This article is missing information about numeric property.(February 2021) |
In colorimetry, CIECAM02 is the color appearance model published in 2002 by the International Commission on Illumination (CIE) Technical Committee 8-01 (Color Appearance Modelling for Color Management Systems) and the successor of CIECAM97s. [1]
The two major parts of the model are its chromatic adaptation transform, CIECAT02, and its equations for calculating mathematical correlates for the six technically defined dimensions of color appearance: brightness (luminance), lightness, colorfulness, chroma, saturation, and hue.
Brightness is the subjective appearance of how bright an object appears given its surroundings and how it is illuminated. Lightness is the subjective appearance of how light a color appears to be. Colorfulness is the degree of difference between a color and gray. Chroma is the colorfulness relative to the brightness of another color that appears white under similar viewing conditions. This allows for the fact that a surface of a given chroma displays increasing colorfulness as the level of illumination increases. Saturation is the colorfulness of a color relative to its own brightness. Hue is the degree to which a stimulus can be described as similar to or different from stimuli that are described as red, green, blue, and yellow, the so-called unique hues. The colors that make up an object’s appearance are best described in terms of lightness and chroma when talking about the colors that make up the object’s surface, and in terms of brightness, saturation and colorfulness when talking about the light that is emitted by or reflected off the object.
CIECAM02 takes for its input the tristimulus values of the stimulus, the tristimulus values of an adapting white point, adapting background, and surround luminance information, and whether or not observers are discounting the illuminant (color constancy is in effect). The model can be used to predict these appearance attributes or, with forward and reverse implementations for distinct viewing conditions, to compute corresponding colors.
The Windows Color System introduced in Windows Vista uses Canon's Kyuanos (キュアノス) technology for mapping image gamuts between output devices, which in turn uses CIECAM02 for color matching. [2]
The inner circle is the stimulus, from which the tristimulus values should be measured in CIE XYZ using the 2° standard observer. The intermediate circle is the proximal field, extending out another 2°. The outer circle is the background, reaching out to 10°, from which the relative luminance (Yb) need be measured. If the proximal field is the same color as the background, the background is considered to be adjacent to the stimulus. Beyond the circles which comprise the display field (display area, viewing area) is the surround field (or peripheral area), which can be considered to be the entire room. The totality of the proximal field, background, and surround is called the adapting field (the field of view that supports adaptation—extends to the limit of vision). [3]
When referring to the literature, it is also useful to be aware of the difference between the terms adopted white point (the computational white point) and the adapted white point (the observer white point). [4] The distinction may be important in mixed mode illumination, where psychophysical phenomena come into play. This is a subject of research.
CIECAM02 defines three surround(ing)s – average, dim, and dark – with associated parameters defined here for reference in the rest of this article: [5]
Surround condition | Surround ratio | F | c | Nc | Application |
---|---|---|---|---|---|
Average | SR > 0.15 | 1.0 | 0.69 | 1.0 | Viewing surface colors |
Dim | 0 < SR < 0.15 | 0.9 | 0.59 | 0.9 | Viewing television |
Dark | SR = 0 | 0.8 | 0.525 | 0.8 | Using a projector in a dark room |
For intermediate conditions, these values can be linearly interpolated. [5]
The absolute luminance of the adapting field, which is a quantity that will be needed later, should be measured with a photometer. If one is not available, it can be calculated using a reference white:
where Yb is the relative luminance of background, the Ew = πLW is the illuminance of the reference white in lux, LW is the absolute luminance of the reference white in cd/m2, and Yw is the relative luminance of the reference white in the adapting field. If unknown, the adapting field can be assumed to have average reflectance ("gray world" assumption): LA = LW / 5.
Note: Care should be taken not to confuse LW, the absolute luminance of the reference white in cd/m2, and Lw the red cone response in the LMS color space.
