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Color vision
Color vision
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Colorless, green, and red photographic filters as imaged by camera

Color vision (CV), a feature of visual perception, is an ability to perceive differences between light composed of different frequencies independently of light intensity.

Color perception is a part of the larger visual system and is mediated by a complex process between neurons that begins with differential stimulation of different types of photoreceptors by light entering the eye. Those photoreceptors then emit outputs that are propagated through many layers of neurons ultimately leading to higher cognitive functions in the brain. Color vision is found in many animals and is mediated by similar underlying mechanisms with common types of biological molecules and a complex history of the evolution of color vision within different animal taxa. In primates, color vision may have evolved under selective pressure for a variety of visual tasks including the foraging for nutritious young leaves, ripe fruit, and flowers, as well as detecting predator camouflage and emotional states in other primates.[1][2][3]

Wavelength

[edit]
sRGB rendering of the spectrum of visible light
sRGB rendering of the spectrum of visible light
Color Wave­length
(nm)
Fre­quen­cy
(THz)
Photon energy
(eV)
  violet
380–450 670–790 2.75–3.26
  blue
450–485 620–670 2.56–2.75
  cyan
485–500 600–620 2.48–2.56
  green
500–565 530–600 2.19–2.48
  yellow
565–590 510–530 2.10–2.19
  orange
590–625 480–510 1.98–2.10
  red
625–750 400–480 1.65–1.98

Isaac Newton discovered that white light after being split into its component colors when passed through a dispersive prism could be recombined to make white light by passing them through a different prism.

Photopic relative brightness sensitivity of the human visual system as a function of wavelength (luminosity function)

The visible light spectrum ranges from about 380 to 740 nanometers. Spectral colors (colors that are produced by a narrow band of wavelengths) such as red, orange, yellow, green, cyan, blue, and violet can be found in this range. These spectral colors do not refer to a single wavelength, but rather to a set of wavelengths: red, 625–740 nm; orange, 590–625 nm; yellow, 565–590 nm; green, 500–565 nm; cyan, 485–500 nm; blue, 450–485 nm; violet, 380–450 nm.

Wavelengths longer or shorter than this range are called infrared or ultraviolet, respectively. Humans cannot generally see these wavelengths, but other animals may.

Hue detection

[edit]

Sufficient differences in wavelength cause a difference in the perceived hue; the just-noticeable difference in wavelength varies from about 1 nm in the blue-green and yellow wavelengths to 10 nm and more in the longer red and shorter blue wavelengths. Although the human eye can distinguish up to a few hundred hues, when those pure spectral colors are mixed together or diluted with white light, the number of distinguishable chromaticities can be much higher.

In very low light levels, vision is scotopic: light is detected by rod cells of the retina. Rods are maximally sensitive to wavelengths near 500 nm and play little, if any, role in color vision. In brighter light, such as daylight, vision is photopic: light is detected by cone cells which are responsible for color vision. Cones are sensitive to a range of wavelengths, but are most sensitive to wavelengths near 555 nm. Between these regions, mesopic vision comes into play and both rods and cones provide signals to the retinal ganglion cells. The shift in color perception from dim light to daylight gives rise to differences known as the Purkinje effect.

The perception of "white" is formed by the entire spectrum of visible light, or by mixing colors of just a few wavelengths in animals with few types of color receptors. In humans, white light can be perceived by combining wavelengths such as red, green, and blue, or just a pair of complementary colors such as blue and yellow.[4]

Non-spectral colors

[edit]

There are a variety of colors in addition to spectral colors and their hues. These include grayscale colors, shades of colors obtained by mixing grayscale colors with spectral colors, violet-red colors, impossible colors, and metallic colors.

Grayscale colors include white, gray, and black. Rods contain rhodopsin, which reacts to light intensity, providing grayscale coloring.

Shades include colors such as pink or brown. Pink is obtained from mixing red and white. Brown may be obtained from mixing orange with gray or black. Navy is obtained from mixing blue and black.

Violet-red colors include hues and shades of magenta. The light spectrum is a line on which violet is one end and the other is red, and yet we see hues of purple that connect those two colors.

Impossible colors are a combination of cone responses that cannot be naturally produced. For example, medium cones cannot be activated completely on their own; if they were, we would see a 'hyper-green' color.

Dimensionality

[edit]

Color vision is categorized foremost according to the dimensionality of the color gamut, which is defined by the number of primaries required to represent the color vision. This is generally equal to the number of photopsins expressed: a correlation that holds for vertebrates but not invertebrates. The common vertebrate ancestor possessed four photopsins (expressed in cones) plus rhodopsin (expressed in rods), so was tetrachromatic. However, many vertebrate lineages have lost one or many photopsin genes, leading to lower-dimension color vision. The dimensions of color vision range from 1-dimensional and up:

Dimension Characteristic Occurrence
Achromacy lack of any color perception Most skates
Monochromacy 1D color vision Some mammals, including Pinnipeds, Cetaceans and Xenarthra[5][6]
Dichromacy 2D color vision Most mammals and a quarter of color blind humans
Trichromacy 3D color vision Most Old World monkeys and apes, including most humans; possibly monotremes and some marsupials
Tetrachromacy 4D color vision Most birds, reptiles and fish, and rarely in humans
Pentachromacy and higher 5D+ color vision Rare in vertebrates

Physiology of color perception

[edit]
Normalized response spectra of human cones to monochromatic spectral stimuli, with wavelength given in nanometers
The same figures as above represented here as a single curve in three (normalized cone response) dimensions

Perception of color begins with specialized retinal cells known as cone cells. Cone cells contain different forms of opsin – a pigment protein – that have different spectral sensitivities. Humans contain three types, resulting in trichromatic color vision.

Each individual cone contains pigments composed of opsin apoprotein covalently linked to a light-absorbing prosthetic group: either 11-cis-hydroretinal or, more rarely, 11-cis-dehydroretinal.[7]

The cones are conventionally labeled according to the ordering of the wavelengths of the peaks of their spectral sensitivities: short (S), medium (M), and long (L) cone types. These three types do not correspond well to particular colors as we know them. Rather, the perception of color is achieved by a complex process that starts with the differential output of these cells in the retina and which is finalized in the visual cortex and associative areas of the brain.

For example, while the L cones have been referred to simply as red receptors, microspectrophotometry has shown that their peak sensitivity is in the greenish-yellow region of the spectrum. Similarly, the S cones and M cones do not directly correspond to blue and green, although they are often described as such. The RGB color model, therefore, is a convenient means for representing color but is not directly based on the types of cones in the human eye.

The peak response of human cone cells varies, even among individuals with so-called normal color vision;[8] in some non-human species this polymorphic variation is even greater, and it may well be adaptive.[jargon][9]

Theories

[edit]
Opponent process theory

Two complementary theories of color vision are the trichromatic theory and the opponent process theory. The trichromatic theory, or Young–Helmholtz theory, proposed in the 19th century by Thomas Young and Hermann von Helmholtz, posits three types of cones preferentially sensitive to blue, green, and red, respectively. Others have suggested that the trichromatic theory is not specifically a theory of color vision but a theory of receptors for all vision, including color but not specific or limited to it.[10] Equally, it has been suggested that the relationship between the phenomenal opponency described by Ewald Hering and the physiological opponent processes are not straightforward (see below), making of physiological opponency a mechanism that is relevant to the whole of vision, and not just to color vision alone.[10] Hering proposed the opponent process theory in 1872.[11] It states that the visual system interprets color in an antagonistic way: red vs. green, blue vs. yellow, black vs. white. Both theories are generally accepted as valid, describing different stages in visual physiology, visualized in the adjacent diagram.[12]: 168 

Green–magenta and blue–yellow are scales with mutually exclusive boundaries. In the same way that there cannot exist a "slightly negative" positive number, a single eye cannot perceive a bluish-yellow or a reddish-green. Although these two theories are both currently widely accepted theories, past and more recent work has led to criticism of the opponent process theory, stemming from a number of what are presented as discrepancies in the standard opponent process theory. For example, the phenomenon of an after-image of complementary color can be induced by fatiguing the cells responsible for color perception, by staring at a vibrant color for a length of time, and then looking at a white surface. This phenomenon of complementary colors shows that cyan, rather than green, is the complement of red, and that magenta, rather than red, is the complement of green. It therefore also shows that the reddish-green color supposed to be impossible by opponent process theory is actually the color yellow. Although this phenomenon is more readily explained by the trichromatic theory, explanations for the discrepancy may include alterations to the opponent process theory, such as redefining the opponent colors as red vs. cyan, to reflect this effect. Despite such criticisms, both theories remain in use.

