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The MelissaRGB profile deserves some explanation. Melissa RGB is not an 'official' color space, but is the combination of the ProPhoto color space, with an sRGB gamma curve. It's important because Melissa RGB is what Lightroom uses for its readouts. Specifically, the RGB values you get as Lightroom readouts are in. Choosing a Working RGB color space A Photoshop RGB working space should encompass the full gamut of BOTH the source device (e.g. A camera or scanner) AND the destination device (e.g. A press), otherwise some of the colors achievable on one or both devices may be clipped or distorted. A common misconception is that converting a raw image from a wide-gamut scanner or digital camera profile into. The ICC Profile for Adobe 1998 RGB, used in this example, can be found here on Adobe’s site (Windows, Mac and Linux versions). Download your appropriate file and copy the file named AdobeRGB1998.icc to a handy location on your system. For this example, I created a folder on my desktop called icc to use as an example.

In color management, an ICC profile is a set of data that characterizes a color input or output device, or a color space, according to standards promulgated by the International Color Consortium (ICC). Profiles describe the color attributes of a particular device or viewing requirement by defining a mapping between the device source or target color space and a profile connection space (PCS). This PCS is either CIELAB (L*a*b*) or CIEXYZ. Mappings may be specified using tables, to which interpolation is applied, or through a series of parameters for transformations.

Every device that captures or displays color can be profiled. Some manufacturers provide profiles for their products, and there are several products that allow an end-user to generate their own color profiles, typically through the use of a tristimulus colorimeter or a spectrophotometer (sometimes called a spectrocolorimeter).^[1]

The ICC defines the format precisely but does not define algorithms or processing details. This means there is room for variation between different applications and systems that work with ICC profiles. Two main generations are used: the legacy ICCv2 and the December 2001 ICCv4. Since late 2010, the current version of the format specification (ICC.1) is 4.3.^[2]

ICC has also published a preliminary specification for iccMAX (ICC.2) or ICCv5, a next-generation color management architecture with significantly expanded functionality and a choice of colorimetric, spectral or material connection space.^[3]

Details

Color gamut is a popular concept in digital color management, and is frequently mentioned in discussions about the selection of a color space (e.g., sRGB or ProPhoto RGB) or the compression of colors in a color-managed workflow. Color gamut volume and color gamut boundary colors are the two aspects of a color gamut that get the most attention, and both provide useful information.

Unfortunately, the concept of a color gamut has been applied to color imaging devices that do not actually have a color gamut. Only devices, or systems, that render color have a color gamut. To quote Dr. Roy S. Berns from RIT in the book Billmeyer and Saltzman’s Principles of Color Technology, 'Color gamut: Range of colors produced by a coloration system.' To be a little clearer about this, the concept of a color gamut applies to systems that produce color (e.g., color printer, color television, color monitor, or color projector).

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The concept of a color gamut is not relevant to systems, or devices, that measure color. In the context of digital color imaging, a color measurement device is exposed to colored light and delivers a set of digital values to represent that colored light. The obvious examples are colorimeters and spectrophotometers, which are used in scientific color measurement work. Digital color cameras and scanners are also color measurement devices. These devices do not render or produce color, they measure color. Therefore, none of them have a color gamut.

We can characterize a color measurement device, with some constraints on the exposure conditions, and use that characterization in an ICC profile for that device (e.g., an ICC profile for a digital color camera or a color film scanner). But that characterization is not the same as a color gamut. The characterization may look a lot like a color gamut in a software tool that displays color gamuts and device characterizations, and that may be the reason why people think the concept of a color gamut is relevant for digital color cameras.

Another contributing factor to the confusion is the option on a digital color camera to choose an RGB color space (e.g., sRGB, Adobe RGB (1998), or ProPhoto RGB) for the encoding of a photograph within the digital color camera. These RGB color spaces are convenient color spaces that simplify color management of a digital photograph downstream from the digital camera. Encoding a digital photograph in one of these RGB color spaces will constrain the digital photograph to the gamut of the color space (Yes, each of these RGB color spaces has a color gamut that is constrained by the colorimetric values of the red, green, and blue primaries of the color space). It will also tie the digital photograph to the white point of the color space and establish the digital resolution within the color space (e.g., 8-bits per channel or 16-bits per channel). But the selected RGB color space is not the color gamut of the digital camera. If this distinction is not obvious after you have read the entire blog post, please leave a comment and I will go into more detail.

If we cannot apply the concept of a color gamut to a color measurement device, then how do we describe the capabilities and limitations of the color measurement device? The proper way to describe the capabilities and limitations of a color measurement device is to provide the color-matching functions of the device. The color-matching functions quantitatively describe the spectral sensitivities of the separate color sensors (e.g., red, green, and blue filters over separate light detectors). This becomes a little more obvious when you think about the color-matching functions for human vision. Human vision is a color measurement system, and we use the color-matching functions of the CIE 1931 standard colorimetric observer, or the CIE 1964 supplementary standard colorimetric observer, to quantify measured colors.

I recognize that it is easier to understand color management when we can see the color gamut of each device displayed in the same color space. Unfortunately, we cannot display the color gamut of a digital color camera in CIELAB space, or the CIE xy chromaticity space, for comparison with the color gamut of a color monitor or a color printer because the digital color camera does not have a color gamut. Furthermore, a diagram of the color-matching functions of a digital color camera lends very little insight when compared to a 2-D or 3-D rendering of the color gamut of a color monitor or a color printer. So I am sympathetic with the desire to give a digital color camera a color gamut in order to facilitate a comparison to color rendering devices. The good news is that we have a simple solution: device characterization with a common colorimetric color space (e.g., CIELAB).

In the practical application of a color management system, the characterization of a color-imaging device is the information that enables color management. This is true for any color rendering device and any color measurement device in the digital color workflow. The data within an ICC profile are based on characterization data, not the limits of a color gamut or the color-matching functions. The information taken from an ICC profile and rendered by software tools to visualize the color volume and boundaries of the color-imaging device is based on the characterization data. We should keep this in mind when someone incorrectly talks about the color gamut for a digital camera. We know that a digital color camera does not have a color gamut, but we can talk about the characterization of a digital camera, or the selection of a standard RGB color space within the camera, and frame the discussion in that context.

Post written by Parker Plaisted

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References:
R. S. Berns, Billmeyer and Saltzman’s Principles of Color Technology, 3rd Edition, John Wiley & Sons, New York, N.Y. (2000).

International Color Consortium, ICC Profile Format Specification. (http://www.color.org)

Imaging FAQ on the RIT CIS Munsell Color Science Laboratory (MCSL) Website https://www.rit.edu/cos/colorscience/rc_faq_faq3.php#255