CIE 1931 xy chromaticity diagram showing the gamut of the sRGB color space and location of the primaries. The D65 white point is shown in the center. The Planckian locus is shown with color temperatures labeled in kelvin. The outer curved boundary is the spectral (or monochromatic) locus, with wavelengths shown in nanometers (labeled in blue). Note that the colors in this displayed file are being specified using sRGB. Areas outside the triangle cannot be accurately colored because they are out of the gamut of sRGB therefore they have been interpreted. Also note how the D65 label is not an ideal 6500-kelvin blackbody because it is based on atmospheric filtered daylight.

Plot of the sRGB intensities versus sRGB numerical values (red), and this function's slope in log-log space (blue) which is the effective gamma at each point. Below a compressed value of 0.04045 or a linear intensity of 0.00313, the curve is linear so the gamma is 1. Behind the red curve is a dashed black curve showing an exact gamma = 2.2 power law.

sRGB is a standard RGB color space created cooperatively by HP and Microsoft in 1996 for use on monitors, printers, and the Internet.

sRGB uses the ITU-R BT.709 primaries, the same as are used in studio monitors and HDTV,^[1] and a transfer function (gamma curve) typical of CRTs. This specification allowed sRGB to be directly displayed on typical CRT monitors of the time, a factor which greatly aided its acceptance.

Unlike most other RGB color spaces, the sRGB gamma cannot be expressed as a single numerical value. The overall gamma is approximately 2.2, consisting of a linear (gamma 1.0) section near black, and a non-linear section elsewhere involving a 2.4 exponent and a gamma (slope of log output versus log input) changing from 1.0 through about 2.3.

Background[link]

The sRGB color space has been endorsed by the W3C, Exif, Intel, Pantone, Corel, and many other industry players; it is used in proprietary and open graphics file formats, such as SVG.

The sRGB color space is well specified and is designed to match typical home and office viewing conditions, rather than the darker environment typically used for commercial color matching.

Nearly all software is now designed with the assumption that an 8-bit-per-channel image file placed unchanged onto an 8-bit-per-channel display will appear much as the sRGB specification dictates. LCDs, digital cameras, printers, and scanners all follow the sRGB standard. Devices which do not naturally follow sRGB (as was the case for older CRT monitors) include compensating circuitry or software so that, in the end, they also obey this standard. For this reason, one can generally assume, in the absence of embedded profiles or any other information, that any 8-bit-per-channel image file or any 8-bit-per-channel image API or device interface can be treated as being in the sRGB color space. When an RGB color space with a larger gamut is needed, color management usually must be employed to map image data to appear correctly on the display.

The sRGB gamut[link]

sRGB defines the chromaticities of the red, green, and blue primaries, the colors where one of the three channels is nonzero and the other two are zero. The gamut of chromaticities that can be represented in sRGB is the color triangle defined by these primaries. As with any RGB color space, for non-negative values of R, G, and B it is not possible to represent colors outside this triangle, which is well inside the range of colors visible to a human.

On an sRGB display, each solid bar should look as bright as the surrounding striped dither. (Note: must be viewed at original, 100% size)

sRGB also defines a nonlinear transformation between the intensity of these primaries and the actual number stored. The curve is similar to the gamma response of a CRT display. It is more important to replicate this curve than the primaries to get correct display of an sRGB image. This nonlinear conversion means that sRGB is a reasonably efficient use of the values in an integer-based image file to display human-discernible light levels.

sRGB is sometimes avoided by high-end print publishing professionals because its color gamut is not big enough, especially in the blue-green colors, to include all the colors that can be reproduced in CMYK printing.

Specification of the transformation[link]

The forward transformation (CIE xyY or CIE XYZ to sRGB)[link]

The first step in the calculation of sRGB tristimulus values from the CIE XYZ tristimulus values is a linear transformation, which may be carried out by a matrix multiplication. The numerical values below match those in the official sRGB specification (IEC 61966-2-1:1999) and differ slightly from those in a publication by sRGB's creators.^[2] Note that these linear values are not the final result.

