DCam 1 Example

(Go back to All About RGB Working Spaces)

(Revised March 7, 2017)

The colors of this digital snapshot readily fit within the very small gamut of DCam 1, because the image has both neutral highlights (the clouds) and reasonably neutral shadows, especially the very dark shadows. The version you see here has had a +20 chroma variant applied after RAW conversion. The clipping amounts to only a few pixels in the medium shadows where there is moderate color.

Were the lighter tones in this image very colorful at all, DCam 1 would probably not hold them. Each working space, in a Yxy plot, resembles a triangular tent with vertical walls and a roof that somewhat resembles a three-sided pyramid. The larger gamuts have the three corners of the tent further out, but they also have roofs which slope away from the hight point, the white, at lower and lower slopes as the corners move out. A small space like DCam 1 is especially lacking in headroom, and most acutely on the warm side of white. We can see this clearly in the side view of the Five DCam Spaces illustration near the end the main profiles page.

In contrast, DCam 5 has so much headroom that RAW conversions rarely need the extra room that it has, compared with DCam 4, if any care is exercised during RAW conversion. Still DCam 5 could be useful for automated RAW conversions, to avoid essentially 100 percent of clipping at that point, keeping in mind that as you give yourself more room, you increase quantization proportionately. DCam 5 is designed to very precisely include all of the entire spectrum locus, i.e. all of the real colors, and no more than required to do that. It is huge. Also remember that during the editing phase, we ordinarly need to push colors in ways which demand more gamut, and that if you're using chroma variants to handle the portion of that work which includes adding color, they give you extra gamut volume, as needed for that, and thus you're better off not to start that process with an overly large space to begin with, inasmuch as you can avoid winding up with really gigantically expanded spaces. It's also true that although our data might typically have started off with a 14-bit analog to digital conversion, the tools we use to adjust color are 8-bit in their precision. One point of color balance adjustment in a double-radius space has double the effect as in a single-radius space.