A newer theory proposed by Edwin H. Land, the Retinex Theory, is based on a demonstration of color constancy, which shows that the color of any surface that is part of a complex natural scene is to a large degree independent of the wavelength composition of the light reflected from it. Also the after-image produced by looking at a given part of a complex scene is also independent of the wavelength composition of the light reflected from it alone. Thus, while the color of the after-image produced by looking at a green surface that is reflecting more "green" (middle-wave) than "red" (long-wave) light is magenta, so is the after–image of the same surface when it reflects more "red" than "green" light (when it is still perceived as green). This would seem to rule out an explanation of color opponency based on retinal cone adaptation.[13]

According to Land's Retinex theory, color in a natural scene depends upon the three sets of cone cells ("red," "green," and "blue") separately perceiving each surface's relative lightness in the scene and, together with the visual cortex, assigning color based on comparing the lightness values perceived by each set of cone cells.[14]

Cone cells in the human eye

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Cones are present at a low density throughout most of the retina, with a sharp peak in the center of the fovea. Conversely, rods are present at high density throughout most of the retina, with a sharp decline in the fovea.

A range of wavelengths of light stimulates each of these receptor types to varying degrees. The brain combines the information from each type of receptor to give rise to different perceptions of different wavelengths of light.

Cone type Name Range Peak wavelength[15][16]
S β 400–500 nm 420–440 nm
M γ 450–630 nm 534–555 nm
L ρ 500–700 nm 564–580 nm

Cones and rods are not evenly distributed in the human eye. Cones have a high density at the fovea and a low density in the rest of the retina.[17] Thus color information is mostly taken in at the fovea. Humans have poor color perception in their peripheral vision, and much of the color we see in our periphery may be filled in by what our brains expect to be there on the basis of context and memories. However, our accuracy of color perception in the periphery increases with the size of stimulus.[18]

The opsins (photopigments) present in the L and M cones are encoded on the X chromosome; defective encoding of these leads to the two most common forms of color blindness. The OPN1LW gene, which encodes the opsin present in the L cones, is highly polymorphic; one study found 85 variants in a sample of 236 men.[19] A small percentage of women may have an extra type of color receptor because they have different alleles for the gene for the L opsin on each X chromosome. X chromosome inactivation means that while only one opsin is expressed in each cone cell, both types may occur overall, and some women may therefore show a degree of tetrachromatic color vision.[20] Variations in OPN1MW, which encodes the opsin expressed in M cones, appear to be rare, and the observed variants have no effect on spectral sensitivity.

Color in the primate brain

[edit]
Visual pathways in the human brain. The ventral stream (purple) is important in color recognition. The dorsal stream (green) is also shown. They originate from a common source in the visual cortex.

Color processing begins at a very early level in the visual system (even within the retina) through initial color opponent mechanisms. Both Helmholtz's trichromatic theory and Hering's opponent-process theory are therefore correct, but trichromacy arises at the level of the receptors, and opponent processes arise at the level of retinal ganglion cells and beyond. In Hering's theory, opponent mechanisms refer to the opposing color effect of red–green, blue–yellow, and light-dark. However, in the visual system, it is the activity of the different receptor types that are opposed. Some midget retinal ganglion cells oppose L and M cone activity, which corresponds loosely to red–green opponency, but actually runs along an axis from blue-green to magenta. Small bistratified retinal ganglion cells oppose input from the S cones to input from the L and M cones. This is often thought to correspond to blue–yellow opponency but actually runs along a color axis from yellow-green to violet.

Visual information is then sent to the brain from retinal ganglion cells via the optic nerve to the optic chiasma: a point where the two optic nerves meet and information from the temporal (contralateral) visual field crosses to the other side of the brain. After the optic chiasma, the visual tracts are referred to as the optic tracts, which enter the thalamus to synapse at the lateral geniculate nucleus (LGN).

The lateral geniculate nucleus is divided into laminae (zones), of which there are three types: the M-laminae, consisting primarily of M-cells, the P-laminae, consisting primarily of P-cells, and the koniocellular laminae. M- and P-cells receive relatively balanced input from both L- and M-cones throughout most of the retina, although this seems to not be the case at the fovea, with midget cells synapsing in the P-laminae. The koniocellular laminae receives axons from the small bistratified ganglion cells.[21][22]

After synapsing at the LGN, the visual tract continues on back to the primary visual cortex (V1) located at the back of the brain within the occipital lobe. Within V1 there is a distinct band (striation). This is also referred to as "striate cortex", with other cortical visual regions referred to collectively as "extrastriate cortex". It is at this stage that color processing becomes much more complicated.

In V1 the simple three-color segregation begins to break down. Many cells in V1 respond to some parts of the spectrum better than others, but this "color tuning" is often different depending on the adaptation state of the visual system. A given cell that might respond best to long-wavelength light if the light is relatively bright might then become responsive to all wavelengths if the stimulus is relatively dim. Because the color tuning of these cells is not stable, some believe that a different, relatively small, population of neurons in V1 is responsible for color vision. These specialized "color cells" often have receptive fields that can compute local cone ratios. Such "double-opponent" cells were initially described in the goldfish retina by Nigel Daw;[23][24] their existence in primates was suggested by David H. Hubel and Torsten Wiesel, first demonstrated by C.R. Michael[25] and subsequently confirmed by Bevil Conway.[26] As Margaret Livingstone and David Hubel showed, double opponent cells are clustered within localized regions of V1 called blobs, and are thought to come in two flavors, red–green and blue-yellow.[27] Red–green cells compare the relative amounts of red–green in one part of a scene with the amount of red–green in an adjacent part of the scene, responding best to local color contrast (red next to green). Modeling studies have shown that double-opponent cells are ideal candidates for the neural machinery of color constancy explained by Edwin H. Land in his retinex theory.[28]

When viewed in full size, this image contains about 16 million pixels, each corresponding to a different color in the full set of RGB colors. The human eye can distinguish about 10 million different colors.[29]

From the V1 blobs, color information is sent to cells in the second visual area, V2. The cells in V2 that are most strongly color tuned are clustered in the "thin stripes" that, like the blobs in V1, stain for the enzyme cytochrome oxidase (separating the thin stripes are interstripes and thick stripes, which seem to be concerned with other visual information like motion and high-resolution form). Neurons in V2 then synapse onto cells in the extended V4. This area includes not only V4, but two other areas in the posterior inferior temporal cortex, anterior to area V3, the dorsal posterior inferior temporal cortex, and posterior TEO.[30][31] Area V4 was initially suggested by Semir Zeki to be exclusively dedicated to color,[32] and he later showed that V4 can be subdivided into subregions with very high concentrations of color cells separated from each other by zones with lower concentration of such cells though even the latter cells respond better to some wavelengths than to others,[33] a finding confirmed by subsequent studies.[30][34][35] The presence in V4 of orientation-selective cells led to the view that V4 is involved in processing both color and form associated with color[36] but it is worth noting that the orientation selective cells within V4 are more broadly tuned than their counterparts in V1, V2 and V3.[33] Color processing in the extended V4 occurs in millimeter-sized color modules called globs.[30][31] This is the part of the brain in which color is first processed into the full range of hues found in color space.[37][30][31]

Anatomical studies have shown that neurons in extended V4 provide input to the inferior temporal lobe. "IT" cortex is thought to integrate color information with shape and form, although it has been difficult to define the appropriate criteria for this claim. Despite this murkiness, it has been useful to characterize this pathway (V1 > V2 > V4 > IT) as the ventral stream or the "what pathway", distinguished from the dorsal stream ("where pathway") that is thought to analyze motion, among other features.

