This drawing represents the four unique hues UR, UY, UG, and UB (similar to red, yellow, green, and blue, but more narrowly defined), along with their binary balanced hues (i.e., secondary, tertiary, quaternary). Although originally conceived as the cardinal hues of the Hering opponent process, subsequent investigation revealed that perceptually defined unique hues (also known subjective unique hues) are not the same. The opponent process operates very far upstream in the data stream of the visual system (in the retinal ganglia and the lateral geniculate nucleus, or LGN, about where the optic nerve enters the brain). They still haven’t found the perceptually defined unique hues, but are looking further downstream, around V4, which comes after the V1, V2 and V3, and the prefrontal cortex. Unique hues are also frequently confused with the four most prominent focal colors of the Berlin & Kay / World Color Survey (WCS) model. All these reds, yellows, greens, and blues may be related, but that hasn’t been established.
Finding legitimate names for all the 3rd-order binaries was challenging. None are made up or proprietary. The qualifier “electric” is often used in color names to signify RGB spectral hues (or their nearest equivalent). BV is short for “bright vivid” (also known as “luminous vivid”) essentially the same as “electric,” i.e., maximally saturated computer-display color.
Unique hues come up mainly in vision research, either as a subject of study, or as a tool for measuring other things. For example, the wavelength at which people see unique green is a strong indicator of their macular pigment density (the higher the density the lower the wavelength). Low macular pigment density is a major risk factor for macular degeneration, a leading cause of blindness. One study used unique hues to determine that men, on average, see color as if it were 2.2 nm higher wavelength than women.
Over the years, a number of theories have been proposed to explain what unique hues are and why they exist. One of the more promising theories has to do with color constancy. The idea is that the brain has color correction software that figures out what color things are independent of the light striking them. This is similar to using a gray card in photography, having software analyze the color of the card to figure out the lighting of the scene, then compensate accordingly.
In this theory, the brain has “virtual cones” the mimic the behavior of the cone cells in the eye, but tweak images ever so slightly. Specifically, the blue virtual cones have a sensitivity curve the same shape as the real ones. The virtual red and green cones have curves that are a narrower than the real ones, and are farther apart on the spectrum. Although this may not seem like much, it has a huge effect on how color is processed, making it more accurate and illuminant-independent.
One of the consequences of this model is that certain hues, specifically red, green, blue, and yellow stand out like sore thumbs because of their mathematical “singularity.” If each color can be represented by three numbers in LMS space (referring to the three types of cones cells, L, M, and S, also known as red, green and blue), then in this virtual LMS space the above four hues have either one or two LMS numbers that are close to zero. Furthermore, the mathematical model is set up in such a way that as one or numbers approach zero, the remaining number(s) approach infinity. The result is that red, green, blue, and yellow should be, perceptually, extremely stable across different (natural) lighting conditions.
This theory, by Vazquez-Corral, O’Regan, Vanrell, and Finlayson (2012) draws on Edwin Land’s retinex model and Finlayson’s “sharp sensors” (used in machine vision).
lightcolorvision 