Failed to parse (Missing texvc executable; please see math/README to configure.): \begin{bmatrix} R_\mathrm{linear}\\G_\mathrm{linear}\\B_\mathrm{linear}\end{bmatrix}= \begin{bmatrix} 3.2406&-1.5372&-0.4986\\ -0.9689&1.8758&0.0415\\ 0.0557&-0.2040&1.0570 \end{bmatrix} \begin{bmatrix} X \\ Y \\ Z \end{bmatrix}

Note also, that if the CIE xyY color space values are given (where x, y are the chromaticity coordinates and Y is the luminance), they must first be transformed to CIE XYZ tristimulus values by:

Failed to parse (Missing texvc executable; please see math/README to configure.): X = Y x / y,\,

Failed to parse (Missing texvc executable; please see math/README to configure.): Z = Y (1- x - y)/y\,

The intermediate parameters Failed to parse (Missing texvc executable; please see math/README to configure.): R_\mathrm{linear} , Failed to parse (Missing texvc executable; please see math/README to configure.): G_\mathrm{linear}

and Failed to parse (Missing texvc executable; please see math/README to configure.): B_\mathrm{linear}
for in-gamut colors are defined to be in the range [0,1], which means that the initial X, Y, and Z values need to be similarly scaled (if you start with XYZ values going to 100 or so, divide them by 100 first, or apply the matrix and then scale by a constant factor to the [0,1] range).  The linear RGB values are usually clipped to that range, with display white represented as (1,1,1); the corresponding original XYZ values are such that white is D65 with unit luminance (X,Y,Z = 0.9505, 1.0000, 1.0890). Calculations assume the 2° standard colorimetric observer.[2]

sRGB was designed to reflect a typical real-world monitor with a gamma of 2.2, and the following formula transforms the linear values into sRGB. Let Failed to parse (Missing texvc executable; please see math/README to configure.): C_\mathrm{linear}

be Failed to parse (Missing texvc executable; please see math/README to configure.): R_\mathrm{linear}

, Failed to parse (Missing texvc executable; please see math/README to configure.): G_\mathrm{linear} , or Failed to parse (Missing texvc executable; please see math/README to configure.): B_\mathrm{linear} , and Failed to parse (Missing texvc executable; please see math/README to configure.): C_\mathrm{srgb}

be Failed to parse (Missing texvc executable; please see math/README to configure.): R_\mathrm{srgb}

,Failed to parse (Missing texvc executable; please see math/README to configure.): G_\mathrm{srgb}

or Failed to parse (Missing texvc executable; please see math/README to configure.): B_\mathrm{srgb}

Failed to parse (Missing texvc executable; please see math/README to configure.): C_\mathrm{srgb}=\begin{cases} 12.92C_\mathrm{linear}, & C_\mathrm{linear} \le 0.0031308\\ (1+a)C_\mathrm{linear}^{1/2.4}-a, & C_\mathrm{linear} > 0.0031308 \end{cases}

• where Failed to parse (Missing texvc executable; please see math/README to configure.): a = 0.055

These gamma-corrected values are in the range 0 to 1. If values in the range 0 to 255 are required, e.g. for video display or 8-bit graphics, the usual technique is to multiply by 255 and round to an integer.

The reverse transformation[link]

Again the sRGB component values Failed to parse (Missing texvc executable; please see math/README to configure.): R_\mathrm{srgb} , Failed to parse (Missing texvc executable; please see math/README to configure.): G_\mathrm{srgb} , Failed to parse (Missing texvc executable; please see math/README to configure.): B_\mathrm{srgb}

are in the range 0 to 1. (A range of 0 to 255 can simply be divided by 255).

Failed to parse (Missing texvc executable; please see math/README to configure.): C_\mathrm{linear}= \begin{cases}\frac{C_\mathrm{srgb}}{12.92}, & C_\mathrm{srgb}\le0.04045\\ \left(\frac{C_\mathrm{srgb}+a}{1+a}\right)^{2.4}, & C_\mathrm{srgb}>0.04045 \end{cases}

(where Failed to parse (Missing texvc executable; please see math/README to configure.): C

is Failed to parse (Missing texvc executable; please see math/README to configure.): R

, Failed to parse (Missing texvc executable; please see math/README to configure.): G , or Failed to parse (Missing texvc executable; please see math/README to configure.): B ). Followed by a matrix multiplication of the linear values to get XYZ:

Failed to parse (Missing texvc executable; please see math/README to configure.): \begin{bmatrix} X\\Y\\Z\end{bmatrix}= \begin{bmatrix} 0.4124&0.3576&0.1805\\ 0.2126&0.7152&0.0722\\ 0.0193&0.1192&0.9505 \end{bmatrix} \begin{bmatrix} R_\mathrm{linear}\\ G_\mathrm{linear}\\ B_\mathrm{linear}\end{bmatrix}

