomson/Brooks/Cole, Belmont (2007)

    Google Scholar 

  9. Rouse, D.M., Hemami, S.S.: Understanding and simplifying the structural similarity metric. In: 2008 IEEE Int. Conf. on Image Processing, pp. 1188–1191 (2008)

    Google Scholar 

  10. Sheikh, H., Sabir, M., Bovik, A.: A statistical evaluation of recent full reference image quality assessment algorithms. IEEE Transactions on Image Processing 15(11), 3440–3451 (2006)

    Article  Google Scholar 

  11. Wang, Z., Shang, X.: Spatial pooling strategies for perceptual image quality assessment. In: 2006 IEEE Int. Conf. on Image Processing, pp. 2945–2948 (2006)

    Google Scholar 

  12. Wang, Z., Simoncelli, E., Bovik, A.: Multiscale structural similarity for image quality assessment. In: Conference Records of the 37th Asilomar Conference on Signals, Systems and Computers, vol. 2, pp. 1398–1402. IEEE (2004)

    Google Scholar 

  13. Wang, Z., Bovik, A., Sheikh, H., Simoncelli, E.: Image quality assessment: from error visibility to structural similarity. IEEE Transactions on Image Processing 13(4), 600–612 (2004)

    Article  Google Scholar 

  14. Wang, Z., Li, Q.: Information content weighting for perceptual image quality assessment. IEEE Transactions on Image Processing 20(5), 1185–1198 (2011)

    Article  MathSciNet  Google Scholar 

  15. Wang, Z., Lu, L., Bovik, A.C.: Video quality assessment based on structural distortion measurement. Signal Processing: Image Communication 19(2), 121–132 (2004)

    Google Scholar 

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Author information

Authors and Affiliations

  1. Institute of Informatics, Silesian University of Technology, Gliwice, Poland

    Przemysław Skurowski

  2. Polish-Japanese Institute of Information Technology, Bytom, Poland

    Mateusz Janiak

Authors
  1. Przemysław Skurowski
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  2. Mateusz Janiak
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Editor information

Editors and Affiliations

  1. Faculty of Applied Informatics and Mathematics, Warsaw University of Life Sciences (SGGW), Poland

    Leszek J. Chmielewski

  2. Faculty of Applied Informatics and Mathematics, Warsaw University of Life Sciences - SGGW, Nowoursynowska str. 159, 02-776, Warsaw, Poland

    Ryszard Kozera

  3. The .enpeda.. Project, The University of Auckland, New Zealand

    Bok-Suk Shin

  4. Institute of Computer Science, Silesian University of Technology, Akademicka 16, 44-100, Gliwice, Poland

    Konrad Wojciechowski

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© 2014 Springer International Publishing Switzerland

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Skurowski, P., Janiak, M. (2014). Component Weight Tuning of SSIM Image Quality Assessment Measure. In: Chmielewski, L.J., Kozera, R., Shin, BS., Wojciechowski, K. (eds) Computer Vision and Graphics. ICCVG 2014. Lecture Notes in Computer Science, vol 8671. Springer, Cham. https://doi.org/10.1007/978-3-319-11331-9_8

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  • DOI: https://doi.org/10.1007/978-3-319-11331-9_8

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-11330-2

  • Online ISBN: 978-3-319-11331-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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