Skip to main content
bioRxiv
  • Home
  • About
  • Submit
  • ALERTS / RSS
Advanced Search
New Results

Computational-Observer Analysis of Illumination Discrimination

Xiaomao Ding, Ana Radonjić, Nicolas P. Cottaris, Haomiao Jiang, Brian A. Wandell, David H. Brainard
doi: https://doi.org/10.1101/302315
Xiaomao Ding
1Neuroscience Graduate Group, University of Pennsylvania
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • For correspondence: xiaomao@sas.upenn.edu
Ana Radonjić
2Department of Psychology, University of Pennsylvania
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • For correspondence: radonjic@psych.upenn.edu
Nicolas P. Cottaris
2Department of Psychology, University of Pennsylvania
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • For correspondence: cottaris@psych.upenn.edu
Haomiao Jiang
3Department of Electrical Engineering, Stanford University
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • For correspondence: hjiang36@gmail.com
Brian A. Wandell
4Department of Psychology, Stanford University
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • For correspondence: wandell@stanford.edu
David H. Brainard
2Department of Psychology, University of Pennsylvania
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • For correspondence: brainard@psych.upenn.edu
  • Abstract
  • Full Text
  • Info/History
  • Metrics
  • Preview PDF
Loading

Abstract

The spectral properties of the ambient illumination provide useful information about time of day and weather. We study the perceptual representation of illumination by analyzing measurements of how well people discriminate between illuminations across scene configurations. More specifically, we compare human performance to a computational-observer analysis that evaluates the information available in the isomerizations of the cones in a model human photoreceptor mosaic. Some patterns of human performance are predicted by the computational observer, other aspects are not. The analysis clarifies which aspects of performance require additional explanation in terms of the action of visual mechanisms beyond the isomerization of light by the cones.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
Back to top
PreviousNext
Posted April 16, 2018.
Download PDF
Email

Thank you for your interest in spreading the word about bioRxiv.

NOTE: Your email address is requested solely to identify you as the sender of this article.

Enter multiple addresses on separate lines or separate them with commas.
Computational-Observer Analysis of Illumination Discrimination
(Your Name) has forwarded a page to you from bioRxiv
(Your Name) thought you would like to see this page from the bioRxiv website.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Share
Computational-Observer Analysis of Illumination Discrimination
Xiaomao Ding, Ana Radonjić, Nicolas P. Cottaris, Haomiao Jiang, Brian A. Wandell, David H. Brainard
bioRxiv 302315; doi: https://doi.org/10.1101/302315
Digg logo Reddit logo Twitter logo CiteULike logo Facebook logo Google logo Mendeley logo
Citation Tools
Computational-Observer Analysis of Illumination Discrimination
Xiaomao Ding, Ana Radonjić, Nicolas P. Cottaris, Haomiao Jiang, Brian A. Wandell, David H. Brainard
bioRxiv 302315; doi: https://doi.org/10.1101/302315

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
  • Tweet Widget
  • Facebook Like
  • Google Plus One

Subject Area

  • Neuroscience
Subject Areas
All Articles
  • Animal Behavior and Cognition (2646)
  • Biochemistry (5266)
  • Bioengineering (3678)
  • Bioinformatics (15796)
  • Biophysics (7253)
  • Cancer Biology (5627)
  • Cell Biology (8095)
  • Clinical Trials (138)
  • Developmental Biology (4765)
  • Ecology (7516)
  • Epidemiology (2059)
  • Evolutionary Biology (10576)
  • Genetics (7730)
  • Genomics (10131)
  • Immunology (5193)
  • Microbiology (13905)
  • Molecular Biology (5385)
  • Neuroscience (30779)
  • Paleontology (215)
  • Pathology (879)
  • Pharmacology and Toxicology (1524)
  • Physiology (2254)
  • Plant Biology (5022)
  • Scientific Communication and Education (1041)
  • Synthetic Biology (1385)
  • Systems Biology (4146)
  • Zoology (812)