Statistical Modeling of Photographic Images
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Natural images have characteristic statistical properties such as self-similarity across scales and heavy tailed wavelet marginal distributions that do not occur in synthetic videos of these types.
“Natural images have several characteristic statistical properties such as self-similarity across scales, heavy tailed wavelet marginal distributions and so on [70], [76], that do not occur in synthetic videos of these types.”
From Motion Tuned Spatio-Temporal Quality Assessment of Natural Videos (2010) · cites this paper as [76]
Cites
The Nonlinear Statistics of High-Contrast Patches in Natural Images
Lee, A. B., Pedersen, K. S., & Mumford, D. (2003) · International Journal of Computer Vision · doi:10.1023/a:1023705401078 · Cited by 234 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Deep learning for visual understanding: A review
Guo, Y., Liu, Y., Oerlemans, A., Lao, S., Wu, S., & Lew, M. S. (2016) · Neurocomputing · doi:10.1016/j.neucom.2015.09.116 · Cited by 2,504 · see citing works
Efficient Learning of Sparse Representations with an Energy-Based Model
Ranzato, M., Poultney, C., Chopra, S., & LeCun, Y. (2007) · Advances in Neural Information Processing Systems 19 · doi:10.7551/mitpress/7503.003.0147 · Cited by 1,106 · see citing works
Modern Image Quality Assessment
Wang, Z., & Bovik, A. C. (2006) · Synthesis Lectures on Image, Video, and Multimedia Processing · doi:10.1007/978-3-031-02238-8 · Cited by 967 · see citing works
Motion Tuned Spatio-Temporal Quality Assessment of Natural Videos
Seshadrinathan, K., & Bovik, A. C. (2010) · IEEE Transactions on Image Processing · doi:10.1109/tip.2009.2034992 · Cited by 708 · see citing works
On deep generative models with applications to recognition
Ranzato, M., Susskind, J., Mnih, V., & Hinton, G. (2011) · CVPR 2011 · doi:10.1109/cvpr.2011.5995710 · Cited by 237 · see citing works
- Authors
- Simoncelli, E. P.
- Affiliations
- New York University (US)
- Corresponding author
- Simoncelli, Eero P.
- ORCID
- Simoncelli, Eero P.
- Venue
- Handbook of Image and Video Processing
- Publisher
- Elsevier
- Published
- 2005
- Pages
- 431-441
- OpenAlex
- W11828546
- Cited by
- 93
- References
- 1
- Citations by year
- 2023: 5 · 2022: 5 · 2021: 1 · 2020: 1 · 2019: 1 · 2018: 5 · 2017: 5 · 2016: 3 · 2015: 6 · 2014: 8 · 2013: 4 · 2012: 6
- FWCI
- 10.31
- Type
- book chapter
- Language
- en
- Open access
- closed
- Locations
- Elsevier eBooks (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Image and Signal Denoising Methods
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Image Retrieval and Classification Techniques
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Image and Video Quality Assessment
- Keywords
- natural image statistics, image denoising, image compression, image generation, image enhancement
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
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