The DOI matches its Crossref record; 14 of the 14 references it cites were found in a registry or an index.
A no-reference perceptual image sharpness metric based on a cumulative probability of blur detection
Abstract
In this paper, a no-reference objective sharpness metric based on a cumulative probability of blur detection is proposed. The metric is evaluated by taking into account the human visual system (HVS) response to blur distortions. The perceptual significance of the metric is validated through subjective experiments. It is shown that the proposed metric results in a very good correlation with subjective scores especially for images with varying foreground and background perceived blur qualities. This is accomplished with a significantly lower computational complexity as compared to existing methods that take into account the visual attention information.
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“Cumulative Probability Blur Detection (CPBD) [119], a non-reference measure, is also widely used to evaluate the loss of sharpness during video generation.”
From Deep learning for visual speech analysis: A survey (2024) · cites this paper as [119]
Citations
Cites
A model of saliency-based visual attention for rapid scene analysis
Itti, L., Christof Koch, A., & Niebur, E. (1998) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/34.730558 · Cited by 11,289
Modeling attention to salient proto-objects
Walther, D. B., & Koch, C. (2006) · Neural Networks · doi:10.1016/j.neunet.2006.10.001 · Cited by 1,256
A no-reference objective image sharpness metric based on the notion of just noticeable blur (JNB)
Ferzli, R., & Karam, L. J. (2009) · IEEE Transactions on Image Processing · doi:10.1109/tip.2008.2011760 · Cited by 758
Self-citationNo-reference quality assessment using natural scene statistics: JPEG2000
Sheikh, H. R., Bovik, A. C., & Cormack, L. (2005) · IEEE Transactions on Image Processing · doi:10.1109/tip.2005.854492 · Cited by 575
A no-reference perceptual blur metric
Marziliano, P., Frederic Dufaux, A., WINKLER, S. S., & Ebrahimi, T. (2003) · Proceedings - International Conference on Image Processing · doi:10.1109/icip.2002.1038902 · Cited by 568
Digital Video Quality: Vision Models and Metrics
WINKLER, S. S. (2005) · Cited by 388
Objective video quality assessment
(2003) · Handbook of Video Databases · doi:10.1201/9780203489864-45 · Cited by 359
WINKLER, S. S. (2005) · Wiley eBooks · doi:10.1002/9780470024065 · Cited by 331
A survey of hybrid MC/DPCM/DCT video coding distortions
Yuen, M., & Wu, H. R. (1998) · Signal Processing · doi:10.1016/s0165-1684(98)00128-5 · Cited by 254
No-reference sharpness metric based on local edge kurtosis
Caviedes, J. E., & Gurbuz, S. (2003) · Proceedings - International Conference on Image Processing · doi:10.1109/icip.2002.1038901 · Cited by 141
Research works printed but not linked: 2
- 2000, Final report from the video quality experts group on the validation of objective models of video quality assessment
- sheikh, 2003, LIVE Image Quality Assessment Database
Cited by
Sorted by citations
No-Reference Image Quality Assessment in the Spatial Domain
Mittal, A., Moorthy, A. K., & Bovik, A. C. (2012) · IEEE Transactions on Image Processing · doi:10.1109/tip.2012.2214050 · Cited by 6,064
Blind Image Quality Assessment: From Natural Scene Statistics to Perceptual Quality
Moorthy, A. K., & Bovik, A. C. (2011) · IEEE Transactions on Image Processing · doi:10.1109/tip.2011.2147325 · Cited by 1,763
Blind/Referenceless Image Spatial Quality Evaluator
Mittal, A., Moorthy, A. K., & Bovik, A. C. (2011) · Asilomar Conference on Signals, Systems and Computers (ACSSC) · doi:10.1109/acssc.2011.6190099 · Cited by 446
Seven Challenges in Image Quality Assessment: Past, Present, and Future Research
Chandler, D. M. (2013) · ISRN Signal Processing · doi:10.1155/2013/905685 · Cited by 427
${\bf S}_{3}$: A Spectral and Spatial Measure of Local Perceived Sharpness in Natural Images
Vu, C. T., Phan, T. D., & Chandler, D. M. (2011) · IEEE Transactions on Image Processing · doi:10.1109/tip.2011.2169974 · Cited by 388
Metadata
- Authors
- Narvekar, N. D., & Karam, L. J.
- Affiliations
- Arizona State University (US)
- ORCID
- Karam, Lina J.
- Venue
- 2009 International Workshop on Quality of Multimedia Experience
- Publisher
- IEEE
- Published
- 2009-07
- Pages
- 87-91
- OpenAlex
- W2162220380
- Cited by
- 208
- References
- 14
- Citations by year
- 2026: 4 · 2025: 9 · 2024: 15 · 2023: 26 · 2022: 17 · 2021: 14 · 2020: 20 · 2019: 12 · 2018: 9 · 2017: 11 · 2016: 14 · 2015: 12 · 2014: 13 · 2013: 12 · 2012: 11
- FWCI
- 5.44
- 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 › Advanced Image Processing Techniques
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Image Retrieval and Classification Techniques
- Keywords
- no-reference image quality assessment, blur detection, cumulative probability, human visual system, perceptual image quality, visual attention, computational complexity
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