You might’ve heard that color is highly subjective. Working in the color management industry, our team is quite familiar with this fact. But don’t just take our word for it. Today, we’re launching a new series where we dive into the science behind color perception and the many factors that impact how we see (which, by the way, is not exactly the same as how our friends or neighbors or coworkers see).
Today’s post explores some of the basics of color vision and perception. Later, we’ll go into physical factors that impact color perception. Finally, we’ll cover environmental factors.
We hope you’ll walk away with a better understanding of why we so often disagree when it comes to color.
How we see
We see thanks to photoreceptor cells in the retinas of our eyes that transmit signals to our brains. Highly sensitive rods allow us to see at very low light levels – but in shades of gray. To see color, we need brighter light and cone cells that respond to roughly three different wavelengths:
- Short (S) – blue spectrum (absorption peak ≈ 445 nm)
- Medium (M) – green spectrum (absorption peak ≈ 535 nm)
- Long (L) – red spectrum (absorption peak ≈ 565 nm)
This is the basis of trichromatic theory, also called Young-Helmholtz after the researchers who developed it. It was only confirmed in the 1960s.
Opponent process theory postulates that color vision depends upon three receptor complexes with opposite actions: light/dark (white/black), red/green, and blue/yellow. Together, the two theories help describe the complexity of our perception of color.
Perceived color depends upon how an object absorbs and reflects wavelengths. Human beings can only see a small portion of the electromagnetic spectrum, from about 400 nm to 700 nm, but it’s enough to allow us to see millions of colors.
Subjectivity in color perception
We’re pretty good at recognizing the color of familiar objects even as lighting circumstances change. This adaptation of eye and brain is known as color constancy. It doesn’t apply to subtle color variations, though, or counteract the changes in color due to intensity or quality of light.
We might also be able to agree with each other on the wavelengths that define basic colors. This might have more to do with our brains than our eyes. For instance, in a 2005 study at the University of Rochester, individuals tended to perceive colors the same way even though their number of cones in their retinas varied widely. When volunteers were asked to tune a disk to what they’d describe as “pure yellow” light, everyone selected nearly the same wavelength.
But things get much more complicated when individuals or multiple people try to match colors to samples. Physical/environmental factors and personal differences among viewers can alter perception. These factors include:
|· Light source· Background|
|· Age· Medications|
Mathematics of color
Since environmental and personal factors influence color perception, we can’t be assured of accurate matches when we’re comparing colors visually to a standard sample. This can cause real business problems like production delays, material waste, and quality control failures.
As a result, businesses are turning to mathematical equations to specify colors and non-subjective measuring devices to ensure matching.
The CIE color model, or CIE XYZ color space, was created in 1931. It’s essentially a mapping system that plots colors in a 3D space using red, green, and blue values as the axes.
Many other color spaces have been defined. CIE variants include CIELAB, defined in 1976, where L refers to luminance, A the red/green axis, and B the blue/yellow axis. Yet another model, CIE L*C*h, factors in lightness, chroma, and hue.
Measurement depends upon colorimeters or spectrophotometers that provide digital descriptions of colors. For instance, the percentages of each of the three primary colors required to match a color sample are referred to as tristimulus values. Tristimulus colorimeters are used in quality control applications. Datacolor offers a complete line of spectrophotometers suitable for a variety of industries and more sophisticated applications.