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A statistical reduced-reference method for color image quality assessment

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Abstract

Although color is a fundamental feature of human visual perception, it has been largely unexplored in the reduced-reference (RR) image quality assessment (IQA) schemes. In this paper, we propose a natural scene statistic (NSS) method, which efficiently uses this information. It is based on the statistical deviation between the steerable pyramid coefficients of the reference color image and the degraded one. We propose and analyze the multivariate generalized Gaussian distribution (MGGD) to model the underlying statistics. In order to quantify the degradation, we develop and evaluate two measures based respectively on the Geodesic distance between two MGGDs and on the closed-form of the Kullback Leibler divergence. We performed an extensive evaluation of both metrics in various color spaces (RGB, HSV, CIELAB and YCrCb) using the TID 2008 benchmark and the FRTV Phase I validation process. Experimental results demonstrate the effectiveness of the proposed framework to achieve a good consistency with human visual perception. Furthermore, the best configuration is obtained with CIELAB color space associated to KLD deviation measure.

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References

  1. Abramowitz M, Stegun I (1965) Handbook of Mathematical Functions. Dover Publications, New York

    Google Scholar 

  2. CIE Publ. 15-2004, 3 Edition, Colorimetry. (CIE Central Bureau, Rd Vienna, 2004)

  3. Color Science (1982) Concepts and methods, quantitative data and formulae. Wyszecki and Stiles. Wiley

  4. Decherchi S, Gastaldo P, Redi JA, Zunino R (2013) E Cambria: circular-ELM for the reduced-reference assessment of perceived image quality neurocomputing 102:78–89

  5. Fang KT, Kotz S, Ng KW (1990) Symmetric multivariate and related distributions, monographs on statistics and applied probability, vol 36. Chapman and Hall, New York

    Book  Google Scholar 

  6. He L, Wang D, Li X, Tao D, Gao X, Gao F (2012) Color fractal structure model for reduced-reference colorful image quality assessment. ICONIP 2:401–408

    Google Scholar 

  7. http://www.vqeg.org, VQEG RRNR-TV Group TEST PLAN, Draft version 1.7, 2004.6.21[EB/OL], 2005.1.10

  8. Li Q, Wang Z (2009) Reduced-reference image quality assessment using divisive normalization-based image representation. IEEE J Sel Topics Signal Process 3:202–211

    Article  Google Scholar 

  9. Omari M, Abdelouahad AA, El Hassouni M, Cherifi H (2013) Color image quality assessment measure using multivariate generalized gaussian distribution. SITIS:195–200

  10. Ponomarenko N, Carli M, Lukin V, Egiazarian K, Astola J, Battisti F (2008) Color image database for evaluation of image quality metrics. In: Int. workshop on multimedia signal processing. Australia

  11. Redi J, Gastaldo PI, Heynderickx I, Zunino R (2010) Color distribution information for the reduced-reference assessment of perceived image quality. IEEE Trans Circ Syst Video Technol 20(12):1745–1756

    Article  Google Scholar 

  12. Sheikh H, Wang Z, Cormack L, Bovik A (2005) LIVE image quality assessment database. Retrieved from http://live.ece.utexas.edu/research/quality

  13. Simoncelli EP, Freeman WT, Adelson EH, Heeger DJ (1992) Shiftable multi-scale transforms. IEEE Trans Inf Theory 38(2):587–607

    Article  MathSciNet  Google Scholar 

  14. Soundararajan R, Bovik AC (2012) RRED indices: reduced reference entropic differencing for image quality assessment. IEEE Trans Image Process 21(2):517–526

    Article  MathSciNet  Google Scholar 

  15. Verdoolaege G, Scheunders P (2011) Geodesics on the manifold of multivariate generalized gaussian distributions with an application to multicomponent texture discrimination. Int J Comput Vis 95(3):265–286

    Article  Google Scholar 

  16. Verdoolaege G., Rosseel Y, Lambrechts M, Scheunders P (2009) Wavelet-based colour texture retrieval using the kullback-leibler divergence between bivariate generalized Gaussian models. ICIP:265–268

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

  18. Wang Z, Wu G, Sheikh HR, Simoncelli EP, Yang EH, Bovik AC (2006) Quality-aware images. IEEE Trans Image Process 15(5):1680–1689

    Article  MATH  Google Scholar 

Download references

Acknowledgments

This work has been supported by the project CNRS-CNRST STIC 02/2014.

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Correspondence to Mohammed El Hassouni.

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Omari, M., Hassouni, M.E., Abdelouahad, A.A. et al. A statistical reduced-reference method for color image quality assessment. Multimed Tools Appl 74, 8685–8701 (2015). https://doi.org/10.1007/s11042-014-2353-z

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  • DOI: https://doi.org/10.1007/s11042-014-2353-z

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