Reduced-reference image quality assessment using a wavelet-domain natural image statistic model

Zhou Wang, Eero Simoncelli

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Reduced-reference (RR) image quality measures aim to predict the visual quality of distorted images with only partial information about the reference images. In this paper, we propose an RR image quality assessment method based on a natural image statistic model in the wavelet transform domain. We use the Kullback-Leibler distance between the marginal probability distributions of wavelet coefficients of the reference and distorted images as a measure of image distortion. A generalized Gaussian model is employed to summarize the marginal distribution of wavelet coefficients of the reference image, so that only a relatively small number of RR features are needed for the evaluation of image quality. The proposed method is easy to implement and computationally efficient. In addition, we find that many well-known types of image distortions lead to significant changes in wavelet coefficient histograms, and thus are readily detectable by our measure. A Matlab implementation of the method has been made available online at http://www.cns.nyu.edu/~lcv/rriqa/.

Original languageEnglish (US)
Title of host publicationProceedings of SPIE - The International Society for Optical Engineering
EditorsB.E. Rogowitz, T.N. Pappas, S.J. Daly
Pages149-159
Number of pages11
Volume5666
DOIs
StatePublished - 2005
EventProceedings of SPIE-IS and T Electronic Imaging - Human Vision and Electronic Imaging X - San Jose, CA, United States
Duration: Jan 17 2005Jan 20 2005

Other

OtherProceedings of SPIE-IS and T Electronic Imaging - Human Vision and Electronic Imaging X
CountryUnited States
CitySan Jose, CA
Period1/17/051/20/05

Fingerprint

Image quality
Statistics
statistics
Wavelet transforms
Probability distributions
coefficients
histograms
wavelet analysis
evaluation

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Condensed Matter Physics

Cite this

Wang, Z., & Simoncelli, E. (2005). Reduced-reference image quality assessment using a wavelet-domain natural image statistic model. In B. E. Rogowitz, T. N. Pappas, & S. J. Daly (Eds.), Proceedings of SPIE - The International Society for Optical Engineering (Vol. 5666, pp. 149-159). [20] https://doi.org/10.1117/12.597306

Reduced-reference image quality assessment using a wavelet-domain natural image statistic model. / Wang, Zhou; Simoncelli, Eero.

Proceedings of SPIE - The International Society for Optical Engineering. ed. / B.E. Rogowitz; T.N. Pappas; S.J. Daly. Vol. 5666 2005. p. 149-159 20.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Wang, Z & Simoncelli, E 2005, Reduced-reference image quality assessment using a wavelet-domain natural image statistic model. in BE Rogowitz, TN Pappas & SJ Daly (eds), Proceedings of SPIE - The International Society for Optical Engineering. vol. 5666, 20, pp. 149-159, Proceedings of SPIE-IS and T Electronic Imaging - Human Vision and Electronic Imaging X, San Jose, CA, United States, 1/17/05. https://doi.org/10.1117/12.597306
Wang Z, Simoncelli E. Reduced-reference image quality assessment using a wavelet-domain natural image statistic model. In Rogowitz BE, Pappas TN, Daly SJ, editors, Proceedings of SPIE - The International Society for Optical Engineering. Vol. 5666. 2005. p. 149-159. 20 https://doi.org/10.1117/12.597306
Wang, Zhou ; Simoncelli, Eero. / Reduced-reference image quality assessment using a wavelet-domain natural image statistic model. Proceedings of SPIE - The International Society for Optical Engineering. editor / B.E. Rogowitz ; T.N. Pappas ; S.J. Daly. Vol. 5666 2005. pp. 149-159
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