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Chromaticity
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The CIE 1931 xy chromaticity space, also showing the chromaticities of black-body light sources of various temperatures, and lines of constant correlated color temperature
sRGB gamut plotted in CIE xyY color space. x and y are the chromaticity axes, the Y axis represents (linear) luminance.

Chromaticity is an objective specification of the quality of a color regardless of its luminance. Chromaticity consists of two independent parameters, often specified as hue (h) and colorfulness (s), where the latter is alternatively called saturation, chroma, intensity,[1] or excitation purity.[2][3] This number of parameters follows from trichromacy of vision of most humans, which is assumed by most models in color science.

Quantitative description

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In color science, the white point of an illuminant or of a display is a neutral reference characterized by a chromaticity; all other chromaticities may be defined in relation to this reference using polar coordinates. The hue is the angular component, and the purity is the radial component, normalized[clarification needed] by the maximum radius for that hue.

Purity is roughly equivalent to the term saturation in the HSV color model. The property hue is as used in general color theory and in specific color models such as HSL and HSV color spaces, though it is more perceptually uniform in color models such as Munsell, CIELAB or CIECAM02.

Some color spaces separate the three dimensions of color into one luminance dimension and a pair of chromaticity dimensions. For example, the white point of an sRGB display is an x, y chromaticity of (0.3127, 0.3290), where x and y coordinates are used in the xyY space.

(u′, v′), the chromaticity in CIELUV, is a fairly perceptually uniform presentation of the chromaticity as (another than in CIE 1931) planar Euclidean shape. This presentation is a projective transformation of the CIE 1931 chromaticity diagram above.

These pairs determine a chromaticity as affine coordinates on a triangle in a 2D-space, which contains all possible chromaticities. These x and y are used because of simplicity of expression in CIE 1931 (see below) and have no inherent advantage. Other coordinate systems on the same X-Y-Z triangle, or other color triangles, can be used.

On the other hand, some color spaces such as RGB and XYZ do not separate out chromaticity, but chromaticity is defined by a mapping that normalizes out intensity, and its coordinates, such as r and g or x and y, can be calculated through the division operation, such as x = ⁠X/X + Y + Z⁠, and so on.

The xyY space is a cross between the CIE XYZ and its normalized chromaticity coordinates xyz, such that the luminance Y is preserved and augmented with just the required two chromaticity dimensions.[4]

See also

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Wikimedia Commons has media related to Chromatic diagrams.

References

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Chromaticity

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Chromaticity is the property of a colour stimulus defined by its chromaticity coordinates, or by its dominant or complementary wavelength and purity taken together, specifying the quality of a color independent of its luminance or brightness.[1] In color science, it separates the hue and saturation aspects of color from intensity, allowing for precise description of color tones in fields such as photometry, imaging, and display technology.[2] This concept forms a foundational element of standardized color models, enabling consistent reproduction and comparison of colors across devices and illuminants.[3] The modern framework for chromaticity originated with the International Commission on Illumination (CIE) in 1931, based on extensive color-matching experiments conducted with human observers using monochromatic primaries at wavelengths of 700 nm (red), 546.1 nm (green), and 435.8 nm (blue).[3] These experiments led to the CIE XYZ tristimulus color space, where colors are quantified by three values—X, Y, and Z—derived from the spectral power distribution of light weighted by standard observer sensitivity functions.[4] Chromaticity coordinates are then calculated as normalized ratios: $ x = \frac{X}{X + Y + Z} $, $ y = \frac{Y}{X + Y + Z} $, and $ z = 1 - x - y $, with only x and y needed since their sum with z equals unity.[5] The Y value retains luminance information, making the xyY space a practical extension for applications requiring both color and brightness specification.[3] A key visualization tool is the CIE 1931 chromaticity diagram, a two-dimensional plane where points defined by x and y coordinates represent all perceivable chromaticities, forming a horseshoe-shaped locus bounded by the spectral colors of the visible spectrum (approximately 380–780 nm) and the line of purples.[6] In this diagram, the ordinate is y and the abscissa is x, with the interior points indicating mixtures of spectral colors and the boundary denoting maximum saturation; equal distances do not correspond to equally perceptible differences, a limitation addressed in later uniform chromaticity scales.[4] The diagram's white point, often at x ≈ 0.333, y ≈ 0.333 for equal-energy illuminant E, serves as a reference for neutral colors.[3] Subsequent refinements include the CIE 1960 UCS (Uniform Chromaticity Scale) diagram using u, v coordinates for better perceptual uniformity and the 1976 u', v' scale, which corrects distortions in the green region of the 1931 diagram.[4] Chromaticity specifications are essential in industries like lighting (e.g., LED color binning), printing, and computer graphics, where they ensure color fidelity under varying conditions, and continue to underpin advanced color spaces like CIELAB for difference metrics.[7]

