Jove
Visualize
Contact Us

Related Concept Videos

Color Vision01:24

Color Vision

368
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.
368
Photoreceptors and Visual Pathways01:22

Photoreceptors and Visual Pathways

5.4K
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,...
5.4K

You might also read

Related Articles

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

Sort by
Same author

HyperHazeOff: Hyperspectral Remote Sensing Image Dehazing Benchmark.

Journal of imaging·2025
Same author

Leveraging Achromatic Component for Trichromat-Friendly Daltonization.

Journal of imaging·2025
Same author

OrgNet: orientation-gnostic protein stability assessment using convolutional neural networks.

Bioinformatics (Oxford, England)·2025
Same author

Formulae Differences Commence a Database for Interlaboratory Studies of Natural Organic Matter.

Environmental science & technology·2023
Same author

Aromaticity Index with Improved Estimation of Carboxyl Group Contribution for Biogeochemical Studies.

Environmental science & technology·2022
Same author

Structure-Preserving and Perceptually Consistent Approach for Visualization of Mass Spectrometry Imaging Datasets.

Analytical chemistry·2020
Same journal

Human-AI Interaction in Interventional Radiology: A Narrative Review of Current Applications, Challenges, and Future Directions.

Journal of imaging·2026
Same journal

Coronary Artery Anomalies and Anatomical Variants: Cross-Sectional Diagnostic Imaging and Clinical Background.

Journal of imaging·2026
Same journal

YoLeTooth: A Unified Framework for Joint Tooth Segmentation and Periapical Lesion Detection in Panoramic Radiographs.

Journal of imaging·2026
Same journal

Radiomics-Guided Multi-Sequence Learning for Pathological Complete Response Prediction from Breast MRI with Missing Auxiliary Sequences.

Journal of imaging·2026
Same journal

Cutaneous Thermography in Arthropathies: Quantitative Imaging, Machine Learning, and Clinical Translation.

Journal of imaging·2026
Same journal

Two-Stage Dynamic Synergistic Segmentation Method for Myocardial Pathology.

Journal of imaging·2026
See all related articles
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 Experiment Video

Updated: May 8, 2025

Visualizing Visual Adaptation
04:43

Visualizing Visual Adaptation

Published on: April 24, 2017

8.9K

Evaluation of Color Difference Models for Wide Color Gamut and High Dynamic Range.

Olga Basova1,2, Sergey Gladilin1,3, Vladislav Kokhan3

  • 1Federal Research Center "Computer Science and Control" of the Russian Academy of Sciences, 119333 Moscow, Russia.

Journal of Imaging
|December 27, 2024
PubMed
Summary
This summary is machine-generated.

New research validates color difference models (CDMs) for wide color gamut (WCG) and high dynamic range (HDR) imaging. The CAM16-UCS model shows promise but requires further refinement for accurate color reproduction.

Keywords:
color difference datasetcolor difference modelcolor model evaluationgray-scale methodhigh dynamic rangestrict substitutionwide color gamut

More Related Videos

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

9.3K
Applying Hyperspectral Reflectance Imaging to Investigate the Palettes and the Techniques of Painters
07:05

Applying Hyperspectral Reflectance Imaging to Investigate the Palettes and the Techniques of Painters

Published on: June 18, 2021

2.3K

Related Experiment Videos

Last Updated: May 8, 2025

Visualizing Visual Adaptation
04:43

Visualizing Visual Adaptation

Published on: April 24, 2017

8.9K
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

9.3K
Applying Hyperspectral Reflectance Imaging to Investigate the Palettes and the Techniques of Painters
07:05

Applying Hyperspectral Reflectance Imaging to Investigate the Palettes and the Techniques of Painters

Published on: June 18, 2021

2.3K

Area of Science:

  • Color science
  • Image processing
  • Perceptual color modeling

Background:

  • Color difference models (CDMs) are crucial for accurate color reproduction.
  • Current CDMs are inadequately tested in wide color gamut (WCG) and high dynamic range (HDR) environments due to dataset limitations.
  • Existing datasets often lack coverage of diverse color difference (CD) magnitudes, particularly larger ones.

Purpose of the Study:

  • To validate and improve CDMs for WCG and HDR contexts.
  • To develop a novel CDM tailored to psychophysical data from WCG and HDR.
  • To assess CDM performance across a broad spectrum of color differences.

Main Methods:

  • Collected a new dataset with a wide range of CDs in WCG and HDR.
  • Developed and fitted a novel CDM to the new dataset.
  • Benchmarked multiple CDMs using STRESS and error fraction metrics on existing and new datasets.

Main Results:

  • CAM16-UCS with power correction demonstrated the best overall performance among evaluated CDMs.
  • The model performed well across WCG colors up to 1611 cd/m².
  • Despite strong performance, even the best models exhibited significant errors and did not meet desired accuracy limits.

Conclusions:

  • CAM16-UCS is a versatile CDM for WCG and HDR but needs further refinement.
  • Improvements are particularly needed in the power correction component to better model the non-geodesic nature of perceptual color space.
  • Further research is essential to enhance CDM accuracy for advanced display technologies.