Subjectivity of color perception

[edit]

Color is a feature of visual perception by an observer. There is a complex relationship between the wavelengths of light in the visual spectrum and human experiences of color. Although most people are assumed to have the same mapping, the philosopher John Locke recognized that alternatives are possible, and described one such hypothetical case with the "inverted spectrum" thought experiment. For example, someone with an inverted spectrum might experience green while seeing 'red' (700 nm) light, and experience red while seeing 'green' (530 nm) light. This inversion has never been demonstrated in experiment, though.

Synesthesia (or ideasthesia) provides some atypical but illuminating examples of subjective color experience triggered by input that is not even light, such as sounds or shapes. The possibility of a clean dissociation between color experience from properties of the world reveals that color is a subjective psychological phenomenon.

The Himba people have been found to categorize colors differently from most Westerners and are able to easily distinguish close shades of green, barely discernible for most people.[38] The Himba have created a very different color scheme which divides the spectrum to dark shades (zuzu in Himba), very light (vapa), vivid blue and green (buru) and dry colors as an adaptation to their specific way of life.

The perception of color depends heavily on the context in which the perceived object is presented.[39]

Psychophysical experiments have shown that color is perceived before the orientation of lines and directional motion by as much as 40ms and 80 ms respectively, thus leading to a perceptual asynchrony that is demonstrable with brief presentation times.

Chromatic adaptation

[edit]

In color vision, chromatic adaptation refers to color constancy; the ability of the visual system to preserve the appearance of an object under a wide range of light sources.[40] For example, a white page under blue, pink, or purple light will reflect mostly blue, pink, or purple light to the eye, respectively; the brain, however, compensates for the effect of lighting (based on the color shift of surrounding objects) and is more likely to interpret the page as white under all three conditions, a phenomenon known as color constancy.

In color science, chromatic adaptation is the estimation of the representation of an object under a different light source from the one in which it was recorded. A common application is to find a chromatic adaptation transform (CAT) that will make the recording of a neutral object appear neutral (color balance), while keeping other colors also looking realistic.[41] For example, chromatic adaptation transforms are used when converting images between ICC profiles with different white points. Adobe Photoshop, for example, uses the Bradford CAT.[42]

Color vision in nonhumans

[edit]

Many species can see light with frequencies outside the human "visible spectrum". Bees and many other insects can detect ultraviolet light,[43] which helps them to find nectar in flowers. Plant species that depend on insect pollination may owe reproductive success to ultraviolet "colors" and patterns rather than how colorful they appear to humans. Birds, too, can see into the ultraviolet (300–400 nm), and some have sex-dependent markings on their plumage that are visible only in the ultraviolet range.[44][45] Many animals that can see into the ultraviolet range, however, cannot see red light or any other reddish wavelengths. For example, bees' visible spectrum ends at about 590 nm, just before the orange wavelengths start. Birds, however, can see some red wavelengths, although not as far into the light spectrum as humans.[46] It is a myth that the common goldfish is the only animal that can see both infrared and ultraviolet light;[47] their color vision extends into the ultraviolet but not the infrared.[48]

The basis for this variation is the number of cone types that differ between species. Mammals, in general, have a color vision of a limited type, and usually have red–green color blindness, with only two types of cones. Humans, some primates, and some marsupials see an extended range of colors, but only by comparison with other mammals. Most non-mammalian vertebrate species distinguish different colors at least as well as humans, and many species of birds, fish, reptiles, and amphibians, and some invertebrates, have more than three cone types and probably superior color vision to humans.

In most Catarrhini (Old World monkeys and apes—primates closely related to humans), there are three types of color receptors (known as cone cells), resulting in trichromatic color vision. These primates, like humans, are known as trichromats. Many other primates (including New World monkeys) and other mammals are dichromats, which is the general color vision state for mammals that are active during the day (i.e., felines, canines, ungulates). Nocturnal mammals may have little or no color vision. Trichromat non-primate mammals are rare.[12]: 174–175 [49]

Many invertebrates have color vision. Honeybees and bumblebees have trichromatic color vision which is usually insensitive to red[nb 1] but sensitive to ultraviolet. The Solitary Bee Osmia rufa, for example, possess a trichromatic color system, which they use in foraging for pollen from flowers.[51] In view of the importance of color vision to bees one might expect these receptor sensitivities to reflect their specific visual ecology; for example the types of flowers that they visit. However, the main groups of hymenopteran insects excluding ants (i.e., bees, wasps and sawflies) mostly have three types of photoreceptor, with spectral sensitivities similar to the honeybee's.[52] Papilio butterflies possess six types of photoreceptors and may have pentachromatic vision.[53] The most complex color vision system in the animal kingdom has been found in stomatopods (such as the mantis shrimp) having between 12 and 16 spectral receptor types thought to work as multiple dichromatic units.[54]

Vertebrate animals such as tropical fish and birds sometimes have more complex color vision systems than humans; thus the many subtle colors they exhibit generally serve as direct signals for other fish or birds, and not to signal mammals.[55] In bird vision, tetrachromacy is achieved through up to four cone types, depending on species. Each single cone contains one of the four main types of vertebrate cone photopigment (LWS/ MWS, RH2, SWS2 and SWS1) and has a colored oil droplet in its inner segment.[52] Brightly colored oil droplets inside the cones shift or narrow the spectral sensitivity of the cell. Pigeons may be pentachromats.[56]

Reptiles and amphibians also have four cone types (occasionally five), and probably see at least the same number of colors that humans do, or perhaps more. In addition, some nocturnal geckos and frogs have the capability of seeing color in dim light.[57][58] At least some color-guided behaviors in amphibians have also been shown to be wholly innate, developing even in visually deprived animals.[59]

In the evolution of mammals, segments of color vision were lost, then for a few species of primates, regained by gene duplication. Eutherian mammals other than primates (for example, dogs, mammalian farm animals) generally have less-effective two-receptor (dichromatic) color perception systems, which distinguish blue, green, and yellow—but cannot distinguish oranges and reds. There is some evidence that a few mammals, such as cats, have redeveloped the ability to distinguish longer wavelength colors, in at least a limited way, via one-amino-acid mutations in opsin genes.[60] The adaptation to see reds is particularly important for primate mammals, since it leads to the identification of fruits, and also newly sprouting reddish leaves, which are particularly nutritious.

However, even among primates, full color vision differs between New World and Old World monkeys. Old World primates, including monkeys and all apes, have vision similar to humans. New World monkeys may or may not have color sensitivity at this level: in most species, males are dichromats, and about 60% of females are trichromats, but the owl monkeys are cone monochromats, and both sexes of howler monkeys are trichromats.[61][62][63][64] Visual sensitivity differences between males and females in a single species is due to the gene for yellow-green sensitive opsin protein (which confers ability to differentiate red from green) residing on the X sex chromosome.

Several marsupials, such as the fat-tailed dunnart (Sminthopsis crassicaudata), have trichromatic color vision.[65]

Marine mammals, adapted for low-light vision, have only a single cone type and are thus monochromats.[citation needed]

Evolution

[edit]

Color perception mechanisms are highly dependent on evolutionary factors, of which the most prominent is thought to be satisfactory recognition of food sources. In herbivorous primates, color perception is essential for finding proper (immature) leaves. In hummingbirds, particular flower types are often recognized by color as well. On the other hand, nocturnal mammals have less-developed color vision since adequate light is needed for cones to function properly. There is evidence that ultraviolet light plays a part in color perception in many branches of the animal kingdom, especially insects. In general, the optical spectrum encompasses the most common electronic transitions in matter and is therefore the most useful for collecting information about the environment.

