Genesis of the Idea what led to the discovery of these simple facts
While reviewing my earlier work on color integrity I made two key observations where the rules of color integrity as I had defined them did not seem to work as expected. First, with my mathematical approach, managing the colors in order to get and then maintain color integrity in a digital image required considerable care, often in knowing what to avoid doing. Yet it is rare to see a painting with the same sort of unsettling color. My past study of the methods of oil painting did not turn up difficulties of this nature. Oil paintings (that were intended to) typically and obviously showed color integrity. Of course oil painting requires considerable knowledge of color and how colors work together, but why did the color integrity problem not befall oil painters as it has photographers?
Equally puzzling was the phenomenon of "blackpoint," a common adjustment for digital images which completely violated what I then understood to be the rules necessary for maintaining color integrity. Yet the colors in an image remained very natural over wide ranges of blackpoint adjustment. Furthermore, the blackpoint adjustment is most often done incorrectly (as is the case in Photoshop). I found that when using the incorrect form of the adjustment, the colors lost their natural appearance. Blackpoint was regarded primarily as a correction for common flaws in the light sensitivity behavior of film and image sensors in general. If blackpoint really was just correcting for a flaw then it would be expected that there would be just one correct setting but instead the colors looked natural over a wide range when the correct form of the blackpoint adjustment was used.
These two puzzles caused me to explore both artistic painting and the mathematics of blackpoint to see if I could find answers. As it finally turned out, it really was necessary to run the two studies in tandem to arrive at a final solution that is both very surprising and yet quite obvious after the fact. The study of artistic painting led me to understand that my earlier version of color integrity was exactly equivalent to the practice of adding various amounts of black to a palette color to produce the darker shades of the same color for a painting and that this in turn was exactly equivalent to lowering the light level on the original scene. Adding black does not change colors and so using it to preserve color integrity seemed obvious and that led me to explore adding white, which also does not change colors. I was amazed to find that adding white was exactly equivalent to using the correct blackpoint adjustment! This completely explained the blackpoint mystery. Adding white by various means in painting is used to produce glare in highlights and also to produce fog effects. Indeed, it is exactly equivalent to the presence of fog in the original scene. Thus the blackpoint adjustment can be used to increase or decrease the level of fog in a photographic scene, which it can do with marvelous accuracy. However, this requires the correct blackpoint adjustment. Photoshop and other image editing programs normally do the blackpoint adjustment incorrectly and so visibly damage color integrity long before significant fog can be added to or removed from an image.
Still, at this point I had discovered the solution to maintaining color integrity in an image by simply adding or removing black or white and it was mathematically obvious how this simple rule could be extended to deal with color balance while maintaining color integrity.
Perspectives and Comments
Genesis of the Idea what led to the discovery of these simple facts.
Why We Give Few Illustrative Examples of Color Integrity
Color Integrity from the Viewpoint of Artistic Painting.
Color Integrity from the Viewpoint of Basic Physics and Mathematics.
Trying to Deal With Color Integrity in Photoshop
Color Integrity and Color Balance A Few Examples
Comments on Calibrating Digital Images
"Acceptable Accuracy" in Calibration
Calibration and Color Profiling
The Pitfalls of Using Profiling as Camera Calibration
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