Fundamentals

Definition

Chromaticity is a two-dimensional representation of a color's hue and saturation, excluding its brightness or luminance.[2][8] This quality allows for the specification of color tones in a way that remains invariant under changes in intensity, focusing solely on the perceptual attributes that distinguish one color from another regardless of how bright or dim it appears.[2][9] In color science, chromaticity describes the relative proportions of primary colors—typically red, green, and blue—required to match a given color through additive mixing, without accounting for the scaling factor that determines overall intensity.[4] These proportions capture the color's qualitative essence, enabling consistent reproduction across different lighting conditions or media.[2] For example, each pure spectral color corresponds to a distinct point in chromaticity space, reflecting its unique hue, while mixtures that produce white light can exhibit subtle variations in hue—such as warmer or cooler tones—but these mixtures share the same brightness level only if their luminances are equivalent.[4][2] Conceptually, chromaticity differs from tristimulus values, such as those in the CIE XYZ system, by normalizing the total stimulus to eliminate the influence of luminance, thereby isolating the color's non-intensity components.[8] In the foundational CIE 1931 color space, this normalization provides a standardized framework for chromaticity.[4]

Relation to Color Perception

Chromaticity provides a model for human color perception by projecting the three-dimensional tristimulus color space onto a two-dimensional plane, effectively isolating the chromatic aspects of color—hue and saturation—from luminance or brightness. This separation aligns with psychophysical principles of human vision, including the opponent-process theory, which describes color processing through antagonistic channels: red-green and blue-yellow opponency, distinct from the achromatic luminance pathway. Standard chromaticity coordinates, however, are based on tristimulus values derived from color-matching experiments, with opponent dimensions incorporated in later uniform color spaces like CIELUV to better approximate how the visual system encodes color independently of intensity. In this framework, perceptual correlates of color are mapped directly onto chromaticity coordinates: hue is quantified by the angular position of a point relative to a reference white point in the chromaticity diagram, reflecting the dominant wavelength or opponent channel balance perceived by the observer. Saturation, or colorfulness relative to a neutral achromatic stimulus, corresponds to the radial distance from the white point, indicating the strength of the chromatic signal against a desaturated background. These attributes stem from experimental color-matching data that underpin standard colorimetry, ensuring that chromaticity coordinates predictably describe how humans distinguish color differences under controlled viewing conditions.[10] However, early chromaticity representations, such as the CIE 1931 diagram, exhibit limitations in perceptual uniformity due to the non-linear nature of human visual responses, where equal geometric distances do not equate to equally noticeable color shifts. This non-uniformity was quantified through studies like MacAdam ellipses, which illustrate elliptical regions of just-noticeable differences rather than circular ones, highlighting distortions particularly in the green and blue regions. These perceptual inaccuracies prompted the creation of improved uniform spaces, such as CIELUV, which incorporate opponent-color transformations to better align coordinate distances with human sensitivity.[11][12] A key example of chromaticity's role in perception is its explanation of metamerism, where two spectrally distinct stimuli produce identical tristimulus values—and thus the same chromaticity coordinates—under a specific illuminant, leading observers to perceive them as matching in hue and saturation despite their physical differences. Under a different illuminant, however, the chromaticity coordinates shift differently for each spectrum, resulting in a perceived hue mismatch. This phenomenon underscores how chromaticity captures the human eye's reliance on integrated spectral responses rather than full spectral detail, a foundational insight from color-matching experiments.[13][14]