The evolution of trichromatic color vision in primates occurred as the ancestors of modern monkeys, apes, and humans switched to diurnal (daytime) activity and began consuming fruits and leaves from flowering plants.[66] Color vision, with UV discrimination, is also present in a number of arthropods—the only terrestrial animals besides the vertebrates to possess this trait.[67]

Some animals can distinguish colors in the ultraviolet spectrum. The UV spectrum falls outside the human visible range, except for some cataract surgery patients.[68] Birds, turtles, lizards, many fish and some rodents have UV receptors in their retinas.[69] These animals can see the UV patterns found on flowers and other wildlife that are otherwise invisible to the human eye.

Ultraviolet vision is an especially important adaptation in birds. It allows birds to spot small prey from a distance, navigate, avoid predators, and forage while flying at high speeds. Birds also utilize their broad spectrum vision to recognize other birds, and in sexual selection.[70][71]

Mathematics of color perception

[edit]

A "physical color" is a combination of pure spectral colors (in the visible range). In principle there exist infinitely many distinct spectral colors, and so the set of all physical colors may be thought of as an infinite-dimensional vector space (a Hilbert space). This space is typically notated Hcolor. More technically, the space of physical colors may be considered to be the topological cone over the simplex whose vertices are the spectral colors, with white at the centroid of the simplex, black at the apex of the cone, and the monochromatic color associated with any given vertex somewhere along the line from that vertex to the apex depending on its brightness.

An element C of Hcolor is a function from the range of visible wavelengths—considered as an interval of real numbers [Wmin,Wmax]—to the real numbers, assigning to each wavelength w in [Wmin,Wmax] its intensity C(w).

A humanly perceived color may be modeled as three numbers: the extents to which each of the 3 types of cones is stimulated. Thus a humanly perceived color may be thought of as a point in 3-dimensional Euclidean space. We call this space R3color.

Since each wavelength w stimulates each of the 3 types of cone cells to a known extent, these extents may be represented by 3 functions s(w), m(w), l(w) corresponding to the response of the S, M, and L cone cells, respectively.

Finally, since a beam of light can be composed of many different wavelengths, to determine the extent to which a physical color C in Hcolor stimulates each cone cell, we must calculate the integral (with respect to w), over the interval [Wmin,Wmax], of C(ws(w), of C(wm(w), and of C(wl(w). The triple of resulting numbers associates with each physical color C (which is an element in Hcolor) a particular perceived color (which is a single point in R3color). This association is easily seen to be linear. It may also easily be seen that many different elements in the "physical" space Hcolor can all result in the same single perceived color in R3color, so a perceived color is not unique to one physical color.

Thus human color perception is determined by a specific, non-unique linear mapping from the infinite-dimensional Hilbert space Hcolor to the 3-dimensional Euclidean space R3color.

Technically, the image of the (mathematical) cone over the simplex whose vertices are the spectral colors, by this linear mapping, is also a (mathematical) cone in R3color. Moving directly away from the vertex of this cone represents maintaining the same chromaticity while increasing its intensity. Taking a cross-section of this cone yields a 2D chromaticity space. Both the 3D cone and its projection or cross-section are convex sets; that is, any mixture of spectral colors is also a color.

The CIE 1931 xy chromaticity diagram with a triangle showing the gamut of the Adobe RGB color space. The Planckian locus is shown with color temperatures labeled in kelvins. The outer curved boundary is the spectral locus, with wavelengths shown in nanometers. Note that the colors in this file are specified in Adobe RGB. Areas outside the triangle cannot be accurately rendered because they are out of the gamut of Adobe RGB, therefore they have been interpreted. Note that the colors depicted depend on the color space of the device you use to view the image (number of colors on your monitor, etc.), and may not be a strictly accurate representation of the color at a particular position.

In practice, it would be quite difficult to physiologically measure an individual's three cone responses to various physical color stimuli. Instead, a psychophysical approach is taken.[72] Three specific benchmark test lights are typically used; let us call them S, M, and L. To calibrate human perceptual space, scientists allowed human subjects to try to match any physical color by turning dials to create specific combinations of intensities (IS, IM, IL) for the S, M, and L lights, resp., until a match was found. This needed only to be done for physical colors that are spectral, since a linear combination of spectral colors will be matched by the same linear combination of their (IS, IM, IL) matches. Note that in practice, often at least one of S, M, L would have to be added with some intensity to the physical test color, and that combination matched by a linear combination of the remaining 2 lights. Across different individuals (without color blindness), the matchings turned out to be nearly identical.

By considering all the resulting combinations of intensities (IS, IM, IL) as a subset of 3-space, a model for human perceptual color space is formed. (Note that when one of S, M, L had to be added to the test color, its intensity was counted as negative.) Again, this turns out to be a (mathematical) cone, not a quadric, but rather all rays through the origin in 3-space passing through a certain convex set. Again, this cone has the property that moving directly away from the origin corresponds to increasing the intensity of the S, M, L lights proportionately. Again, a cross-section of this cone is a planar shape that is (by definition) the space of "chromaticities" (informally: distinct colors); one particular such cross-section, corresponding to constant X+Y+Z of the CIE 1931 color space, gives the CIE chromaticity diagram.

This system implies that for any hue or non-spectral color not on the boundary of the chromaticity diagram, there are infinitely many distinct physical spectra that are all perceived as that hue or color. So, in general, there is no such thing as the combination of spectral colors that we perceive as (say) a specific version of tan; instead, there are infinitely many possibilities that produce that exact color. The boundary colors that are pure spectral colors can be perceived only in response to light that is purely at the associated wavelength, while the boundary colors on the "line of purples" can each only be generated by a specific ratio of the pure violet and the pure red at the ends of the visible spectral colors.

The CIE chromaticity diagram is horseshoe-shaped, with its curved edge corresponding to all spectral colors (the spectral locus), and the remaining straight edge corresponding to the most saturated purples, mixtures of red and violet.

See also

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Notes

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References

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Further reading

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from Grokipedia
Color vision is the ability of the to perceive and distinguish differences in the wavelengths of , enabling the differentiation of objects and environments through hues such as , , and . In humans, this process is mediated by specialized photoreceptor cells in the and neural pathways in the , which convert energy into electrochemical signals that the interprets as color. The foundation of human color vision lies in the retina's cone photoreceptors, which are divided into three types based on their peak sensitivity to different wavelengths: short-wavelength-sensitive (S) cones for blue light (~420 nm), medium-wavelength-sensitive (M) cones for green light (~530 nm), and long-wavelength-sensitive (L) cones for red light (~560 nm). These cones, numbering approximately 6–7 million in the retina, contain photopigments (opsins) that absorb and initiate a phototransduction cascade, transforming photons into neural signals via hyperpolarization of the cone cells. This trichromatic organization, first proposed by Thomas Young and , allows for the perception of a vast spectrum of colors through the relative activation of the three cone types, with humans exhibiting as an evolutionary adaptation in Old World primates for detecting ripe against foliage. Signals from the cones are relayed through bipolar and cells in the , where initial color opponency emerges, such as red-green (L-M cone differences) and blue-yellow (S versus L+M cone sums) channels, aligning with Ewald Hering's . These chromatic signals travel via the parvocellular pathway through the (LGN) of the to the primary (V1), where double-opponent cells further refine color contrasts by comparing center-surround receptive fields. Higher-level processing in areas like V4 integrates color with form, , and motion, contributing to phenomena such as —maintaining perceived hue under varying illumination—and enabling complex discriminations, though vulnerabilities like arise from genetic defects in cone pigments.