This section may require cleanup to meet Wikipedia's quality standards. The specific problem is: Sharpened LMS should be just called RGB per original definition, Fairchild book, and CAM16 doc. Might need an explanation about how it's a funky LMS instead of an additive light model though.(February 2021) |
Given a set of tristimulus values in XYZ, the corresponding LMS values can be determined by the MCAT02 transformation matrix (calculated using the CIE 1931 2° standard colorimetric observer). [1] The sample color in the test illuminant is:
Once in LMS, the white point can be adapted to the desired degree by choosing the parameter D. [3] For the general CAT02, the corresponding color in the reference illuminant is:
where the Yw / Ywr factor accounts for the two illuminants having the same chromaticity but different reference whites. [6] The subscripts indicate the cone response for white under the test (w) and reference illuminant (wr). The degree of adaptation (discounting) D can be set to zero for no adaptation (stimulus is considered self-luminous) and unity for complete adaptation (color constancy). In practice, it ranges from 0.65 to 1.0, as can be seen from the diagram. Intermediate values can be calculated by: [5]
where surround F is as defined above and LA is the adapting field luminance in cd/m2. [1]
In CIECAM02, the reference illuminant has equal energy Lwr = Mwr = Swr = 100) and the reference white is the perfect reflecting diffuser (i.e., unity reflectance, and Ywr = 100) hence:
Furthermore, if the reference white in both illuminants have the Y tristimulus value (Ywr = Yw) then:
After adaptation, the cone responses are converted to the Hunt–Pointer–Estévez space by going to XYZ and back: [5]
Note that the matrix above, which was inherited from CIECAM97s, [7] has the unfortunate property that since 0.38971 + 0.68898 – 0.07868 = 1.00001, 1⃗ ≠ MH1⃗ and that consequently gray has non-zero chroma, [8] an issue which CAM16 aims to address. [9]
Finally, the response is compressed based on the generalized Michaelis–Menten equation (as depicted aside): [5]
FL is the luminance level adaptation factor.
As previously mentioned, if the luminance level of the background is unknown, it can be estimated from the absolute luminance of the white point as LA = LW / 5 using the "medium gray" assumption. (The expression for FL is given in terms of 5LA for convenience.) In photopic conditions, the luminance level adaptation factor (FL) is proportional to the cube root of the luminance of the adapting field (LA). In scotopic conditions, it is proportional to LA (meaning no luminance level adaptation). The photopic threshold is roughly LW = 1 (see FL–LA graph above).
CIECAM02 defines correlates for yellow-blue, red-green, brightness, and colorfulness. Let us make some preliminary definitions.
The correlate for red–green (a) is the magnitude of the departure of C1 from the criterion for unique yellow (C1 = C2 / 11), and the correlate for yellow–blue (b) is based on the mean of the magnitude of the departures of C1 from unique red (C1 = C2) and unique green (C1 = C3). [3]
The 4.5 factor accounts for the fact that there are fewer cones at shorter wavelengths (the eye is less sensitive to blue). The order of the terms is such that b is positive for yellowish colors (rather than blueish).
The hue angle (h) can be found by converting the rectangular coordinate (a, b) into polar coordinates:
To calculate the eccentricity (et) and hue composition (H), determine which quadrant the hue is in with the aid of the following table. Choose i such that hi ≤ h′ < hi+1, where h′ = h if h > h1 and h′ = h + 360° otherwise.
Red | Yellow | Green | Blue | Red | |
---|---|---|---|---|---|
i | 1 | 2 | 3 | 4 | 5 |
hi | 20.14 | 90.00 | 164.25 | 237.53 | 380.14 |
ei | 0.8 | 0.7 | 1.0 | 1.2 | 0.8 |
Hi | 0.0 | 100.0 | 200.0 | 300.0 | 400.0 |
(This is not exactly the same as the eccentricity factor given in the table.)
Calculate the achromatic response A:
where
The correlate of lightness is
where c is the impact of surround (see above), and
The correlate of brightness is
Then calculate a temporary quantity t.
The correlate of chroma is
The correlate of colorfulness is
The correlate of saturation is
The appearance correlates of CIECAM02, J, a, and b, form a uniform color space that can be used to calculate color differences, as long as a viewing condition is fixed. A more commonly-used derivative is the CAM02 Uniform Color Space (CAM02-UCS), an extension with tweaks to better match experimental data. [10]
Like many color models, CIECAM02 aims to model the human perception of color. The CIECAM02 model has been shown to be a more plausible model of neural activity in the primary visual cortex, compared to the earlier CIELAB model. Specifically, both its achromatic response A and red-green correlate a can be matched to EMEG activity (entrainment), each with their own characteristic delay. [11]
Y′UV, also written YUV, is the color model found in the PAL analogue color TV standard. A color is described as a Y′ component (luma) and two chroma components U and V. The prime symbol (') denotes that the luma is calculated from gamma-corrected RGB input and that it is different from true luminance. Today, the term YUV is commonly used in the computer industry to describe colorspaces that are encoded using YCbCr.