Historical Development

Early Concepts

The foundations of chromaticity concepts emerged in the 19th century through pioneering work in color vision and mixing, building on empirical observations of how colors combine without reliance on intensity. Thomas Young proposed the trichromatic theory of color vision in the early 1800s, suggesting that human color perception arises from three distinct types of retinal receptors sensitive to different wavelength ranges, laying the groundwork for separating hue from brightness in visual sensations.[15] This idea, initially outlined in Young's 1802 Bakerian Lecture, emphasized that all observable colors could be produced by mixing three primaries, providing an early conceptual basis for representing colors independently of their luminous intensity. Hermann von Helmholtz advanced this framework in the 1850s and 1860s, elaborating on Young's theory through detailed physiological and psychophysical investigations. In his work, Helmholtz introduced the notion of three primary color sensations—red, green, and blue—and described the spectral locus as the curved boundary of pure spectral colors in a color space, where mixtures of these primaries could match most hues.[16] His experiments, including color-matching tasks, demonstrated that color perception depends on relative stimulations of these primaries rather than absolute light intensity, thus isolating chromatic qualities from luminance.[17] Helmholtz's contributions, detailed in his 1867 Handbuch der physiologischen Optik, solidified the trichromatic model and highlighted how desaturated colors result from unequal primary mixtures.[18] James Clerk Maxwell further developed these ideas in the 1860s, conducting additive color mixing experiments that confirmed trichromacy and introduced geometric representations of color mixtures. Using red, green, and blue primaries, Maxwell created a color triangle in his 1860 paper, where points within the triangle represented additive combinations of these lights, enabling the visualization of color gamuts independent of brightness. He projected spectral colors onto this plane, forming a horseshoe-shaped locus that illustrated decreasing color purity toward the center, where white or neutral tones appear from balanced mixtures.[19] Maxwell's disk-spinning apparatus and photometric measurements quantified how intensity variations do not alter the chromatic position, establishing a precursor to modern chromaticity separation.[20] These 19th-century advancements set the stage for 20th-century international standardization efforts.

CIE Standardization

In the 1920s and 1930s, the International Commission on Illumination (CIE) advanced the standardization of color measurement through systematic experiments on human color perception, culminating in the establishment of the CIE 1931 XYZ color space. These efforts built on earlier trichromatic theories by incorporating empirical data from visual matching tests to define a device-independent framework for specifying colors. The CIE's work emphasized the need for internationally agreed-upon standards to facilitate consistent color reproduction across industries such as printing and lighting.[21] Key contributions came from British physicists William David Wright and John Guild, who conducted independent visual color-matching experiments in the late 1920s. Wright's study, involving ten observers, measured the amounts of red, green, and blue primary lights required to match monochromatic spectral colors across a 2° field of view, published in 1929. Guild's parallel investigation at the National Physical Laboratory used seven observers under similar conditions and was detailed in his 1931 paper, providing complementary data on spectral color properties. These experiments, averaging results from a total of 17 observers, demonstrated consistent patterns in human color matching while accounting for individual variations, forming the empirical basis for the CIE's standard colorimetric functions. In 1931, the CIE adopted these findings to recommend the XYZ tristimulus values as the foundation for color specification, transforming the experimental RGB data into imaginary primaries X, Y, and Z to ensure all real colors could be represented with positive values. Chromaticity coordinates were defined as $ x = \frac{X}{X + Y + Z} $ and $ y = \frac{Y}{X + Y + Z} $, projecting the three-dimensional XYZ space onto a two-dimensional plane independent of luminance for analyzing hue and saturation. This 2° standard observer, representing foveal vision, became the cornerstone of modern colorimetry, enabling precise quantification of spectral loci and mixture boundaries.[21] Recognizing limitations in the 2° observer for larger visual fields, the CIE updated the standard in 1964 with a 10° supplementary observer, derived from experiments by W. S. Stiles and J. M. Burch (1959) and L. I. Speranskaya (1959) involving wider foveal and parafoveal vision. This revision addressed discrepancies in peripheral color matching, providing more accurate functions for applications involving extended viewing angles, such as display design and environmental lighting. The 10° model supplements rather than replaces the 1931 standard, with selection based on the angular subtense of the stimulus.[22]

