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Color vision is the capacity of an organism or machine to distinguish objects based on the wavelengths (or frequencies) of the light they reflect or emit. The nervous system derives color by comparing the responses to light from the several types of cone photoreceptors in the eye. These cone photoreceptors are sensitive to different portions of the visible spectrum. For humans, the visible spectrum ranges approximately from 380 to 750 nm, and there are normally three types of cones. The visible range and number of cone types differ between species.
A 'red' apple does not emit red light. Rather, it simply absorbs all the frequencies of visible light shining on it except for a group of frequencies that is perceived as red, which are reflected. An apple is perceived to be red only because the human eye can distinguish between different wavelengths. Three things are needed to see color: a light source, a detector (e.g. the eye) and a sample to view. The advantage of color, which is a quality constructed by the visual brain and not a property of objects as such, is the better discrimination of surfaces allowed by this aspect of visual processing.
In order for animals to respond accurately to their environments, their visual systems need to correctly interpret the form of objects around them. A major component of this is perception of colors.
Color perception[edit | edit source]
Perception of color is achieved in mammals through color receptors containing pigments with different spectral sensitivities. In most primates closely related to humans there are three types of color receptors (known as cone cells). This confers trichromatic color vision, so these primates, like humans, are known as trichromats. Many other primates and other mammals are dichromats, and many mammals have little or no color vision.
In the human eye, the cones are maximally receptive to short, medium, and long wavelengths of light and are therefore usually called S-, M-, and L-cones. L-cones are often referred to as the red receptor, but while the perception of red depends on this receptor, microspectrophotometry has shown that its peak sensitivity is in the yellow region of the spectrum.
The peak response of human color receptors varies, even amongst individuals with 'normal' color vision; in non-human species this polymorphic variation is even greater, and it may well be adaptive.
Cone cells in the human eye[edit | edit source]
|Cone type||Name||Range||Peak sensitivity|
|S||β (Blue)||400..500 nm||420 nm|
|M||γ (Bluish-Green)||450..630 nm||534 nm|
|L||ρ (Yellowish-Green)||500..700 nm||564 nm|
A particular frequency of light stimulates each of these receptor types to varying degrees. Red light, stimulates almost exclusively L-cones, and blue light almost exclusively S-cones. The visual system combines the information from each type of receptor to give rise to different perceptions of different wavelengths of light.
The pigments 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 codes for the pigment that responds to yellowish-green light, is highly polymorphic (a recent study by Verrelli and Tishkoff, 2004, found 85 variants in a sample of 236 men), so it is possible for a woman to have an extra type of color receptor, and thus a degree of tetrachromatic color vision [How to reference and link to summary or text]. Variations in OPN1MW, which codes for the bluish-green pigment, appear to be rare, and the observed variants have no effect on spectral sensitivity.
Color processing begins at a very early level in the visual system (even within the retina) through initial color opponent mechanisms. Opponent mechanisms refer to the opposing color effect of red-green, blue-yellow, and light-dark. Visual information is then sent back via the optic nerve to the optic chiasm: 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 chiasm the visual fiber tracts are referred to as the optic tracts, which enter the thalamus to synapse at the lateral geniculate nucleus (LGN). The LGN is segregated into six layers: two magnocellular (large cell) achromatic layers (M cells) and four parvocellular (small cell) chromatic layers (P cells). Within the LGN P-cell layers there are two chromatic opponent types: red vs. green and blue vs. green/red.
After synapsing at the LGN, the visual tract continues on back toward 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; their existence in primates was suggested by David Hubel and Torsten Wiesel and subsequently proven by Bevil Conway. 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. 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.
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 area V4. Area V4 is a relatively large visual area, the largest by far cortical area outside V1, encompassing almost as much cortex as V1. Neurons in V4 were originally proposed by Semir Zeki to be exclusively dedicated to color, but this has since been shown not to be the case. Quantitative studies have argued that there is no higher concentration of color cells in V4 than in primary visual cortex, although this remains controversial. Independent of color sensitivity, V4 neurons have been shown to be very sensitive to the shape of stimuli, curvature, and stereo-scopic depth. V4 neurons have also been shown to be modulated by attention. The role of V4 neurons in color vision remains to be better characterized: indeed the vast majority of scientific papers examining the function of V4 do not concern color processing.
Anatomical studies have shown that neurons in 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 many other features.
Other animals enjoying three, four or even five color vision systems include tropical fish and birds. In the latter case tetrachromacy is achieved through up to four cone types, depending on species. Brightly colored oil droplets inside the cones shift the spectral sensitivity of the cell. (Some species of bird such as the pigeon in fact possess five distinct types of droplet and may thus be pentachromats). Mammals other than primates generally have less effective two-receptor color perception systems, allowing only dichromatic color vision; marine mammals have only a single cone type and are thus monochromats.
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 (mature) 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.
Mathematics of color perception[edit | edit source]
A "physical color" is a combination of pure spectral colors (in the visible range). Since there are, in principle, infinitely many distinct spectral colors, the set of all physical colors may be thought of as an infinite-dimensional vector space, in fact a Hilbert space. We call this space Hcolor. (More technically, the space of physical colors may be considered to be the (mathematical) cone over the simplex whose vertices are the spectral colors.)
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 r(w), g(w), b(w) corresponding to the so-called "red", "green", and "blue" cone cells, respectively.
Finally, 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(w)*r(w) (for red), of C(w)*g(w) (for green), and of C(w)*b(w) (for blue). The triple of resulting numbers associates to each physical color C in Hcolor a particular perceptual color in R3color. This association is easily seen to be linear.