Fundamentals of Color Perception

Visible Spectrum and Wavelengths

The encompasses the full range of , organized by wavelength or frequency, including radio waves, microwaves, , , , X-rays, and gamma rays. constitutes a narrow segment of this spectrum, typically spanning wavelengths from approximately 380 to 700 nanometers (nm), which is the portion detectable by the . This range represents only about 0.0035% of the entire . Within the visible spectrum, the perceived color of light corresponds directly to its wavelength: shorter wavelengths, around 380–450 nm, appear as violet or blue, while progressively longer wavelengths transition through green (approximately 495–570 nm), yellow (570–590 nm), and orange (590–620 nm), culminating in red at 620–700 nm. Monochromatic light at a single wavelength produces a pure spectral color, but most perceived colors result from mixtures of wavelengths. Light intensity, or the amount of per unit area, influences the of the perceived color without altering its hue, as higher intensity increases the overall while maintaining the spectral composition. purity, defined as the proportion of a dominant wavelength relative to added broadband light (such as light), affects color saturation; high-purity light yields vivid, saturated colors, whereas low-purity light appears more desaturated or pastel. The foundational understanding of the visible spectrum emerged from Isaac Newton's experiments in 1666, where he passed sunlight through a glass prism to decompose it into a continuous band of colors, demonstrating that white light is a composite of distinct spectral components rather than a single entity. This prism-based decomposition, detailed in his later work Opticks (1704), established the wavelength basis for color and refuted earlier corpuscular theories by showing refraction's dependence on wavelength.

Hue Detection and Non-Spectral Colors

Hue detection in the human arises from the differential absorption of wavelengths by photoreceptors in the . When enters the eye, photoreceptors absorb photons based on their curves, generating electrical signals proportional to the absorbed energy. The relative activation levels across different photoreceptor types create a of responses that the interprets as specific hues, allowing discrimination between wavelengths even when overall intensity is similar. This process relies on contrast rather than absolute energy, enabling the of color in varied lighting conditions. Non-spectral colors, also known as extraspectral colors, are hues that cannot be produced by a single of within the but emerge from mixtures of spectral lights. A prominent example is , which results from combining (around 650–700 nm) and blue light (around 450–500 nm), stimulating long- and short-wavelength-sensitive photoreceptors without significant middle-wavelength activation. This combination evokes a reddish-purple absent in , as the brain interpolates the gap between the spectrum's and violet ends. Other non-spectral colors, such as certain browns or pinks, similarly arise from or multi-peak spectral distributions rather than monochromatic sources. The phenomenon of complementary colors further illustrates the perceptual mapping of hues beyond the linear . Complementary pairs, such as and or and , are hues that, when mixed in appropriate proportions, produce achromatic or gray by balancing photoreceptor activations to neutralize color signals. This occurs because complements activate opposing response channels in the , canceling chromatic content. The forms a linear sequence from approximately 380 nm (violet) to 750 nm () and does not close into a perceptual loop, as no single bridges the gap between and violet; instead, non-spectral purples like complete the circle through additive mixing, reflecting the brain's organization of rather than physical light properties. Psychological primaries, or , represent fundamental perceptual categories that structure human color experience: , , , and . These hues are defined as the points in where one chromatic quality appears pure without contamination by its opponent, such as a red devoid of yellow or green tinges. Proposed by Ewald Hering in the late 19th century, they form the basis for describing all other hues as mixtures of adjacent pairs (e.g., orange as red-yellow), highlighting the categorical nature of hue perception independent of spectral linearity. Empirical studies confirm these primaries vary slightly across individuals but remain stable anchors for color naming and matching tasks.

Physiological Basis

Photoreceptors in the Eye

Color vision begins with the detection of light by specialized photoreceptor cells in the of the , primarily the cells, which are responsible for perceiving wavelengths across the under well-lit conditions. cells are elongated, cone-shaped neurons with outer segments that contain stacks of membranous discs housing light-sensitive photopigments. These discs are open to the via a connecting , allowing for rapid diffusion of signaling molecules and continuous renewal through shedding and by the . Unlike , which mediate achromatic vision in low light, cones enable high spatial acuity and color discrimination due to their denser packing in central retinal regions and direct connections to bipolar cells. Human cone cells are categorized into three types based on their spectral sensitivity: long-wavelength-sensitive (L) cones, medium-wavelength-sensitive (M) cones, and short-wavelength-sensitive (S) cones. L cones, often associated with light perception, have peak sensitivity at approximately 564 nm; M cones, linked to , peak at about 534 nm; and S cones, sensitive to , peak at around 420 nm. These sensitivities arise from distinct photopigments that absorb light across overlapping regions of the (roughly 400–700 nm), allowing the eye to distinguish a wide range of hues through differential activation. The absorption spectra of these photopigments are bell-shaped curves, with L and M cones showing broad overlap in the yellow-green range, while S cones have a narrower, shifted profile toward shorter wavelengths. The photopigments in cells consist of proteins covalently bound to a molecule, 11-cis-retinal, derived from . Upon absorption, 11-cis-retinal isomerizes to all-trans-retinal, triggering a conformational change in the opsin that initiates the phototransduction cascade, hyperpolarizing the cell and modulating release. Each cone type expresses a specific opsin: L-cone opsin (encoded by OPN1LW), M-cone opsin (OPN1MW), and S-cone opsin (OPN1SW), with variations—such as the presence of a in L and M opsins but not in S opsin—fine-tuning their spectral properties. This molecular arrangement ensures that light of different wavelengths elicits unique response patterns across the cone population. In the human , approximately 6 million cells are distributed unevenly, with the highest density in the —a small, rod-free pit about 1.5 mm in diameter at the center of the —where packing reaches up to 200,000 cells per square millimeter. This foveal concentration supports sharp, detailed color vision for tasks like reading or face recognition, as each often connects to a single bipolar cell. In contrast, outnumber by about 20:1 overall (around 120 million per eye) and dominate the peripheral , providing sensitivity to dim but no color information. Beyond the fovea, density declines rapidly, dropping to a few thousand per square millimeter in the mid-periphery. The genetic basis for L-cone function lies in the OPN1LW gene on the , which encodes the protein sensitive to long wavelengths; it is arranged in a tandem array with OPN1MW, regulated by a locus control region to ensure proper expression ratios of L to M cones (typically about 2:1). Mutations in OPN1LW can shift peak sensitivity or impair function, but in normal vision, it underpins the red-sensitive component of trichromatic color perception. Similar genetic loci control M- and S-cone , highlighting the evolutionary adaptation of these photoreceptors for daylight color vision in .

Neural Pathways and Brain Processing

Color signals originate from the retina's photoreceptors, which are processed by distinct types of cells that form parallel pathways to the . The parvocellular (P) pathway, arising from cells, is specialized for high and red-green color opponency, transmitting slow-conducting signals sensitive to fine details and chromatic differences. In contrast, the magnocellular (M) pathway, from parasol ganglion cells, prioritizes low but fast conduction for and motion detection, with minimal color sensitivity. These pathways segregate early, enabling independent processing of color and dynamic visual features. Axons from these ganglion cells project to the (LGN) of the , where color signals are further organized into layered structures. In , the P pathway terminates primarily in the parvocellular layers 3-6 of the LGN, preserving color opponency through center-surround receptive fields that compare cone inputs from L (long-wavelength) and M (medium-wavelength) cones. The M pathway targets the magnocellular layers 1-2, focusing on achromatic contrasts.00379-7) This segregation in the LGN maintains the parallel streams, with koniocellular layers (interlaminar) adding blue-yellow color processing from small bistratified cells. From the LGN, these pathways relay to the primary (V1), where color information integrates with form processing. In V1, color-sensitive neurons in the cytochrome oxidase-rich blobs exhibit double-opponent responses, detecting chromatic edges while lacking strong orientation selectivity, thus linking color to basic . P pathway inputs drive these blob regions for fine-scale color and form analysis, while M inputs support broader luminance-based orientation tuning in interblob areas. This integration allows V1 to represent colored contours and surfaces essential for object boundaries. Further processing occurs in extrastriate area V4, which specializes in by normalizing signals across varying illuminations. Neurons in V4 maintain responses to object hues despite background changes, achieving perceptual stability through broad chromatic tuning and contextual modulation. Seminal recordings in macaques showed that V4 lesions impair without affecting hue discrimination, highlighting its role in adaptive color . V4 receives convergent from V1 and V2, refining color representations for mid-level vision. In higher ventral stream areas, such as V8 and the inferotemporal (IT) cortex, color contributes to . V8, located adjacent to V4, processes retinotopic color maps and supports conscious color perception, with fMRI showing strong activation to isoluminant chromatic stimuli. IT cortex neurons exhibit color selectivity tuned to natural object hues, integrating chromatic cues with shape for categorical identification, as evidenced by responses to monkey faces and fruits. This enables robust object color memory and discrimination. Recent post-2010 reveals interactions between color areas and motion-sensitive MT+, facilitating integrated of dynamic colored scenes. Functional MRI studies demonstrate that color signals from V4 modulate MT+ responses to motion direction, enhancing of colored moving objects via feedback connections. High-resolution 7T confirms these cross-talk pathways, where chromatic cues influence motion coherence detection in MT+, supporting real-world visual binding.00355-6)

