Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Color Vision01:24

Color Vision

1.2K
Color perception begins in the retina, the light-sensitive layer at the back of the eye. Two main theories explain how colors are seen: the trichromatic theory and the opponent-process theory. The trichromatic theory, proposed by Thomas Young in 1802 and extended by Hermann von Helmholtz in 1852, suggests that color vision is based on three types of cone receptors in the retina. These cones are sensitive to different but overlapping ranges of wavelengths corresponding to red, blue, and green.
1.2K
Photoreceptors and Visual Pathways01:22

Photoreceptors and Visual Pathways

8.3K
At the molecular level, visual signals trigger transformations in photopigment molecules, resulting in changes in the photoreceptor cell's membrane potential. The photon's energy level is denoted by its wavelength, with each specific wavelength of visible light associated with a distinct color. The spectral range of visible light, classified as electromagnetic radiation, spans from 380 to 720 nm. Electromagnetic radiation wavelengths exceeding 720 nm fall under the infrared category,...
8.3K
Difference from Background: Limit of Detection01:05

Difference from Background: Limit of Detection

7.9K
The limit of detection (LOD) is the smallest amount of analyte that can be distinguished from the background noise. The LOD value corresponds to the concentration at which the analyte signal is three times larger than the standard deviation of the blank signal. Below this value, the analyte signal cannot be differentiated from the background noise. It is calculated by dividing the calibration slope by 3 times the standard deviation of the blank signals.
The LOD indicates the presence or absence...
7.9K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Evaluating and reducing observer metamerism on displays.

Optics express·2025
Same author

Individual color matches and cone spectral sensitivities in 100 observers of varying age.

Optics express·2025
Same author

Visual comfort models based on coloured text and neutral background combinations.

Vision research·2024
Same author

Generic color correction for tone mapping operators in high dynamic range imaging.

Optics express·2024
Same author

Individual differences in color matches and cone spectral sensitivities in 51 young adults.

Optics express·2024
Same author

Optimized principal component analysis for camera spectral sensitivity estimation.

Journal of the Optical Society of America. A, Optics, image science, and vision·2023

Related Experiment Video

Updated: Dec 13, 2025

Enabling High Grayscale Resolution Displays and Accurate Response Time Measurements on Conventional Computers
06:50

Enabling High Grayscale Resolution Displays and Accurate Response Time Measurements on Conventional Computers

Published on: February 29, 2012

9.6K

Color difference evaluation for wide-color-gamut displays.

Baiyue Zhao, Qiang Xu, Ming Ronnier Luo

    Journal of the Optical Society of America. A, Optics, Image Science, and Vision
    |August 5, 2020
    PubMed
    Summary

    New research shows that CAM02-UCS is superior for predicting color differences in wide-color-gamut displays, outperforming traditional methods like CIELAB and CIEDE2000 in highly saturated regions.

    Area of Science:

    • Color Science
    • Display Technology
    • Human Visual Perception

    Background:

    • Traditional color difference formulas struggle with wide-color-gamut (WCG) displays due to limitations in predicting color perception in highly saturated regions.
    • Existing uniform color spaces were often developed using data from smaller color gamuts, limiting their accuracy for modern display technologies.

    Purpose of the Study:

    • To evaluate the performance of various uniform color spaces and color difference equations on a WCG display.
    • To identify the most reliable method for predicting color differences in highly saturated color regions relevant to WCG applications.

    Main Methods:

    • A psychophysical experiment was conducted at 310 cd/m² luminance on a DCI-P3 WCG display.
    • 192 sample pairs across 12 color centers were judged by 18 observers using the grayscale psychophysical method.

    More Related Videos

    Visualizing Visual Adaptation
    04:43

    Visualizing Visual Adaptation

    Published on: April 24, 2017

    9.5K
    Qualitative Identification of Carboxylic Acids, Boronic Acids, and Amines Using Cruciform Fluorophores
    09:46

    Qualitative Identification of Carboxylic Acids, Boronic Acids, and Amines Using Cruciform Fluorophores

    Published on: August 19, 2013

    15.9K

    Related Experiment Videos

    Last Updated: Dec 13, 2025

    Enabling High Grayscale Resolution Displays and Accurate Response Time Measurements on Conventional Computers
    06:50

    Enabling High Grayscale Resolution Displays and Accurate Response Time Measurements on Conventional Computers

    Published on: February 29, 2012

    9.6K
    Visualizing Visual Adaptation
    04:43

    Visualizing Visual Adaptation

    Published on: April 24, 2017

    9.5K
    Qualitative Identification of Carboxylic Acids, Boronic Acids, and Amines Using Cruciform Fluorophores
    09:46

    Qualitative Identification of Carboxylic Acids, Boronic Acids, and Amines Using Cruciform Fluorophores

    Published on: August 19, 2013

    15.9K
  • Six color spaces/equations (CIELAB, CIEDE2000, CAM02-UCS, Jab, ICC, nICC) were tested for local and global uniformity using color discrimination ellipses.

    • Main Results:

    • All tested color difference formulas showed improved performance with a mean lightness parametric factor around 0.5.
    • CAM02-UCS demonstrated significantly superior overall, local, and global uniformity compared to other methods.
    • The study generated a high-quality visual dataset for future color difference formula development.

    Conclusions:

    • CAM02-UCS is the most effective color space for accurately predicting color differences on wide-color-gamut displays.
    • The developed dataset provides a valuable resource for advancing color science in WCG display applications.
    • Further research is recommended to derive new color difference formulas optimized for WCG displays.