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Color Vision

Color Vision

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.

Photoreceptors and Visual Pathways

Photoreceptors and Visual Pathways

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, whereas...

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Color distribution from multicolor LED arrays.

Ivan Moreno, Ulises Contreras

|June 18, 2009

Summary

This study presents an analytical method to predict light color patterns from multicolor LED assemblies. The findings aid in optimizing LED array design and diffuser placement for effective color mixing in lighting systems.

Area of Science:

Optics and Photonics
Lighting Technology
Color Science

Background:

Multicolor light-emitting diode (LED) assemblies are widely used in lighting.
Accurate prediction of color patterns and correlated color temperature (CCT) is crucial for lighting design.
Existing methods may lack simplicity or sufficient accuracy for complex array configurations.

Purpose of the Study:

To develop a fully-analytical and accurate method for computing the color patterns of light emitted from multicolor LED assemblies.
To analyze the spatial distributions of color variation and CCT based on various influencing parameters.
To provide a tool for optimizing LED array configuration and diffuser distance in lighting systems.

Main Methods:

Developed a simple, fully-analytical method for color pattern computation.

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Investigated spatial distributions of color variation and CCT.

Simulated and analyzed color patterns for linear, ring, and square RGB arrays.

Considered different LED radiation patterns (Lambertian, batwing, side-emitting).

Main Results:

Demonstrated the capability to compute spatial distributions of color variation and CCT.
Showcased analysis for various array configurations (linear, ring, square) and LED types.
Identified key parameters influencing color patterns, including LED spectrum, radiation distribution, target distance, spacing, and number of LEDs.

Conclusions:

The proposed analytical method offers a simple yet accurate approach to predict color patterns in multicolor LED lighting.
The findings are valuable for selecting optimal array configurations and diffuser distances.
This work supports the design of advanced lighting systems with precise color mixing capabilities.