I have tried several methods for handling out of gamut values.
The first one was a Normalized Moment space , which is something Troy mentioned in another forum, it worked pretty well because any chroma greater than 1 in this space meant it was outside the Gamut, but this had some issues with values too far from the xy triangle and because it kept photometric luminance constant it wasn’t the best looking in some scenarios like negative luminance in all camera spaces.
The second method is a normalized Spherical Model, it basically is a smooth version of HSV, the S channel is 0 to 1 for in gamut, and the V channel is the same as Max(r,g,b) but calculated mathematically based on the first method instead of by using max(r,g,b). I have seen similar attempts explored before but not sure why it wasn’t explored further as it’s the best option I have seen so far, its chromaticity linear, it doesn’t have issues with negative luminance and its gamut independent.
This model I use pre-image formation and for mapping the formed image to smaller spaces.
I have even used it to make a chromaticy linear image formation like the current attempts for CAMDRT 2.0
Lowguardrail.nk (44.1 KB)