HSL and HSV are the two most common cylindrical-coordinate representations of points in an RGB color model. The two representations rearrange the geometry of RGB in an attempt to be more intuitive and perceptually relevant than the cartesian (cube) representation. Developed in the 1970s for computer graphics applications, HSL and HSV are used today in color pickers, in image editing software, and less commonly in image analysis and computer vision.
The CIELAB color space, also referred to as L*a*b*, is a color space defined by the International Commission on Illumination in 1976. It expresses color as three values: L* for perceptual lightness and a* and b* for the four unique colors of human vision: red, green, blue and yellow. CIELAB was intended as a perceptually uniform space, where a given numerical change corresponds to a similar perceived change in color. While the LAB space is not truly perceptually uniform, it nevertheless is useful in industry for detecting small differences in color.
YCbCr, Y′CbCr, or Y Pb/Cb Pr/Cr, also written as YCBCR or Y′CBCR, is a family of color spaces used as a part of the color image pipeline in video and digital photography systems. Y′ is the luma component and CB and CR are the blue-difference and red-difference chroma components. Y′ is distinguished from Y, which is luminance, meaning that light intensity is nonlinearly encoded based on gamma corrected RGB primaries.
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In 1931 the International Commission on Illumination (CIE) published the CIE 1931 color spaces which define the relationship between the visible spectrum and the visual sensation of specific colors by human color vision. The CIE color spaces are mathematical models that create a "standard observer", which attempts to predict the perception of unique hues of color. These color spaces are essential tools that provide the foundation for measuring color for industry, including inks, dyes, and paints, illumination, color imaging, etc. The CIE color spaces contributed to the development of color television, the creation of instruments for maintaining consistent color in manufacturing processes, and other methods of color management.
LMS, is a color space which represents the response of the three types of cones of the human eye, named for their responsivity (sensitivity) peaks at long, medium, and short wavelengths.
Relative luminance follows the photometric definition of luminance including spectral weighting for human vision, but while luminance is a measure of light in units such as , relative luminance values are normalized as 0.0 to 1.0, with 1.0 being a theoretical perfect reflector of 100% reference white. Like the photometric definition, it is related to the luminous flux density in a particular direction, which is radiant flux density weighted by the luminous efficiency function of the CIE Standard Observer.
A standard illuminant is a theoretical source of visible light with a spectral power distribution that is published. Standard illuminants provide a basis for comparing images or colors recorded under different lighting.
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Lightness is a visual perception of the luminance of an object. It is often judged relative to a similarly lit object. In colorimetry and color appearance models, lightness is a prediction of how an illuminated color will appear to a standard observer. While luminance is a linear measurement of light, lightness is a linear prediction of the human perception of that light.
In colorimetry, the CIE 1976L*, u*, v*color space, commonly known by its abbreviation CIELUV, is a color space adopted by the International Commission on Illumination (CIE) in 1976, as a simple-to-compute transformation of the 1931 CIE XYZ color space, but which attempted perceptual uniformity. It is extensively used for applications such as computer graphics which deal with colored lights. Although additive mixtures of different colored lights will fall on a line in CIELUV's uniform chromaticity diagram, such additive mixtures will not, contrary to popular belief, fall along a line in the CIELUV color space unless the mixtures are constant in lightness.
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The CIECAM97s model was adopted by the CIE in 1997 for color imaging applications. It includes forward and reverse modes. Some problems in using this model were found in recent field trials. This article suggests revision to the model in two respects: (a) to make the lightness (J) zero when the Y tristimulus value is zero, under all surround conditions; (b) to modify the chromatic induction factor (Nc) from 1.10 to 0.95 for the dim surround condition. To avoid confusion, it is suggested that the revised version of the model be designated CAM97s2. The article also describes an alternative mode to achieve a more nearly exact reversibility between the forward and reverse modes.
Chromatic adaptation transforms (CATs) have appeared in different forms. The reasons for these forms, and the relationships between them, are described. The factors governing which type of CAT should be used in different applications are explained
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