Theory of the transformation[link]

It is often casually stated that the decoding gamma for sRGB data is 2.2, yet the above transform shows an exponent of 2.4. This is because the net effect of the piecewise decomposition is necessarily a changing instantaneous gamma at each point in the range: it goes from gamma=1 at zero to a gamma of 2.4 at maximum intensity with a median value being close to 2.2. The transformation was designed to approximate a gamma of about 2.2, but with a linear portion near zero to avoid having an infinite slope at K = 0, which can cause numerical problems. The continuity condition for the curve Failed to parse (Missing texvc executable; please see math/README to configure.): C_\mathrm{linear}

which is defined above as a piecewise function of Failed to parse (Missing texvc executable; please see math/README to configure.): C_\mathrm{srgb}

, is

Failed to parse (Missing texvc executable; please see math/README to configure.): \left(\frac{K_0+a}{1+a}\right)^\gamma=\frac{K_0}{\phi}.

Solving with Failed to parse (Missing texvc executable; please see math/README to configure.): \gamma = 2.4

and the standard value Failed to parse (Missing texvc executable; please see math/README to configure.): \phi=12.92
yields two solutions, Failed to parse (Missing texvc executable; please see math/README to configure.): K_0
≈ Failed to parse (Missing texvc executable; please see math/README to configure.): 0.0381548
or Failed to parse (Missing texvc executable; please see math/README to configure.): K_0
≈ Failed to parse (Missing texvc executable; please see math/README to configure.): 0.0404482

. The IEC 61966-2-1 standard uses the rounded value Failed to parse (Missing texvc executable; please see math/README to configure.): K_0=0.04045 . However, if we impose the condition that the slopes match as well then we must have

Failed to parse (Missing texvc executable; please see math/README to configure.): \gamma\left(\frac{K_0+a}{1+a}\right)^{\gamma-1}\left(\frac{1}{1+a}\right)=\frac{1}{\phi}.

We now have two equations. If we take the two unknowns to be Failed to parse (Missing texvc executable; please see math/README to configure.): K_0

and Failed to parse (Missing texvc executable; please see math/README to configure.): \phi
then we can solve to give

Failed to parse (Missing texvc executable; please see math/README to configure.): K_0=\frac{a}{\gamma-1},\ \ \ \phi=\frac{(1+a)^\gamma(\gamma-1)^{\gamma-1}}{(a^{\gamma-1})(\gamma^\gamma)}.

Substituting Failed to parse (Missing texvc executable; please see math/README to configure.): a=0.055

and Failed to parse (Missing texvc executable; please see math/README to configure.): \gamma=2.4
gives Failed to parse (Missing texvc executable; please see math/README to configure.): K_0
≈ Failed to parse (Missing texvc executable; please see math/README to configure.): 0.0392857
and Failed to parse (Missing texvc executable; please see math/README to configure.): \phi
≈ Failed to parse (Missing texvc executable; please see math/README to configure.): 12.9232102

, with the corresponding linear-domain threshold at Failed to parse (Missing texvc executable; please see math/README to configure.): K_0 / \phi

≈ Failed to parse (Missing texvc executable; please see math/README to configure.): 0.00303993

. These values, rounded to Failed to parse (Missing texvc executable; please see math/README to configure.): K_0=0.03928 , Failed to parse (Missing texvc executable; please see math/README to configure.): \phi=12.92321 , and Failed to parse (Missing texvc executable; please see math/README to configure.): K_0/\phi=0.00304 , are sometimes used to describe sRGB conversion.^[3] Publications by sRGB's creators^[2] rounded to Failed to parse (Missing texvc executable; please see math/README to configure.): K_0=0.03928

and Failed to parse (Missing texvc executable; please see math/README to configure.): \phi=12.92

, resulting in a small discontinuity in the curve. Some authors adopted these values in spite of the discontinuity.^[4] For the standard, the rounded value Failed to parse (Missing texvc executable; please see math/README to configure.): \phi=12.92

was kept and the Failed to parse (Missing texvc executable; please see math/README to configure.): K_0
value was recomputed to make the resulting curve continuous, as described above, resulting in a slope discontinuity from 12.92 below the intersection to 12.70 above.

