Understanding color management

Three important steps in the evolution of digital imaging

2000: Digital cameras started gaining acceptance among professional photographers
2005: RAW file format was accepted as superior by all serious photographers
2010: RAW profiling of digital cameras became easely manageable by all photographers thanks to the Photokina introduction
of QPcard 202 color reference card and QPcard RAW Profiler application

The color managed camera

Color managed digital cameras is now at every photographer's hands thanks to QPcard 202 and QPcard RAW Profiler. You
no longer have to rely on generic camera specific RAW profiles. From now on you are in full control of the profiling process.
Start creating your own standard RAW profile, specific to your camera and useful in any light. This profile will most probably
improve the colors of all your images, including older images taken with the same camera. This profile will become your
every-day-profile, useful in most lighting conditions.
The second step is to take color fidelity one step further by creating a light specific profile. This is the best way to exploit your
cameras full color potential. You will be amazed by the color difference when you compare images converted with your old
generic profile and a QPcard (camera and light specific) profile.
The third step is to explore mastering “impossible” light. Modern energy efficient light sources, like fluorescent or LED, show
great spectral differences when compared to the sun and tungsten light sources. The spectral distribution is intermittent with
spikes and holes, making colorants reflect or transmit visible light in an inconsistent way. Some wavelengths of the colorants
are boosted while others are suppressed. This makes simple white balancing impossible to use with acceptable results. Color
management and profiling, however, can greatly improve pictures taken in the light of these modern sources.
Heated black-body is the common scientific name for light sources like the sun and tungsten light bulbs. What they all have
in common is continuos spectral distribution of visible wavelengths. This makes them quite easy to color balance by means
of white or gray balancing. However, white balancing only takes care of the light, not camera specific on-sensor filter qualities.
Strictly speaking visible color is depending on two components: colorants and light. If there is no light, colorants will remain
invisible. Colorants can be transparent and transmit light – like in the filters of a scanner, on a camera sensor, in a monitor
display or in a video projector. Colorants can also reflect light – like paint on a canvas or ink on a printed paper.
Light can be emitted from a heated black-body like the sun or a tungsten light bulb, resulting in continuos spectral distribution.
Or it can be artificial with an intermittent spectrum like in fluorescent light. No matter what, visible color is always a
combination of colorants and light.

Color management is the discipline of managing colors in digital images

The imaging business (photography and printing) has gone through revolutionary changes over the last 15-20 years. The
analogue image world is left behind us in favor of a digital image environment. The transition, or even paradigm shift, has
taken many years and cost lots of pain. There have been many obstacles to pass and photographers and other imaging professionals
have had to learn completely new ways of handling images. Fortunately the gain is enormous and well worth the
struggle and no one wants to go back to films, chemicals, waiting times and uncertainty.
The two key words for success during the digital transition are spelled “Color Management”. We have to manage colors in a
completely different and sometimes obscure and abstract way. Color management has been and still is very difficult to comprehend
for many photographers and other image disciplines like post processing, separation, printing and web publishing.
We have to manage colors in scanners, in monitors, in printers and in cameras.
Every single unit used in the process of handling color images has a specific characterization. Scan a picture in 10 different
scanners and it will come out different in all of them. Display a picture on 10 different monitors and it will look different
on all of them. Print a picture with 10 different printers and all prints will look different. Take a picture of a specific subject
with 10 different cameras and all pictures will come out differently. So, in order to make these units communicate colors in
an accurate way, they all have to be color managed.
Camera color management, much more complex and accurate than ordinary white balancing, is quite easy to understand
theoretically. The first step in color management is basically a process of checking color accuracy and compensate discrepancies.
Let’s make a comparison with a digital thermometer. You put the sensor in ice water and check the scale. It shows
+3°C. When you dip the sensor in boiling water it shows +96°C. You know that ice water is 0 and boiling water 100°C. You
have now characterized your thermometer. If you like, you can do the same thing with nine other thermometers and get
characterization of all of them.
Now to the next step of temperature management: profiling. But before profiling, let’s calibrate the thermometer. There are
two small calibration knobs on the thermometer display; one for low temperatures and one for high. Put the sensor in the
ice water again and adjust the first knob until it shows 0°C. Repeat with boiling water, but this time use the second knob
for calibration. Adjust until the display shows 100°C. Go back to ice water and fine-tune to 0°C. After a few adjustments you
have calibrated your thermometer.
Profiling the thermometer is a different thing that involves computing. You create a LUT (Look Up Table) and send the temperature
information through the LUT before displaying the results. If the thermometer signal says +3°C, then the LUT tells
the display to show 0°C. If the thermometer signal says +96°C, then show +100°C. Everything in between can be interpolated
and everything below 0 and above 100 can be extrapolated, with more or less accuracy. The LUT in the profile could be
replaced by a mathematical matrix doing basically the same job as the LUT.
Next concept in color management is linearization. With 0°C and 100°C fine-tuned and correct; can we be sure that 50°C also
is correct? Of course not. In order to more accurately display all temperatures between 0 and 100, we should check some
increments (like 25°, 50° and 75°) and adjust for them as well. This adjustment or correction can be incorporated in the LUT
or matrix of the profile.
Now let’s have a look at the concept color gamut. The analogue for our temperature world would be “temperature gamut”
and it is defined as the difference between maximum and minimum temperature of the thermometer display. Let’s say max
is +120°C and min -40°C. That gives a temperature gamut of 160. We can accurately record temperatures between -40 and
+120. If the real temperature is above 120, the display will in-accurately show 120. The temperature is “out of gamut” and
we have absolutely no idea if the recorded temperature is 120,1 or 957,3°C.
Take a picture of or scan a color target. Show the color target on a monitor and print it with a laser, inkjet or commercial
offset printer. If you don’t manage colors in a scientific and tedious way, you will most certainly end up with a result, maybe
resembling, but for sure not being exact like the original color target.