Quantitative Description

Chromaticity Coordinates

Chromaticity coordinates provide a method to specify the chromatic aspect of a color independently of its luminance, derived from the tristimulus values in the CIE XYZ color space. These coordinates, denoted as xx, yy, and zz, are defined as the normalized ratios:
x=XX+Y+Z,y=YX+Y+Z,z=ZX+Y+Z x = \frac{X}{X + Y + Z}, \quad y = \frac{Y}{X + Y + Z}, \quad z = \frac{Z}{X + Y + Z}
where XX, YY, and ZZ are the tristimulus values. Since x+y+z=1x + y + z = 1, only two coordinates, typically xx and yy, are needed to represent the chromaticity in a two-dimensional plane, with zz omitted for visualization.[23] These coordinates are barycentric, representing points on the plane X+Y+Z=1X + Y + Z = 1 that intersects the positive octant of the three-dimensional XYZ space. The values of xx, yy, and zz range from 0 to 1, and all physically realizable colors lie within the region bounded by the spectral locus—a curve formed by the chromaticities of monochromatic spectral lights from approximately 380 nm to 780 nm—and the line of purples connecting the endpoints. This boundary defines the gamut of human color vision under the CIE standard observer.[23][24] The normalization inherent in the definitions ensures that chromaticity coordinates are independent of the absolute luminance or intensity of the stimulus, as scaling XX, YY, and ZZ by a constant factor leaves xx and yy unchanged. For example, under CIE standard illuminant D65, the white point for a perfect reflecting diffuser has chromaticity coordinates x≈0.3127x \approx 0.3127 and y≈0.3290y \approx 0.3290, calculated from its tristimulus values X=95.047X = 95.047, Y=100.000Y = 100.000, and Z=108.883Z = 108.883.[23] In the xyxy space, chroma or saturation of a color is often approximated as the Euclidean distance from the white point (xw,yw)(x_w, y_w), given by:
s=(x−xw)2+(y−yw)2 s = \sqrt{(x - x_w)^2 + (y - y_w)^2}
This metric provides a simple measure of color vividness, with s=0s = 0 at the achromatic white point and increasing values toward the spectral locus, though it does not account for perceptual nonuniformities in the diagram.[2]

Chromaticity Diagrams

Chromaticity diagrams visualize the chromaticity coordinates of colors in a two-dimensional plane, allowing for the comparison and analysis of hues without regard to brightness. These plots map the full gamut of human-perceivable colors, serving as essential tools in color science for specification, reproduction, and perceptual evaluation. The primary diagram, established by the International Commission on Illumination (CIE), derives directly from tristimulus values but focuses solely on their normalized ratios to emphasize hue and saturation aspects. The CIE 1931 xy chromaticity diagram plots the x and y coordinates, where x = X/(X+Y+Z) and y = Y/(X+Y+Z), against each other to form a characteristic horseshoe shape. This boundary consists of the spectral locus, a curved line tracing the chromaticities of monochromatic spectral colors from wavelengths of 380 nm to 780 nm, and the straight purple line connecting the endpoints at the violet (around 380 nm) and red (around 780 nm) extremes, which delineates non-spectral colors like magentas. The diagram's interior represents all possible mixtures of these boundary colors, with the equal-energy white point—corresponding to illuminant E—at coordinates x ≈ 0.3333, y ≈ 0.3333 located centrally. Straight lines radiating from this white point to the spectral locus enable the determination of dominant wavelength, defined as the monochromatic hue that, when mixed with white light, matches the target color's appearance. Interpretive features enhance the diagram's utility for practical analysis. Excitation purity quantifies a color's saturation as the ratio of the distance from the white point to the color point along a ray to the distance from the white point to the spectral locus intersection, providing a measure of how "pure" or diluted the hue is relative to spectral light. The Planckian locus, a curved path within the diagram, plots the chromaticities of blackbody radiators across temperatures from about 1000 K (reddish) to 10000 K (bluish), facilitating the evaluation of correlated color temperatures for illuminants and light sources. These elements allow users to assess color deviations, gamuts, and perceptual attributes visually. To address perceptual non-uniformities in the xy diagram—where equal distances do not correspond to equal perceived differences—the CIE introduced the 1960 Uniform Chromaticity Scale (UCS) diagram using u and v coordinates. These are defined as $ u = \frac{4X}{X + 15Y + 3Z} $, $ v = \frac{9Y}{X + 15Y + 3Z} $, or equivalently in terms of x and y: $ u = \frac{4x}{-2x + 12y + 3} $, $ v = \frac{9y}{-2x + 12y + 3} $.[25] This variant transforms the xy values to achieve more uniform spacing for colors at similar luminance levels, reducing distortions particularly noticeable in the green and blue regions of the original plot, and is recommended for applications requiring precise color difference assessments.