Viewing environment[link]

The sRGB specification assumes a dimly lit encoding (creation) environment with an ambient correlated color temperature (CCT) of 5000 K. It is interesting to note that this differs from the CCT of the illuminant (D65). Using D50 for both would have made the white point of most photographic paper appear excessively blue.^[5] The other parameters, such as the luminance level, are representative of a typical CRT monitor.

For optimal results, the ICC recommends using the encoding viewing environment (i.e., dim, diffuse lighting) rather than the less-stringent typical viewing environment.^[2]

Usage[link]

This section needs additional citations for verification. Please help improve this article by adding citations to reliable sources. Unsourced material may be challenged and removed. (July 2010)

As the recommended color space for the Internet, sRGB should be used for editing and saving all images intended for publication to the World Wide Web.

Due to the standardization of sRGB on the Internet, on computers, and on printers, many low- to medium-end consumer digital cameras and scanners use sRGB as the default (or only available) working color space. As the sRGB gamut meets or exceeds the gamut of an inkjet printer, an sRGB image is often regarded as satisfactory for home use. However, consumer-level CCDs are typically uncalibrated, meaning that even though the image is being labeled as sRGB, one can't conclude that the image is color-accurate sRGB.

If the color space of an image is unknown and it is an 8- to 16-bit image format, assuming it is in the sRGB color space is a safe choice. This allows a program to identify a color space for all images, which may be much easier and more reliable than trying to track the "unknown" color space. An ICC profile may be used; the ICC distributes three such profiles:^[6] a profile conforming to version 4 of the ICC specification, which they recommend, and two profiles conforming to version 2, which is still commonly used.

Images intended for professional printing via a fully color-managed workflow, e.g. prepress output, sometimes use another color space such as Adobe RGB (1998), which allows for a wider gamut. If such images are to be used on the Internet they may be converted to sRGB using color management tools that are usually included with software that works in these other color spaces.

The two dominant programming interfaces for 3D graphics, OpenGL and Direct3D, have both incorporated support for the sRGB gamma curve. OpenGL supports the textures with sRGB-encoded color components (first introduced with EXT_texture_sRGB extension, added to the core in OpenGL 2.1) and rendering into sRGB-encoded framebuffers (first introduced with EXT_framebuffer_sRGB extension, added to the core in OpenGL 3.0). Direct3D supports sRGB textures and rendering into sRGB surfaces starting with DirectX 9. Correct mipmaping and interpolation of sRGB textures has direct hardware support in texturing units of most modern GPUs (for example nVidia GeForce 8 performs conversion from 8-bit texture to linear values before interpolating those values), and do not have any performance penalty.^[7]

See also[link]

• RGB color space
• scRGB

References[link]

1. ^ Charles A. Poynton (2003). Digital Video and HDTV: Algorithms and Interfaces. Morgan Kaufmann. ISBN 1-55860-792-7. http://books.google.com/books?id=ra1lcAwgvq4C&pg=RA1-PA239&dq=rec+709+smpte. 
2. ^ ^{a b c d} Michael Stokes, Matthew Anderson, Srinivasan Chandrasekar, Ricardo Motta (November 5, 1996). "A Standard Default Color Space for the Internet – sRGB, Version 1.10". http://www.w3.org/Graphics/Color/sRGB. 
3. ^ Phil Green and Lindsay W. MacDonald (2002). Colour Engineering: Achieving Device Independent Colour. John Wiley and Sons. ISBN 0-471-48688-4. http://books.google.com/books?id=tn09voxr6agC&pg=PA350&dq=srgb+0.03928+date:0-2002. 
4. ^ Jon Y. Hardeberg (2001). Acquisition and Reproduction of Color Images: Colorimetric and Multispectral Approaches. Universal-Publishers.com. ISBN 1-58112-135-0. http://books.google.com/books?id=e2umTIdI2u4C&pg=PA40&dq=srgb+0.00304+date:0-2002. 
5. ^ Rodney, Andrew (2005). Color Management for Photographers. Focal Press. p. 121. ISBN 978-0-240-80649-5. http://books.google.com/books?id=jFl-3v9sSEUC&pg=PA121&lpg=PA121&dq=%22My+suggestion+is+to+calibrate+to+a+D65+white+point.%22. "Why Calibrate Monitor to D65 When Light Booth is D50" 
6. ^ sRGB profiles, ICC
7. ^ GPU Gems 3, section 24.4.1, http://http.developer.nvidia.com/GPUGems3/gpugems3_ch24.html

Standards[link]

• IEC 61966-2-1:1999 is the official specification of sRGB. It provides viewing environment, encoding, and colorimetric details.
• Amendment A1:2003 to IEC 61966-2-1:1999 describes an analogous sYCC encoding for YCbCr color spaces, an extended-gamut RGB encoding, and a CIELAB transformation.
• The fourth working draft of IEC 61966-2-1 is available online, but is not the complete standard. It can be downloaded from www.colour.org or www2.units.it.

