White balance and highlight protection

When you fix the white balance of an image, you typically shift the colors using some linear or nonlinear transform. In the case of ColorLab, it's a chromatic adaptation transform based on the CIECAT02 matrix, and it shifts the image colors between two illuminants. The source illuminant is one that the user has helped to define by clicking a pixel in the image that is meant to be white. If this is an orange-tinted color, a light source with these characteristics is found by the algorithm. The destination illuminant is always based on the standard D65 one, which is what modern PAL/NTSC/HDTV as well as computer video assumes.

Anyway, when you shift colors in this way, and some colors are clipped to pure white or nearly pure white in the original image (which has a bad color cast overall), those highlights of the image might look pretty ugly afterwards. See this clock for an example:

As you can see, overall the image has been improved but the clock face is now a dull cyan shade. The linear white balance transform didn't take into account that this was meant to be a highlight. Trying to white balance this image in Adobe Lightroom will give a result that isn't cyan-tinted. However, it seems that Lightroom does this by raising the brightness of the entire image. This causes the clock face to again clip at white. I don't like that, since it might compromise the rest of the image.

So I had to find my own way. After a little experimentation, and discussion with John O., I found a solution that seems to work at least most of the time. I added an option called "Protect highlights" to ColorLab, and made the strength of the effect configurable.


This looks a lot better. :) What the algorithm does is examine the R/G/B value of the original pixel, and depending on how close it is to the maximum (255 for each channel), it shifts the WB-corrected pixel towards a desaturated version of the original. Therefore the luma of the original is retained, while removing the original color cast.

I still have to test this technique on more images, but it looks promising.