Theoretical Frameworks

Trichromatic Theory

The trichromatic theory, also known as the Young-Helmholtz theory, posits that human color vision arises from the responses of three distinct types of photoreceptors in the , each sensitive to different wavelength ranges of light. In 1802, Thomas Young hypothesized that the eye possesses three mechanisms corresponding to the primary colors , , and , enabling the of all other colors through their additive mixtures. This idea built on earlier observations of but provided a physiological foundation, suggesting that spectral colors could be synthesized from combinations of these primaries without invoking more complex interactions. Hermann von Helmholtz further developed and formalized Young's hypothesis in the mid-19th century, elaborating on the physiological in his seminal work. Helmholtz argued that the three cone types—sensitive primarily to long (red), medium (green), and short (blue-violet) wavelengths—generate independent sensations whose linear combinations produce the full spectrum of perceived colors. His elaboration emphasized that no single color sensation requires more than three primaries for matching, a principle that aligned with empirical observations of mixing using lights rather than pigments. The experimental foundation of the theory rests on color matching experiments, where observers adjust the intensities of three primary lights to match a target . Pioneering work by James Clerk Maxwell in 1855 demonstrated trichromatic mixing quantitatively, confirming that all hues could be reproduced with , , and primaries. This was refined in the 1920s and 1930s through systematic studies by William David Wright and John Guild, whose data formed the basis for the International Commission on Illumination's (CIE) 1931 standard color matching functions. These functions, denoted as rˉ(λ)\bar{r}(\lambda), gˉ(λ)\bar{g}(\lambda), and bˉ(λ)\bar{b}(\lambda), quantify the amounts of , , and primaries needed to match monochromatic light at wavelength λ\lambda, providing a mathematical description of human color matching behavior. Mathematically, the theory represents perceived color as a linear combination of the excitations from the three cone types, typically labeled L (long-wavelength sensitive), M (medium-wavelength sensitive), and S (short-wavelength sensitive). The color percept CC can be expressed as: C=aL+bM+cSC = aL + bM + cS where LL, MM, and SS are the quantum catches or excitations of the respective cones, and aa, bb, cc are weighting coefficients determined by the visual system's processing. This formulation captures how variations in cone responses encode the three-dimensional nature of color space, with ratios of L:M:SL:M:S distinguishing hues. Despite its strengths in explaining color matching and mixture, the has limitations in accounting for certain perceptual phenomena, such as negative afterimages, where staring at a color induces its complement upon removal. These effects suggest additional post-receptoral mechanisms beyond simple combinations, though the theory remains foundational for understanding the initial stages of color encoding at the level.

Opponent-Process Theory

The of color vision, first proposed by German physiologist Ewald Hering in 1878, suggests that arises from three antagonistic pairs of neural channels: a red-green system, a blue-yellow system, and a black-white () system. In this framework, each pair operates in opposition, where excitation in one member inhibits the other, preventing the perception of impossible colors like reddish-green or bluish-yellow and explaining why certain color mixtures yield neutral grays.00147-X) Hering's model emphasized that these opponent processes occur post-retinally, integrating sensory inputs to produce perceptual contrasts rather than relying solely on additive mixing at the receptor level. Neural evidence supporting the theory emerged from electrophysiological recordings in the (LGN) of primates, where cells exhibit clear antagonistic responses to color stimuli. For instance, many LGN neurons show excitation to long-wavelength () light and inhibition to medium-wavelength () light, denoted as +/-G responses, while others display +G/-, +B/-Y, or luminance-based opponency. These findings, first systematically documented in macaque monkeys, indicate that opponent organization begins as early as the LGN, transforming cone signals into contrast-sensitive pathways that project to the . The theory elegantly explains key perceptual phenomena beyond simple color addition, such as negative afterimages and simultaneous contrast. In negative afterimages, prolonged fixation on a color like fatigues the -excitatory channel, leading to rebound excitation in the green-inhibitory counterpart when viewing a field, resulting in a green afterimage; similar dynamics occur for blue-yellow pairs. Simultaneous contrast arises from within opponent channels, where a surround enhances the green appearance of a central patch by suppressing shared signals, amplifying perceived differences between adjacent colors. This model integrates with by positing that the three cone types—sensitive to long (L), medium (M), and short (S) wavelengths—provide the foundational inputs, which are then recoded into opponent signals during early neural processing. Specifically, the red-green opponent channel can be approximated as R - G = [L - M](/page/L&M), where L and M signals are subtracted to yield a contrast emphasizing hue differences, while the blue-yellow channel derives from B - Y = S - ([L + M](/page/L&M)); the black-white channel sums across cones. This dual-stage architecture reconciles receptor-level additivity with higher-level perceptual opponency, as validated by psychophysical and physiological data.

Variations and Subjectivity

Chromatic Adaptation

Chromatic adaptation refers to the visual system's ability to adjust in response to changes in the spectral composition of ambient illumination, maintaining relative color appearances across varying conditions. This process enables , where objects appear to retain their inherent colors despite shifts in the illuminant, such as from daylight to artificial . The adaptation occurs over multiple timescales, from rapid adjustments in seconds to slower recalibrations over minutes, ensuring stable in dynamic environments. A foundational mechanism of is the von Kries model, which posits independent scaling of responses from the three photoreceptor types (long-, medium-, and short-wavelength sensitive) to compensate for the illuminant's . In this transform, the adapted response for each class, such as the long- (L) cones, is computed as L=LLavgL' = \frac{L}{L_{avg}}, where LavgL_{avg} represents the average response under the current illuminant, with analogous scaling for medium- (M) and short- (S) cones. This multiplicative gain adjustment normalizes the signals relative to the background, preserving hue relations while shifting the overall . The von Kries hypothesis, originally proposed in 1902, remains a cornerstone for computational models of adaptation due to its simplicity and alignment with early neural processing. Physiologically, chromatic adaptation involves gain control mechanisms at both retinal and cortical levels. In the retina, photoreceptor adaptation rapidly modulates sensitivity through feedback in horizontal and bipolar cells, while retinal ganglion cells exhibit contrast gain control that stabilizes chromatic signals against illuminant changes. Cortical areas, particularly in early visual cortex (V1), further refine these adjustments via selective adaptation to color contrast, integrating luminance and chromatic inputs to enhance constancy. These neural processes ensure that adaptation is not merely peripheral but distributed across the visual pathway. Illustrative examples of include the perceptual shift in white balance when transitioning from daylight (approximately 6500K, bluish) to (around 3200K, reddish), where neutral surfaces like continue to appear achromatic after despite their physically altered spectral reflectance. Similarly, operates in shadowed regions, where cooler skylight illumination casts bluish tints, yet surfaces such as skin or foliage maintain their perceived hues through local and contextual cues, as demonstrated in studies of cast shadows under natural scenes. These phenomena highlight 's role in everyday vision, preventing drastic color distortions from transient variations. Recent advancements incorporate Bayesian frameworks to model chromatic adaptation, treating it as probabilistic inference that combines prior knowledge of natural illuminants with current sensory input to optimize color . For instance, Bayesian observer models reveal implicit priors for daylight spectra in hue tasks, explaining biases in under non-neutral illuminants and extending von Kries predictions to more complex scenes. These approaches, developed in the , account for incomplete in real-world variability, offering improved simulations for perceptual metrics.