Thus human color perception is determined by a specific 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 perceptual color (technically: chromaticity) while increasing its perceived intensity.) Taking a cross-section of this cone for a fixed perceptual intensity yields, approximately, the space of chromaticities. At least in theory!
In practice, however, it would be quite difficult to measure an individual's cones' 3 responses to various physical color stimuli. So instead, three specific benchmark test lights are chosen once and for all; let us call them R, G, and B. In order 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 (I_R, I_G, I_B) for the R, G, and B 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 (I_R, I_G, I_B) matches). Note that in practice, often at one of R, G, B 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 virtually identical.
By considering all the resulting combinations of intensities (I_R, I_G, I_B) as a subset of 3-space, a model for human perceptual color space is formed. (Note that when one of R, G, B 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 R,G,B light. Again, a cross-section of this cone for a constant intensity is a planar shape that is (by definition) the space of "chromaticities" (informally: distinct colors), and this is precisely the CIE 1931 color space, also known as the CIE chromaticity diagram.
It should be noted that this setup implies that for each (non-spectral) perceptual color P there are infinitely many distinct physical colors that are each perceived as P. So, in general there is no such thing as the combination of spectral colors that we perceive as (say) red; instead there are infinitely many possibilities.
Incidentally, the CIE chromaticity diagram is horseshoe-shaped, with its curved edge corresponding to all spectral colors, and the remaining straight edge corresponding to the "purples" -- various mixtures of the red and violet that appear at the extremes of the spectrum. The striking fact that the curved edge of spectral colors is convex in this diagram cannot be explained by the mathematics of this setup. Rather, it is simply an observed fact that is probably explained by evolution's giving human color vision the qualities that would most support survival of the species.
Chromatic adaptation[edit | edit source]
An object may be viewed under various conditions. For example, it may be illuminated by the sunlight, the light of a fire, or a harsh electric light. In all of these situations, the visual system indicates that the object has the same color: an apple always appears red, whether viewed at night or during the day. This feature of the visual system is called chromatic adaptation, or color constancy; when the correction occurs in a camera it is referred to as white balance.
Chromatic adaptation is one aspect of vision that may fool someone into observing an optical illusion. Though the human visual system generally does maintain constant perceived color under different lighting, there are situations where the brightness of a stimulus will appear reversed relative to its "background" when viewed at night. For example, the bright yellow petals of flowers will appear dark compared to the green leaves in very dim light. The opposite is true during the day. This is known as the Purkinje effect.
References[edit | edit source]
- Neitz, Jay & Jacobs, Gerald H. (1986). "Polymorphism of the long-wavelength cone in normal human colour vision." Nature. 323, 623-625.
- Jacobs, Gerald H. (1996). "Primate photopigments and primate color vision." PNAS. 93 (2), 577–581.
- Wandell, B. "Foundations of Vision". Sinauer Press, MA.
- Kandel E, Schwartz J, Jessel T. Principles of Neural Science. 4th ed. New York: McGraw-Hill; 2000. ISBN 0-8385-7701-6
- Martin, Paul R (1998). "Colour processing in the primate retina: recent progress." Journal of Physiology. 513 (3), 631-638.
- Nolte J. The Human Brain: An Introduction to Its Functional Anatomy. 5th ed. St. Louis: Mosby, Inc.; 2002. ISBN 0-323-01320-1* Rowe, Michael H (2002).
- Michael H. Rowe "Trichromatic color vision in primates." News in Physiological Sciences. 17 (3), 93-98.
- Verrelli, BC; Tishkoff, S (2004). "Color vision molecular variation." American Journal of Human Genetics. 75 (3), 363-375.
- Conway, BR (2001). "Spatial structure of cone inputs to color cells in alert macaque primary visual cortex (V-1)" Journal of Neuroscience. 21 (8), 2768-2783.
- McCann, M., ed. 1993. Edwin H. Land's Essays. Springfield, Va.: Society for Imaging Science and Technology.
- Byrne, Alex; Hilbert, D.S. (1997). Readings on Color, Volume 2: The Science of Color, 2nd ed., Cambridge, Massachusetts: MIT Press. ISBN 0-262-52231-4.
- Kaiser, Peter K.; Boynton, R.M. (1996). Human Color Vision, 2nd ed., Washington, DC: Optical Society of America. ISBN 1-55752-461-0.
- Wyszecki, Günther; Stiles, W.S. (2000). Color Science: Concepts and Methods, Quantitative Data and Formulae, 2nd edition, New York: Wiley-Interscience. ISBN 0-471-39918-3.
- McIntyre, Donald (2002). Colour Blindness: Causes and Effects, UK: Dalton Publishing. ISBN 0-9541886-0-8.
- Shevell, Steven K. (2003). The Science of Color, 2nd ed., Oxford, UK: Optical Society of America. ISBN 0-444-512-519.
See also[edit | edit source]
- Abney effect
- Bezold-Brucke effect
- Color additivity
- Colour vision in diabetes
- Inverse hues
- Inverted spectrum
- Primary color
- Retinal zones
- Visual perception
- Young-Helmholtz theory
[edit | edit source]
- "Evidence that men, women literally see the world differently: Study shows color vision may have been adaptive during evolution."
- Colour vision.
- Spectral Sensitivity of the Eye.
- Vision may not be what we thought.
- Overview of color vision.
- The decoding model: a symmetrical model of color vision.
- Dale Purves Lab
|Color vision [Edit]|
|Color vision | Color blindness|
|Monochromat | Dichromat | Trichromat | Tetrachromat | Pentachromat|
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