ArticleVisual neuroscience
Information limits on neural identification of colored surfaces in natural scenes.
Article in Visual neuroscience. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed.
- Hyperspectral Imaging Database of Human Facial Skin.Applied spectroscopy · 2025Article
- Little information loss with red-green color deficient vision in natural environments.iScience · 2023Article
- Analysis of Hyperspectral Data to Develop an Approach for Document Images.Sensors (Basel, Switzerland) · 2023Review
- Information Flow in Biological Networks for Color Vision.Entropy (Basel, Switzerland) · 2022Article
- Spatio-chromatic information available from different neural layers via Gaussianization.Journal of mathematical neuroscience · 2020Article
- Ultrahigh resolution and color gamut with scattering-reducing transmissive pixels.Nature communications · 2019Article
- What is white?Journal of vision · 2015Article
- A Bayesian model of lightness perception that incorporates spatial variation in the illumination.Journal of vision · 2013Article
- Are Gaussian spectra a viable perceptual assumption in color appearance?Journal of the Optical Society of America. A, Optics, image science, and vision · 2012Article
- The brightness of colour.PloS one · 2009Article
- The relation between color discrimination and color constancy: when is optimal adaptation task dependent?Neural computation · 2007Article
- Frequency of metamerism in natural scenes.Journal of the Optical Society of America. A, Optics, image science, and vision · 2006Article
- Color constancy in natural scenes explained by global image statistics.Visual neuroscienceArticle
- Anomalous trichromats' judgments of surface color in natural scenes under different daylights.Visual neuroscienceArticle
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Authors and funding
3 authors.
Funding
Abstract
If surfaces in a scene are to be distinguished by their color, their neural representation at some level should ideally vary little with the color of the illumination. Four possible neural codes were considered: von-Kries-scaled cone responses from single points in a scene, spatial ratios of cone responses produced by light reflected from pairs of points, and these quantities obtained with sharpened (opponent-cone) responses. The effectiveness of these codes in identifying surfaces was quantified by information-theoretic measures. Data were drawn from a sample of 25 rural and urban scenes imaged with a hyperspectral camera, which provided estimates of surface reflectance at 10-nm intervals at each of 1344 x 1024 pixels for each scene. In computer simulations, scenes were illuminated separately by daylights of correlated color temperatures 4000 K, 6500 K, and 25,000 K. Points were sampled randomly in each scene and identified according to each of the codes. It was found that the maximum information preserved under illuminant changes varied with the code, but for a particular code it was remarkably stable across the different scenes. The standard deviation over the 25 scenes was, on average, approximately 1 bit, suggesting that the neural coding of surface color can be optimized independent of location for any particular range of illuminants.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.