Color Vision Deficiencies

Color vision deficiencies, also known as , represent impairments in the of color that deviate from the typical trichromatic vision experienced by most individuals, where subtle differences in hue, saturation, or are harder to distinguish. These conditions can significantly alter subjective color experiences, such as confusing reds and greens in everyday tasks like identifying ripe or traffic signals. The most prevalent forms are congenital and affect the red-green color axis, while rarer variants impact blue-yellow or result in complete color absence. Congenital color vision deficiencies primarily stem from genetic alterations in the genes responsible for photoreceptor function. Protanomaly and deuteranomaly, the most common types, involve weakened sensitivity in the long-wavelength () and medium-wavelength () s, respectively, leading to difficulties in discriminating reds from greens; deuteranomaly is the most frequent subtype overall. These red-green defects affect approximately 8% of males and 0.5% of females due to their pattern. Tritanomaly, a rarer blue-yellow deficiency caused by in the short-wavelength () , impacts fewer than 1 in 10,000 people and affects males and females equally as it is autosomal. , or total , results in the near-complete loss of color perception, relying instead on rod-mediated vision, and occurs in about 1 in 30,000 individuals. The genetic basis for red-green deficiencies lies in or hybrid gene formations in the X-linked OPN1LW (long-wave) and OPN1MW (medium-wave) s, located on the at Xq28; heterozygous females may exhibit milder symptoms due to mosaicism, while hemizygous males are more severely affected. Inheritance follows an X-linked recessive mode, with carrier mothers passing the trait to sons at a 50% probability. Blue-yellow defects arise from autosomal dominant in OPN1SW on 7. Diagnosis of these deficiencies typically involves standardized clinical tests to assess cone function and classify severity. The Ishihara pseudoisochromatic plates, consisting of dotted patterns that reveal numbers or shapes visible only to those with normal or specific deficient vision, are widely used for screening red-green defects, detecting protanomaly and deuteranomaly with high sensitivity in males. For more precise quantification, the anomaloscope employs a bipartite field where patients match a yellow light by mixing red and green, allowing differentiation between anomaly types and degrees of severity; it serves as the gold standard for confirming diagnoses. Prevalence data from population studies indicate red-green deficiencies at 5-8% in males globally, with tritan defects at approximately 0.008-0.01%. Acquired color vision deficiencies can develop later in life due to environmental or pathological factors, often affecting the blue-yellow axis more prominently and potentially reversible upon treatment of the underlying cause. Conditions such as cataracts, which scatter light and alter spectral transmission, lead to tritan-like shifts in color perception that improve post-surgery. Diabetes mellitus, particularly type 2, is associated with early color vision impairments even without , involving tritan deficiencies linked to metabolic stress on cells and occurring in up to 20-30% of patients. Emerging gene therapies offer promise for treating congenital forms, particularly . In 2023 clinical trials, AAV-mediated delivery of functional genes, such as CNGA3 or CNGB3, to cells partially restored color discrimination in patients with complete , enabling detection of hues against grayscale backgrounds, though improvements were limited and variable. As of 2025, ongoing Phase 1/2 trials and long-term follow-ups continue to demonstrate and modest efficacy in restoring some color vision, with challenges in full trichromatic recovery persisting. These trials, building on preclinical success in animal models, highlight ongoing challenges in achieving full trichromatic restoration but represent a high-impact advancement in retinal .

Color Vision Across Species

Invertebrate Systems

Invertebrate color vision exhibits remarkable diversity, often mediated by compound eyes that integrate multiple photoreceptor types to detect a broad spectrum of wavelengths, including beyond human perception. Unlike the trichromatic basis of human vision briefly referenced in theoretical frameworks, invertebrate systems frequently incorporate UV sensitivity and polarization detection, adapting to ecological niches such as or . In insects like honeybees, color vision is trichromatic, relying on three types of photoreceptors in the ommatidia of compound eyes, with spectral sensitivity peaks at approximately 344 nm (ultraviolet), 436 nm (blue), and 556 nm (green). These rhodopsins enable bees to discriminate colors crucial for flower identification and navigation, perceiving ultraviolet patterns invisible to humans. The compound eye structure, with thousands of ommatidia, facilitates this broad spectral detection by distributing photoreceptors across a wide visual field. Cephalopods, such as octopuses and , possess complex camera-like eyes but exhibit limited color vision due to a single visual type, rendering them effectively color-blind in behavioral tasks. Instead, they heavily rely on polarization sensitivity in their rhabdomeric photoreceptors to detect environmental cues, enhancing contrast for prey identification and in dynamic underwater light fields. This compensates for the absence of chromatic , allowing effective visual without spectral opponency. Among crustaceans, (stomatopods) represent an extreme, with 12 to 16 distinct photoreceptor classes spanning to wavelengths, potentially enabling . However, post-2015 studies debate the perceptual dimensionality of this system, suggesting it prioritizes rapid temporal signaling and polarization over fine color discrimination; behavioral experiments indicate mantis shrimp perform worse than humans or bees in hue distinction tasks, implying a non-opponent mechanism tuned for dynamic environments like coral reefs. The evolution of compound eyes in arthropods and other invertebrates has enabled this broad spectral detection, with ommatidial units incorporating diverse opsins to sample light across extended ranges, contrasting with simpler pit eyes in ancestral forms and supporting specialized visual ecologies.

Vertebrate Adaptations

Vertebrates exhibit diverse adaptations in color vision, shaped by ecological niches and evolutionary pressures. Many species, particularly those in shallow waters, possess tetrachromatic vision enabled by four types of cone photoreceptors sensitive to (UV), , , and wavelengths. For instance, the (Carassius auratus) demonstrates through behavioral experiments matching white light with primaries at approximately 367 nm (UV), 434 nm (), 523 nm (), and 641 nm (), allowing enhanced discrimination in aquatic environments rich in spectral complexity. Recent genomic studies on fishes from reveal adaptive evolution in visual , where shifts in cone transcriptomes correlate with habitat-specific light conditions, underscoring the role of genetic variation in fine-tuning color perception across lineages. Birds have similarly advanced tetrachromatic systems, incorporating UV sensitivity alongside , green, and blue cones, which expands their beyond human . A key is the presence of colored oil droplets in cone photoreceptors, which act as spectral filters to sharpen wavelength discrimination and enhance under varying light. These droplets, containing or other pigments, preferentially transmit specific bands (e.g., droplets filter shorter wavelengths), improving the detection of subtle variations critical for and communication. In behavioral contexts, such as mate selection in European starlings (Sturnus vulgaris), females prefer males with higher UV reflectance in when UV light is available, demonstrating how influences by revealing signals invisible to humans. Reptiles and amphibians generally display di- or trichromatic color vision, with adaptations reflecting diurnal or nocturnal lifestyles. Most diurnal reptiles possess three types sensitive to short (UV/), medium (), and long () wavelengths, supporting suited to terrestrial habitats. However, nocturnal species, such as certain geckos, exhibit or reduced color , relying on transmuted rod-like cones that enable color at extremely low light levels where humans perceive only . Amphibians often combine cones with a dual rod system—red and —that facilitates rudimentary color vision in dim conditions, as seen in frogs where these support between wavelengths during nocturnal activity. In mammals, color vision underwent significant simplification following the dinosaur extinction around 66 million years ago, when early mammals adopted nocturnal habits and lost UV-sensitive cones, resulting in widespread based on short-wavelength () and long-wavelength () receptors. This "" limited most modern mammals to two cone types, prioritizing scotopic sensitivity over spectral breadth. An exception occurs in , including humans, where a duplication of the long-wavelength on the restored , enabling discrimination of red-green hues advantageous for detecting ripe fruit and young leaves in arboreal environments.