Applications and Extensions

In Color Reproduction

In color reproduction, chromaticity plays a crucial role in defining the color gamut of display devices, particularly in RGB-based systems where the primaries' positions on the CIE 1931 xy chromaticity diagram determine the reproducible color range. For instance, the sRGB standard specifies primaries at red (x=0.6400, y=0.3300), green (x=0.3000, y=0.6000), and blue (x=0.1500, y=0.0600), forming a triangular gamut that ensures consistent, device-independent color rendering across monitors and web content.[26] Gamut mapping algorithms then adjust source colors to fit within this triangle, targeting these chromaticity coordinates to maintain perceptual accuracy while avoiding shifts in hue or saturation. This approach allows for reliable reproduction in consumer displays, where the white point is set at D65 (x=0.3127, y=0.3290) to simulate daylight viewing conditions.[26] Wider gamuts, such as Adobe RGB, extend the reproducible xy space for professional applications like photography, with primaries at red (x=0.6400, y=0.3300), green (x=0.2100, y=0.7100), and blue (x=0.1500, y=0.0600), also using a D65 white point (x=0.3127, y=0.3290). This configuration covers more vivid greens and cyans, encompassing approximately 50% of the CIE 1931 visible color space compared to sRGB's narrower range, enabling better fidelity for images captured in natural environments.[27][28] In printing technologies, color specifications guide the matching of spot colors within CMYK processes, where device-specific profiles map desired color values to ink combinations for accurate hue reproduction on substrates like paper. For example, spot colors from systems like Pantone are targeted using their defined color values, such as CIELAB, to simulate precise matches, often requiring conversion from CIE XYZ tristimulus values. Undercolor removal (UCR) further optimizes this by reducing overlapping cyan, magenta, and yellow inks in shadow areas, replacing them with black to adjust luminance while preserving the original hue, minimizing ink usage and preventing muddy tones.[29][30] Gamut limitations arise when source colors fall outside the device's triangular boundary in the chromaticity diagram, such as vivid greens beyond sRGB's green primary, necessitating clipping—projecting the color to the nearest gamut edge—or simulation via perceptual mapping to approximate the intent. These out-of-gamut colors are quantified by their Euclidean distance in the xy plane to the boundary, guiding algorithms to minimize perceptual distortion in reproduction. Clipping maintains hue along rays from the white point but can desaturate colors, while more advanced simulations compress the gamut to preserve relative differences.[28][31]

