Video Calibration

The New Wave of Color Calibration Technology: Cube Calibration

ARTICLE INDEX

Current CMS Systems for Cube Calibration

First, let's look at the unmentioned issues that exist from the CIExy chart that everyone sees attached to reviews. The first issue, and a large one, is that color is actually a 3D object. In the CIExy chart that most people use, colors are represented by two, not three, distinct variables: x and y. In this system, x and y values represent tint and saturation, while Y represents brightness or luminance. As you can see we have accounted for hue and saturation but not the Y value, which happens to be the most important element for our visual perception of colors. Even if all of these points line up perfectly, given there is no representation of luminance on these charts, highly perceptible errors can still be observed. For example: if there is too much red, green and blue, then red will be too bright. The shade of red might be perfect, but the Luminance is just too high. This is one fault that the common CIExy chart does not show.

The other major issue with the CIE diagram for evaluating color is that you are only looking at 3 or 6 points in total. With our standard 8-bit RGB displays, we can generate 16.7 million colors, but we're only looking at the performance of 6 of those to determine the performance of a display. What about the rest of the points? The CIE diagram represents a snap shot of a small sliver of data as the data is all collected at a given stimulus point. What if 100% saturated red or blue are perfect, but every other saturation below 100% is incorrect? What about colors that involve mixing red, blue, or green together, and not just a single primary color? The chart shown with most reviews addresses none of these questions.

We can show data that details this performance better using a few different items. One is a saturations chart, which measures saturations other than 100% to see how well the CMS handles those colors. Another is a luminance chart that will show how less intense signals are managed by the CMS. Finally we can use the Gretag Macbeth Color Checker chart that is well known in the photography world, but not as well utilized in the consumer display world. This chart uses 24 colors that represent common objects in the world, like natural greens, sky blue, skin tones, and more, and none of these are points that we try to calibrate to with a CMS. This is a much more demanding test of displays than other test patterns, but also more applicable to real life.

If you're only concerned with how well Cube Calibration performs, feel free to move onto the next page, as these next few paragraphs go into some technical depth about why current calibration systems don't often work correctly.

A key reason to understanding why CMS systems can't do this correctly is to understand how most CMS systems work. Your display outputs everything as RGB values. LCD, CRT, Plasma, OLED, or any other display technology out there currently uses RGB for its display output (although a few add a yellow "primary" to increase light output, but this can cause problems obtaining correct color performance). Most CMS systems are instead designed around HSL, or Hue, Saturation, and Lightness controls, and not RGB controls. When HSL was designed in the 1970's, it was easier for computers of the time to process and for people to comprehend, and for people visual selecting a color; it makes it easier to do than to try to calculate RGB coordinates. Making that orange lighter, or darker, or more saturated is a single control and much more convenient that using RGB.

Where the RGB color space is a linear cube, the HSL color space resembled a pair of cones, with one inverted and the two cones connected at their bases. To go from Black to a solid color in RGB is a linear line from one corner of the cube to another, whereas in the HSL colorspace the path is not as linear. The result of this is that while those points on the CIExy chart might be correct, the points in-between are much harder to determine when calculating them in HSL than in RGB as the colorspace isn't linear like RGB. In many traditional CMS systems this becomes very apparent when you test for saturations, as you can get 100% or 75% correct, but any of the other values are off by a considerable amount, as it can't correctly calculate the non-linear HSL colorspace correctly.

Both the Lumagen Radiance series and the SpectraCal ColorBox use a linear-Gamma RGB color management system for their internal calculations. This should allow for them to produce more accurate colors than the HSL method when you look at data inside the primary and secondary color points. Of course, they also can support 3D cube calibrations, which is what we will discuss next.

3D Cube Calibrations

As we mentioned, most CMS systems are based off the idea of calibrating the white point, then calibrating the primary, and possibly secondary, colors, and then using calculations to get the other millions of colors correct. This is very nice in theory, but it has some problems in real world practice. We might have a display that doesn't exhibit a perfectly linear response, so even if the calculations are correct, the resulting output is incorrect. The calibration might require large adjustments in the CMS system, and the bit-depth available for calculations is too small, resulting in posterization or banding. The controls might not have enough adjustment available to get everything correct, or they can interact with each other, resulting in a tricky balancing act for performance.

Cube calibration works differently. The way to visualize this is to see color as a 3D cube, with 8 points, one at each corner. Two points on diagonally opposite corners are White and Black. The other 6 corners are the primary and secondary colors. Inside the cube you can encompass all of the colors that are possible to be created using RGB. Our previously discussed color systems use between 5 and 26 points for calibration. 6 points are the corners of the cube, and the other points are a path from black to white inside the cube, representing the grayscale. To determine any other color, you need to calculate the distances between these known points, and then output that value.

What a cube calibration does is take multiple measurements for each side of the cube and inside the cube, not just a single corner measurement. With the Radiance line, we can do 5 points on each side of the cube and between each corner, for 125 total points of data, plus 21 independent points along the gray-vector. The ColorBox allows for up to 17 points per side, or over 262,000 data points. Now instead of having potentially large distances between known values, we have very short distances to transverse.

This lets us now account for non-linear displays, and it substantially reduces the amount of possible error in our calculations. Now using more complex methods of checking display performance, such as the Colorchecker chart or Saturations chart, we should start to see lower values in those data points. The color points that most people use for reviews, primary and secondaries, will not have changed if the existing CMS was already good enough to make them accurate. What you will see from this review is that just using those points doesn't provide a full picture of what a display can do, and just were CMS systems are lacking.