Evolutionary Development

Origins in Ancestral Organisms

The evolutionary origins of color vision predate the period, emerging from ancient light-detection mechanisms in unicellular organisms. proteins, the foundational light-sensitive molecules for phototransduction, first appeared in single-celled eukaryotes more than 700 million years ago during the Pre-Cambrian era, enabling rudimentary responses to light such as phototaxis. These early likely functioned in non-visual roles before adapting for vision, marking the initial step toward spectral discrimination in multicellular life. In early metazoans, such as cnidarians, the development of ciliary photoreceptors represented a key advancement toward basic color vision. These photoreceptors, structurally similar to those in vertebrates, supported dichromatic capabilities by expressing multiple opsins sensitive primarily to wavelengths, allowing simple discrimination of spectral contrasts for environmental . This configuration provided cnidarians with an edge in detecting light gradients and potential threats or resources in aquatic habitats. The , approximately 540 million years ago, amplified the selective pressures favoring color vision as animal diversity surged. A 2024 study indicates that animal color vision emerged around 500 million years ago, with a dramatic explosion in color signals over the subsequent 100 million years, predating colorful fruits (∼350 million years ago) and flowers (∼200 million years ago). Enhanced visual discrimination offered critical advantages in predation, prey evasion, and mate selection, contributing to an that propelled the rapid diversification of bilaterian lineages. records of early compound eyes and genetic analyses underscore how these visual innovations coincided with ecological shifts toward complex interactions. Supporting this timeline, fossil and genetic evidence highlights the deep conservation of genes across animal phyla, indicating a shared ancestral toolkit for color . These genes, preserved through billions of years of , show minimal structural changes in core domains, facilitating spectral tuning in diverse lineages. Recent paleogenomic reconstructions of early bilaterian genomes reveal an ancestral repertoire of at least seven (potentially up to 11) genes, including both ciliary and rhabdomeric types, which underpinned the transition to multifaceted color discrimination.

Advancements in Mammals and Primates

Early mammals experienced a around 100 million years ago during the period, when they adapted to nighttime activity to avoid diurnal predators, leading to the loss of short-wavelength-sensitive (S) cones and resulting in widespread across mammalian lineages. This evolutionary constraint reduced cone-based color discrimination to primarily long-wavelength-sensitive (L) cones and rod photoreceptors, optimizing but limiting chromatic capabilities. In , color vision advanced through genetic innovations, particularly in haplorhine lineages. monkeys (catarrhines) achieved uniform via a tandem duplication of the X-linked approximately 30-40 million years ago, producing distinct medium-wavelength-sensitive (M) and opsins alongside retained opsins, enabling discrimination of red-green hues. This duplication event marked a key regain of trichromatic potential lost in early mammals, enhancing visual foraging in diurnal environments. New World monkeys (platyrrhines) exhibit polymorphic , where males and homozygous females are dichromatic, but heterozygous females gain through allelic variation in the X-linked locus, allowing variable red-green sensitivity across individuals. This system arose from a single ancestral gene with polymorphic variants, contrasting the fixed duplication in . Selective pressures driving these advancements primarily involved enhanced detection of ripe fruits against green foliage, with providing advantages in identifying and orange signals from a distance. Studies on foraging behaviors support this, showing trichromatic individuals outperform dichromats in locating camouflaged food items. In strepsirrhine like lemurs, recent analyses reveal retained with occasional polymorphic in females, reflecting basal evolutionary states and ongoing adaptations to Madagascar's diverse habitats, though without the full gene duplications seen in simians.

Mathematical and Computational Models

Color Spaces

Color spaces provide mathematical frameworks for representing and standardizing colors in a way that bridges human perception with computational and industrial applications. These models abstract the biological basis of color vision into coordinate systems that facilitate device-independent color specification, reproduction, and comparison. The development of such spaces began in the early 20th century to address inconsistencies in earlier RGB-based systems tied to specific devices. The CIE 1931 XYZ color space, established by the (CIE), was the first device-independent model derived from extensive human color-matching experiments conducted by researchers like William David Wright and John Guild. It uses tristimulus values X, Y, and Z, where Y corresponds to and X and Z are imaginary primaries chosen to ensure all real colors have positive coordinates. This space transforms from device-specific RGB values through a linear matrix, enabling consistent color representation across illuminants and observers, such as the standard 2° or 10° . In contrast to Cartesian models like XYZ, the HSV (Hue, Saturation, Value) and HSB (Hue, Saturation, ) color spaces offer cylindrical representations more intuitive for perceptual adjustments in graphics and design. Introduced by in 1978, HSV models colors with hue as an angular component around a central axis (0° to 360° for spectral progression), saturation as radial distance from the neutral axis (0 for to 1 for pure color), and value or as height from black (0) to maximum intensity (1). These models facilitate intuitive manipulations, such as varying saturation independently of , and are widely used in software despite not being perceptually uniform. To achieve perceptual uniformity—where equal numerical distances correspond to equal perceived differences—subsequent spaces built on XYZ. The CIELAB (Lab*) space, recommended by the CIE in 1976, transforms XYZ coordinates into lightness (L*, 0 for black to 100 for white), a* (red-green opponent axis), and b* (yellow-blue opponent axis), approximating uniform spacing in human vision. It includes the ΔE metric, defined as the Euclidean distance √[(ΔL*)² + (Δa*)² + (Δb*)²], to quantify just-noticeable color differences, with values below 1 often imperceptible. Recognizing limitations in CIELAB's uniformity, particularly for blue hues and chroma interactions, the CIE introduced the CIEDE2000 (ΔE₀₀) formula in 2001 as an advanced color-difference metric. This update incorporates weighting functions for lightness, chroma, and hue, plus a rotational term to account for interactions, improving accuracy over the original ΔE by up to 20-30% in visual assessments. CIEDE2000 remains the recommended standard for industrial color quality control, such as in textiles and paints, where precise matching is critical.

Perceptual Metrics and Simulations

Perceptual metrics in color vision quantify the smallest distinguishable differences between colors, known as the (JND), which follows an adaptation of Weber's law stating that the JND is proportional to the magnitude of the stimulus. In color perception, this law applies unevenly across attributes like hue, saturation, and brightness, with early experimental work by revealing elliptical regions in chromaticity space where color differences are imperceptible, varying in size and orientation to reflect non-uniform human sensitivity. The , developed by the (CIE) in 1976, approximates perceptual uniformity by defining the color difference metric ΔE, where a value of approximately 1 corresponds to a single JND under reference viewing conditions, enabling practical assessments of color distinguishability. Estimates based on these perceptual metrics suggest that the human eye can distinguish approximately 1 million to 10 million different colors. Computational models extend these metrics to simulate dynamic aspects of color perception, such as constancy under varying illumination. The Retinex algorithm, proposed by Edwin Land in 1977, models color constancy by computing independent long-, medium-, and short-wave retinex channels that estimate surface reflectance through spatial comparisons, achieving robustness to illuminant changes observed in human vision. Neural network simulations further replicate cortical processing, with models of primary visual cortex (V1) emphasizing wavelength detection and opponent processes, while simulations of extrastriate area V4 integrate contextual cues for hue perception and color categorization. For instance, brain-optimized deep neural networks trained on functional MRI data predict V1-V4 responses to color stimuli, capturing hierarchical feature extraction from edge detection in V1 to object-level color invariance in V4. These metrics and models underpin applications in and . In , gamut mapping algorithms use perceptual metrics like ΔE to compress colors from wide-gamut sources (e.g., HDR displays) into narrower device gamuts while minimizing visual distortions, often employing contrast reduction to preserve and hue as perceived by humans. In AI, models detect color vision deficiencies, for example through unsupervised clustering of behavioral task data, achieving high agreement with traditional diagnostic methods for classifying anomalies like deuteranomaly. Recent advances as of 2025 include the HVI color space for low-light image enhancement, which reduces noise in HSV-based , and computational frameworks simulating the of trichromatic color vision through eye and cortical interactions. Despite their utility, perceptual metrics face limitations from cultural influences on color discrimination. Studies comparing speakers of languages with distinct color categories, such as English (with separate terms) and Korean (with additional distinctions), find no significant reduction in JND thresholds at linguistic boundaries, suggesting metrics like ΔE may overlook subtle experiential or environmental factors shaping across cultures.

References

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