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Statistics of natural images: Scaling in the woods
Abstract
We study the statistics of an ensemble of images taken in the woods. Distributions of local quantities such as contrast are scale invariant and have nearly exponential tails. Power spectra exhibit scaling with a nontrivial exponent. These data limit the information content of natural images and point to the importance of gain-control strategies in visual processing.
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Cited by
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
A Parametric Texture Model Based on Joint Statistics of Complex Wavelet Coefficients
Portilla, J., & Simoncelli, E. P. (2000) · International Journal of Computer Vision · doi:10.1023/a:1026553619983 · Cited by 1,806
Independent component filters of natural images compared with simple cells in primary visual cortex
van Hateren, J. H., & van der Schaaf, A. (1998) · Proceedings of the Royal Society of London. Series B: Biological Sciences · doi:10.1098/rspb.1998.0303 · Cited by 1,106
Natural signal statistics and sensory gain control
Schwartz, O., & Simoncelli, E. P. (2001) · Nature Neuroscience · doi:10.1038/90526 · Cited by 835
ConViT: improving vision transformers with soft convolutional inductive biases
d’Ascoli, S., Touvron, H., Leavitt, M. L., Morcos, A. S., Biroli, G., & Sagun, L. (2022) · Journal of Statistical Mechanics: Theory and Experiment · doi:10.1088/1742-5468/ac9830 · Cited by 782
Metadata
- Authors
- Ruderman, D. L., & Bialek, W.
- Venue
- Physical Review Letters
- Publisher
- American Physical Society (APS)
- Published
- 1994-08-08
- Volume
- 73
- Issue
- 6
- Pages
- 814-817
- ISSN
- 0031-9007 (ISSN-L)
- OpenAlex
- W2042755403
- Cited by
- 920
- References
- 0
- FWCI
- 8.02
- Type
- journal article
- Language
- en
- Open access
- closed
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