To be or not to be color manageable

The good thing about a scanner is that the separation filters and the light source always are the same. OK, they will change
over time, but basically speaking: it is color manageable. Meaning if you have a known color target and an appropriate
application you can quite easily linearize, characterize and create a color correcting profile for the unit. You scan the target
once, run the application and boom, you have a scanner profile. Next time you scan an image, you run the scanned result
through the profile and it will correct the colors accordingly. You will end up with a digital image, not only resembling, but
being almost exactly the same as the original. That is of course within the color limits of the scanner being used. If the color
gamut of the scanner is greater than the color gamut of the physical image, it is possible to, without any problems, create a
digital replica with “exactly” the same color values.
The good thing about the monitor is almost the same as the with the scanner; it has color filters and a light source that are
stable. The monitor is color manageable, and in an even easier fashion; you don’t need a physical target. It is all in the application.
The drawback is that you need a measuring device; a colorimeter or a spectrophotometer. On the other hand, if
you choose the right device, it can be used for calibration of your printer as well. What you do is to put the metering device
on the centre of the monitor screen, start running the application and wait. The app will show a series of different known
colors on the screen, ask the measuring device how those colors came out and create a monitor profile taking care of the
differences. There is linearization and adjustment of color temperature involved as well, but basically it is a very simple task
manageable by anyone with basic knowledge in computing.
Just a short note on monitor color temperature. The international standards for photography and printing says
5000K is the correct color temperature for viewing and visual evaluation. However, it is important to understand that the
monitor adjustment does not affect the digital image, it only affects how the digital image is presented on the monitor
screen. When you change the color temperature of the monitor, the only thing that happens is that the image is displayed as
warmer or cooler. In order to recognize the colors of the displayed image correctly you have to consider how your eyes are
color managed or rather white balanced. More about that later.
The good thing about the printer is that the inks being used are the same over time. The color of the paper in use can vary
and different papers might need individual calibration, but basically a printer is easy to color manage – it is color manageable.
Just print a known color pattern, measure the result with a spectrophotometer and let the application do the rest. You
will end up with a customized printing profile that is able to tweak the colors of the image to be printed, making them come
out correctly on paper. Again – within the printer’s color gamut limits. If the color gamut of the printer is smaller than the
color image to be printed, we need to adjust the colors in one way or another. This is called color mapping and more about
that later.

The “color managed” eye

Human eyes are extremely adaptable to different color temperatures. The perfect environment for examination of color images
is, in it self, color free. Neutral mid gray walls, a gray background on your computer screen and no colored post-it messages
on the monitor frame. The perfect environment also has ambient light of moderate strength, preferably with spectral
consistency and 5000K. Your vision will be normalized by, or adapted to, the colors and light of the environment.
Now to the most important matter regarding color managed human vision: the neutral gray of your computer
monitor desktop (monitor background) has to color-wise look exactly the same as the gray surroundings (in the room) lit by
the ambient light. If one of them is lighter is of no or little importance, but they have to be experienced as equally neutral
gray. Most probably you can not adjust the color temperature of the ambient light, so the important matching has to be
managed by adjusting the monitor’s color temperature. Now, what if the color temperature of your monitor is not 5000K?
It really doesn’t matter – as long as your eyes are adjusted to the actual monitor color temperature, they will recognize the
colors of the displayed image correctly.

The camera

The most difficult item to color manage in the image workflow is the camera.
But if I use a neutral gray target like the qpcard 101 or 102 or the Spider Cube and make a custom white balance setting in
my camera, then I must be all safe and clear.
No you are not! Custom white balance setting is of course better than relying on the camera’s built in automatic
white balance, especially in difficult lighting situations, but it only takes you a small part of the way towards a color managed
camera. White balancing is not changing the shape of the RGB curves, it is only changing the balance between them;
their position. With RAW images white balancing can be performed in the post processing in the RAW converter with exactly
the same result as in the camera. Real color management means position adjustment and curve tweaking.
Killing or expanding creativety?
Q) Isn’t there a risk that the technical operation involved in profiling a digital camera kills creativity?
A) We are convinced that it works the other way around. Yes, profiling a camera is technical and non-creative. It involves
reading a (short) manual and some computer operation. But we have put down quite a lot of effort to make the profiling
operation as simple as possible. After a while creating profiles is nothing but a routine task. You start with a standard profile
that works most of the time. Then you continue making light specific profiles for difficult lighting situations. Find out the
effect and advantage using sharp profiles. Compare the result with a generic profile and with your standard profile. Profiling
for difficult light is actually making post processing a lot less tedious and thus helping freeing your creative spirit.
When profiling becomes a routine task, it doesn’t limit your creativety at all. In fact the result means broadening of your
creative mind. Post processing can easily become a tedious task where you end up spending lots of time trying to manipulate
your pictures to a state corresponding to your inner vision. Customized profiling results in correct colors and optimal
color gamut as a starting point making post processing so much easier. To start from a favorable position means not only less
time spent but also better end result.