Choosing colors for scientific visualization: the RGB gamut in CIELUV

I make a lot of plots for work, and color is a very useful way to convey information. These colors are usually represented in RGB, especially when dealing with colors on a computer screen.

However, RGB does not do a good job of representing human perception of color. You will find that [0 255 0] (green) appears much brighter than [255 0 0] (red), which is in turn brighter than [0 0 255] (blue). Furthermore, if you sample uniformly from the RGB space, you will find that an unreasonably large fraction of this appears green.

There have been many attempts to parameterize color in a way that is more closely related to human perception. The one that I've been using is the CIE 1976 (L*, u*, v*) color space, aka CIELUV. The L* is supposed to represent the apparent brightness, and (u*, v*) parameterize the apparent color. It is supposed to do this in such a way that the distance between two points in the CIELUV space corresponds to how distinguishable the corresponding colors are to a human with trichromatic vision.

However, not everything in this color space is representable on a computer monitor. That is, not all of those points will fall within the RGB gamut. So without further ado, I present the RGB gamut in the CIELUV color space:

The boundaries are where one or more of the RGB coordinates saturate.

According to my friend, who (like 7% of American males) has impaired color vision, the color contrast is greatest traveling along the vertical (v*) axis. Of course, there are many ways in which your color vision could be impaired, so his experience is not representative of all color blind people.

More plots below:

For the color conversions, I used the colorspace() function from the FileExchange, though MATLAB now has this capability built in to its Image Processing Toolbox.