External links[link]

• International Color Consortium
• Archive copy of http://www.srgb.com, now unavailable, containing much information on the design, principles and use of sRGB
• A Standard Default Color Space for the Internet – sRGB at w3.org
• OpenGL extension for sRGB textures at sgi.com
• Conversion matrices for RGB vs. XYZ conversion

This article needs additional citations for verification. Please help improve this article by adding citations to reliable sources. Unsourced material may be challenged and removed. (September 2007)

A comparison of the chromaticities enclosed by some color spaces.

A color model is an abstract mathematical model describing the way colors can be represented as tuples of numbers, typically as three or four values or color components (e.g. RGB and CMYK are color models). However, a color model with no associated mapping function to an absolute color space is a more or less arbitrary color system with no connection to any globally understood system of color interpretation.

Adding a certain mapping function between the color model and a certain reference color space results in a definite "footprint" within the reference color space. This "footprint" is known as a gamut, and, in combination with the color model, defines a new color space. For example, Adobe RGB and sRGB are two different absolute color spaces, both based on the RGB model.

In the most generic sense of the definition above, color spaces can be defined without the use of a color model. These spaces, such as Pantone, are in effect a given set of names or numbers which are defined by the existence of a corresponding set of physical color swatches. This article focuses on the mathematical model concept.

Understanding the concept[link]

A comparison of RGB and CMYK color models. This image demonstrates the difference between how colors will look on a computer monitor (RGB) compared to how they will reproduce in a CMYK print process.

A wide range of colors can be created by the primary colors of pigment (cyan (C), magenta (M), yellow (Y), and black (K)). Those colors then define a specific color space. To create a three-dimensional representation of a color space, we can assign the amount of magenta color to the representation's X axis, the amount of cyan to its Y axis, and the amount of yellow to its Z axis. The resulting 3-D space provides a unique position for every possible color that can be created by combining those three pigments.

However, this is not the only possible color space. For instance, when colors are displayed on a computer monitor, they are usually defined in the RGB (red, green and blue) color space. This is another way of making nearly the same colors (limited by the reproduction medium, such as the phosphor (CRT) or filters and backlight (LCD)), and red, green and blue can be considered as the X, Y and Z axes. Another way of making the same colors is to use their Hue (X axis), their Saturation (Y axis), and their brightness Value (Z axis). This is called the HSV color space. Many color spaces can be represented as three-dimensional (X,Y,Z) values in this manner, but some have more, or fewer dimensions, and some, such as Pantone, cannot be represented in this way at all.

Notes[link]

When formally defining a color space, the usual reference standard is the CIELAB or CIEXYZ color spaces, which were specifically designed to encompass all colors the average human can see.

Since "color space" is a more specific term for a certain combination of a color model plus a mapping function, the term "color space" tends to be used to also identify color models, since identifying a color space automatically identifies the associated color model. Informally, the two terms are often used interchangeably, though this is strictly incorrect. For example, although several specific color spaces are based on the RGB model, there is no such thing as the RGB color space.

Since any color space defines colors as a function of the absolute reference frame, color spaces, along with device profiling, allow reproducible representations of color, in both analogue and digital representations.

Conversion[link]

Color space conversion is the translation of the representation of a color from one basis to another. This typically occurs in the context of converting an image that is represented in one color space to another color space, the goal being to make the translated image look as similar as possible to the original.

Density[link]

The RGB color model is implemented in different ways, depending on the capabilities of the system used. By far the most common general-used incarnation as of 2006^[update] is the 24-bit implementation, with 8 bits, or 256 discrete levels of color per channel. Any color space based on such a 24-bit RGB model is thus limited to a range of 256×256×256 ≈ 16.7 million colors. Some implementations use 16 bits per component for 48 bits total, resulting in the same gamut with a larger number of distinct colors. This is especially important when working with wide-gamut color spaces (where most of the more common colors are located relatively close together), or when a large number of digital filtering algorithms are used consecutively. The same principle applies for any color space based on the same color model, but implemented in different bit depths.

