Color Management is a tool critical to the future success of your business. As such, there exists a great deal of interest, confusion and misunderstanding in the concept. What exactly is Color Management? In the simplest terms, it is the measurement and control of each and every step in your reproduction process. The goal is to know exactly what your output is going to look like, before you commit precious resources to print. Rather than a cost, it is an investment that will save you time and money.

So far so good, it’s the implementation of color management that becomes difficult. The process begins with the proper calibration and profiling of each input and output step in your reproduction chain. Calibration is a process that brings a device to known operational state. In and of itself, calibration does not improve your process; it simply brings us to a known, repeatable starting point. Profiling is the process where we determine the operational limits of a device. This operational limit is called a gamut. In the case of an input device, such as a digital camera or a scanner, we are determining how the device interprets a known range of colors. In the case of output, we are learning how known colors are actually reproduced. These profiles become maps that can be used by color management software to manipulate digital data.

The capability of these devices results in what is commonly called device dependent data. In a way this is somewhat of a misnomer because they are not just device dependent, but also media and condition dependent. A printer profile, for example, is only valid for a given substrate using a single ink set, in the environmental conditions that existed at the time. A change of ink cartridges, or an increase in humidity can invalidate your profile. Similarly, a change in ambient viewing conditions will alter your monitor profile.

The color models commonly, but not always used for this device dependent data are RGB for input and monitor output, and CMYK for physical output. A typical color management program will handle data in a device independent color space, such as L*a*b*, translating to and from color dependent data as needed. Doing so frees the data from the gamut limitations any particular device may impose.

The way we reach our goal is to simulate our output device with our proofing device, matching them within the limits of the different color models. This is accomplished by fitting the data into a gamut that accounts for the limitations imposed by each of our devices, (see illustration). In this extremely simple workflow that consists of nothing more than a monitor for proofing, and a printer for final output we have two gamuts to contend with. By constraining our data to the colors that fall within the overlap area of the two, both devices are able to reproduce the same image.

The very simple example shown here is designed to illustrate the concept. There are literally hundreds of different possible workflows and dozens of software packages available. The choice for any particular situation is not to be taken lightly.