In Modern Color Spaces

Modern color spaces have evolved from the CIE 1931 chromaticity coordinates to incorporate perceptual uniformity and account for human vision under varying conditions, integrating chromaticity into three-dimensional models that separate lightness from color attributes. The CIELAB (Lab*) space, standardized by the CIE in 1976, represents colors with L* for lightness and a* (red-green opponent) and b* (yellow-blue opponent) as chromaticity coordinates, where the hue angle is derived as h = atan2(b*, a*). This design aims to provide more uniform spacing in the chromaticity plane compared to the original xy diagram, facilitating accurate color difference calculations in industries like textiles and printing. Similarly, the CIELUV (Luv*) space, also from 1976, uses L* for lightness and u* and v* for chromaticity, optimized for additive color mixing such as in displays, with improved uniformity for saturated colors. Both spaces transform CIE XYZ tristimulus values nonlinearly to approximate perceptual distances, though they assume a fixed white point like D65 without full adaptation modeling.[32][33] Further advancements address limitations in hue linearity and viewing condition dependencies through appearance models that incorporate chromatic adaptation. The IPT color space, developed in 1998, refines chromaticity representation by deriving opponent signals I (lightness), P (red-green), and T (yellow-blue) from cone responses, achieving better constant-hue loci and uniformity for image processing applications. It uses a chromatic adaptation transform based on earlier models like CIECAM97s to handle illuminant shifts, making it suitable for cross-media color reproduction. Building on this, the CIECAM02 model, published by the CIE in 2002, extends chromaticity handling by computing adapted correlates like chroma (C) and hue angle (h) after a von Kries-style adaptation in LMS cone space, accounting for surround effects and background influences in diverse viewing scenarios such as dim or bright environments. These models improve predictions of color appearance across illuminants, with CIECAM02's embedded CAT02 transform enabling corresponding color calculations for real-world adaptations.[34] In digital media, standards like ITU-R Recommendation BT.2020 (Rec. 2020), established in 2012, leverage extended chromaticity gamuts based on xy coordinates to support ultra-high-definition displays and high dynamic range content, encompassing wider spectral loci including DCI-P3 primaries for enhanced color vividness in HDR video. This space defines primaries with larger chromaticity coverage—such as red at (0.708, 0.292)—to approximate more visible colors, facilitating backward compatibility with narrower gamuts like sRGB while pushing perceptual limits in consumer electronics. To mitigate non-uniformities in earlier xy-based systems, contemporary models like CIECAM16 introduce polar forms such as JCh, where J denotes lightness, C chroma, and h hue, providing a more perceptually uniform chromaticity representation that refines CIECAM02's predictions for color management in wide-gamut workflows. These developments prioritize hue constancy and adaptation.[35]

References

  1. 17-23-052 | CIE
  2. Chromaticity – coordinates, CIE XYZ color space, luminance
  3. [PDF] The CIE XYZ and xyY Color Spaces
  4. CIE Color System - HyperPhysics Concepts
  5. 17-23-053 | CIE
  6. 17-23-054 | CIE
  7. Chromaticity Coordinate - an overview | ScienceDirect Topics
  8. [PDF] Chapter 10. Color
  9. https://www.crystalfontz.com/blog/glossary/chromaticity/
  10. On the trichromatic and opponent-process theories: an article by E ...
  11. Color opponency: tutorial - PMC - NIH
  12. Color Perception - HyperPhysics
  13. [PDF] Color measurement – the CIE color space - Datacolor
  14. Chromaticity Space Uniformity and Gamut: Analysis and Visualization
  15. Metamerism - SPIE Digital Library
  16. Metamerism - an overview | ScienceDirect Topics
  17. The Trichromatic Theory of Color Vision - Simply Psychology
  18. The evolution of concepts of color vision - PMC - PubMed Central
  19. Understanding the Trichromatic Theory of Color Vision - Verywell Mind
  20. https://books.google.com/books?id=00zPAAAAMAAJ
  21. Some Color History - HyperPhysics Concepts
  22. [PDF] Maxwell's creation of colour science at Aberdeen
  23. None
  24. CIE 10 degree photopic photometric observer
  25. None
  26. [PDF] Gernot Hoffmann CIE Color Space - LaBRI
  27. A Standard Default Color Space for the Internet - sRGB - W3C
  28. [PDF] A Adobe RGB Color Space Specification
  29. Understanding the Color Gamut of an LCD Monitor - Eizo
  30. Beyond CMYK in Color Printing | X-Rite Blog
  31. Undercolor Removal (UCR) - Kodak Workflow Documentation
  32. Colour gamut mapping between small and large colour gamuts
  33. Colorimetry — Part 4: CIE 1976 L*a*b* colour space
  34. CIE 1976 L*u*v* Colour Space and u', v', Uniform Chromaticity Scale ...
  35. A colour appearance model for colour management systems
  36. The CIE 2016 Colour Appearance Model for Colour Management ...
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