Reduced reference image quality assessment based on Weibull statistics
Abstract
Theories in fragmentation have proved that the statistics of image gradient magnitude followed a Weibull distribution, with β (scale) and γ (shape) as free parameters, which are demonstrated to be strongly correlated with brain response. In this paper, we chose β extracted from the proposed strongest component map (SCM) in scale space, as the reduced reference (RR) feature, and developed a novel method for reduced reference image quality assessment (RRIQA) named βW-SCM. For each scale, the SCM was constructed by assembling coefficients with maximum amplitude among different orientations into a single map. The Weibull parameters were then estimated from the SCM. The final image quality was computed by summing the geometric mean of the defined absolute and relative deviations of β. Performance evaluation on the well-known LIVE database demonstrated an outstanding advantage of low RR feature data rate with nearly the same prediction accuracy and consistency.
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The algorithm based on Weibull statistics of wavelet coefficients achieves good performance at a given data rate.
“The algorithm by [20] based on Weibull statistics of wavelet coefficients achieves good performance at a given data rate.”
From RRED Indices: Reduced Reference Entropic Differencing for Image Quality Assessment (2012) · cites this paper as [20]
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Image quality assessment: from error visibility to structural similarity
Wang, Z., Bovik, A. C., Sheikh, H. R., & Simoncelli, E. P. (2004) · IEEE Transactions on Image Processing · doi:10.1109/tip.2003.819861 · Cited by 57,892 · see citing works
Natural Image Statistics and Neural Representation
Simoncelli, E. P., & Olshausen, B. A. (2001) · Annual Review of Neuroscience · doi:10.1146/annurev.neuro.24.1.1193 · Cited by 2,460 · see citing works
Wang, Z., Wu, G., Sheikh, H. R., Simoncelli, E. P., Yang, E.-H., & Bovik, A. C. (2006) · IEEE Transactions on Image Processing · doi:10.1109/tip.2005.864165 · Cited by 293 · see citing works
Objective quality assessment of color images based on a generic perceptual reduced reference
Carnec, M., Le Callet, P., & Barba, D. (2008) · Signal Processing: Image Communication · doi:10.1016/j.image.2008.02.003 · Cited by 124 · see citing works
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Blind Image Quality Assessment Using Joint Statistics of Gradient Magnitude and Laplacian Features
Xue, W., Mou, X., Zhang, L., Bovik, A. C., & Feng, X. (2014) · IEEE Transactions on Image Processing · doi:10.1109/tip.2014.2355716 · Cited by 641 · see citing works
Self-citationRRED Indices: Reduced Reference Entropic Differencing for Image Quality Assessment
Soundararajan, R., & Bovik, A. C. (2012) · IEEE Transactions on Image Processing · doi:10.1109/tip.2011.2166082 · Cited by 337 · see citing works
Zhang, Y., Moorthy, A. K., Chandler, D. M., & Bovik, A. C. (2014) · Signal Processing: Image Communication · doi:10.1016/j.image.2014.05.004 · Cited by 102 · see citing works
- Authors
- Xue, W., & Mou, X.
- Affiliations
- Xi'an Jiaotong University (CN)
- Venue
- 2010 Second International Workshop on Quality of Multimedia Experience (QoMEX)
- Publisher
- IEEE
- Published
- 2010-06
- Pages
- 1-6
- OpenAlex
- W2064282387
- Cited by
- 47
- References
- 4
- Citations by year
- 2025: 1 · 2022: 2 · 2021: 1 · 2020: 1 · 2019: 1 · 2018: 3 · 2017: 4 · 2016: 4 · 2015: 5 · 2014: 7 · 2013: 4 · 2012: 8
- FWCI
- 4.94
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- International Conference on Quality of Multimedia Experience (QoMEX) (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Image and Video Quality Assessment
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Image Retrieval and Classification Techniques
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Digital Media Forensic Detection
- Keywords
- reduced-reference image quality assessment, Weibull distribution, scale space, scale parameter estimation, brain responses, LIVE database
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