Partial list of color spaces[link]

CIE 1931 XYZ color space was one of the first attempts to produce a color space based on measurements of human color perception (earlier efforts were by James Clerk Maxwell, König & Dieterici, and Abney at Imperial College)^[1] and it is the basis for almost all other color spaces. Derivatives of the CIE XYZ space include CIELUV, CIEUVW, and CIELAB.

Generic color models[link]

Additive color mixing: Three overlapping lightbulbs in a vacuum, adding together to create white.

Subtractive color mixing: Three splotches of paint on white paper, subtracting together to turn the paper black.

RGB uses additive color mixing, because it describes what kind of light needs to be emitted to produce a given color. Light is added together to create form from out of the darkness. RGB stores individual values for red, green and blue. RGBA is RGB with an additional channel, alpha, to indicate transparency.

Common color spaces based on the RGB model include sRGB, Adobe RGB and ProPhoto RGB.

CMYK uses subtractive color mixing used in the printing process, because it describes what kind of inks need to be applied so the light reflected from the substrate and through the inks produces a given color. One starts with a white substrate (canvas, page, etc.), and uses ink to subtract color from white to create an image. CMYK stores ink values for cyan, magenta, yellow and black. There are many CMYK color spaces for different sets of inks, substrates, and press characteristics (which change the dot gain or transfer function for each ink and thus change the appearance).

YIQ was formerly used in NTSC (North America, Japan and elsewhere) television broadcasts for historical reasons. This system stores a luminance value with two chrominance values, corresponding approximately to the amounts of blue and red in the color. It is similar to the YUV scheme used in most video capture systems^[2] and in PAL (Australia, Europe, except France, which uses SECAM) television, except that the YIQ color space is rotated 33° with respect to the YUV color space. The YDbDr scheme used by SECAM television is rotated in another way.

YPbPr is a scaled version of YUV. It is most commonly seen in its digital form, YCbCr, used widely in video and image compression schemes such as MPEG and JPEG.

xvYCC is a new international digital video color space standard published by the IEC (IEC 61966-2-4). It is based on the ITU BT.601 and BT.709 standards but extends the gamut beyond the R/G/B primaries specified in those standards.

HSV (hue, saturation, value), also known as HSB (hue, saturation, brightness) is often used by artists because it is often more natural to think about a color in terms of hue and saturation than in terms of additive or subtractive color components. HSV is a transformation of an RGB colorspace, and its components and colorimetry are relative to the RGB colorspace from which it was derived.

HSL (hue, saturation, lightness/luminance), also known as HLS or HSI (hue, saturation, intensity) is quite similar to HSV, with "lightness" replacing "brightness". The difference is that the brightness of a pure color is equal to the brightness of white, while the lightness of a pure color is equal to the lightness of a medium gray.

Commercial color spaces[link]

• Munsell color system
• Natural Color System (NCS)

Special-purpose color spaces[link]

• The RG Chromaticity space is used in Computer vision applications. It shows the color of light (red, yellow, green etc.), but not its intensity (dark, bright).

Obsolete color spaces[link]

Early color spaces had two components. They largely ignored blue light because the added complexity of a 3-component process provided only a marginal increase in fidelity when compared to the jump from monochrome to 2-component color.

• RG for early Technicolor film
• RGK for early color printing

See also[link]

Wikimedia Commons has media related to: Color spaces

• Color theory
• List of colors

References[link]

1. ^ William David Wright, 50 years of the 1931 CIE Standard Observer. Die Farbe, 29:4/6 (1981).
2. ^ Dean Anderson. "Color Spaces in Frame Grabbers: RGB vs. YUV". http://www.sensoray.com/support/frame_grabber_capture_modes.htm. Retrieved 2008-04-08. 

External links[link]

• Color FAQ, Charles Poynton
• FAQ about color physics, Stephen Westland
• Color Science, Dan Bruton
• Color Spaces, Rolf G. Kuehni (October 2003)
• Colour spaces - perceptual, historical and applicational background, Marko Tkalčič (2003)
• Color formats for image and video processing - Color conversion between RGB, YUV, YCbCr and YPbPr.
• C library of SSE-optimised color format conversions.
• Konica Minolta Sensing: Precise Color Communication