Profile building is something we do with the aid of measurement devices such as GretagMacbeth’s Eye-One Pro (or Spectrolino, or one of the dozen other color measurement devices they make and sell), or X-Rite’s Pulse (or again, one of the dozen other spectrophotometers and colorimeters they manufacture).

One of the first steps in profile building involves measuring the colorimetry of a set of colors from some imaging media or display. If the imaging media or viewing environment differ from the reference, it will be necessary to adapt the measured colorimetry to that appropriate for the profile connection space (PCS). 

These adaptations account for such differences as white point chromaticity and luminance relative to an ideal reflector, viewing environment, viewing illuminant, and flare. Currently, it is the responsibility of the profile building software to do this adaptation.

Different vendors use a different number of test color patches. Given the statistical noise on the output signal it appears reasonable to measure some 15 to 20 samples before averaging the result. It is still subject to discussions how many patches are needed to characterise a device accurately.

The practical importance of reaching agreement is still an open question, as many of the color management systems are evidently not aimed at the printing industry market but at the desktop publishing market. In this market, users do not expect to take even 190 measurements themselves, but to be able to acquire pre-built profiles off the shelf. One decisive difficulty here might be the matter of creating affordably priced profiles to characterise the devices.

Another issue is that those profiles will become useless as devices drift from the manufacturer’s original calibration. And presses and inkjet printers drift considerably. Press drift is typically in the range of deltaE 2 to 4, while inkjet printers may drift well into the double figures.

Equipment used for image capture and for image reproduction have different properties. The different color spaces involved are not only of considerably different sizes (how many colors can be displayed) , but also vary in shape (which colors can be displayed). 

Looking versus Measuring

Usually, scanners can represent a wider gamut of colors and a larger dynamic range of colors than output devices such as printers can. Due to these differences in shape, the desired objective of the best possible reproduction is seldom reached by simply making the larger color space smaller.

As everyone with some knowledge of color management will tell you: the mathematical operations involved are not linear. Diminishing the larger of the two spaces until it fits into the smaller space may substantially distort that color space, and therefore the visual representation of the colors themselves.

A choice must be made between two different conceptions of optimum reproduction. The first is called “appearance matching”. This approach tries to take the eye’s ability into account not only to consider the color at a point under view but also the color of the neighbouring environment. Perceptual rendering intent as it is known in Photoshop, for example, is derived from this approach.

There are ways to compress the source color space and still keep the image visually balanced. Success is measured subjectively, by asking if the greys appear grey and “memory colors” (e.g., flesh, grass, sky) look acceptable. The other approach is called “colorimetric matching”.

Here the goal is to reproduce as many color from the input device as exactly as possible. Success is measured with an objective device such as a colorimeter. In a colorimetric match, some colors from the source image will not be reproducible exactly and some compromises will have to be made. Because the relationship between colors within the image has changed, colorimetrically matched images may not “look right” to human viewers.

Both methods have advantages. Appearance matching is helpful to create the same impression in an output that would be created by looking at the original. Colorimetric matching (Relative and Absolute Rendering Intent) yields measurable data that can be communicated reliably. It can enable remote printing by providing a means of verifying that results are accurate.