Posted by moultano 15 hours ago
Modern color modeling is much richer then 3 parameters, because human vision is much more complex than simply color frequencies. CIE 1931 was low brightness, 2 degree field of vision, center of vision derived. As brightness increases, color perception shifts. Colors are NOT linear; sRGB and CIE 1931 chose such a small section of human vision that they approximate that section with a linear assumption. Modern CIECAM models are not linear, are not 3 parameter, because color is not linear (CIECAM02 is 6 parameter [2], there are several after that one). A century of experiments, wide color gamuts, HDR, have thrown out CIE 1931 as a good model. It’s only momentum now, and slowly higher end things are replacing it.
A good introduction is Color Appearance Models, by Mark Fairchild, also any of his technical papers give a starting point into the science.
[1] https://community.acescentral.com/t/cie-2015-cmfs-what-would...
Does that look like 3d?
Either way, you can project a volume onto a plane, which is great for communicating visual data on paper or screen.
The interesting question is "why that arc in particular"; my ignorance will shine through if I speculate.
I assume that the projection encodes something about our relative perception of each cone's band, hence the big green corner.
This will actually differ from person to person. If you look at a pure yellow wavelength light next to a red/green light mixed such that they create the exact same perceived yellow to you, it will look different to another person.
Aside from that, not really sure what a 3d view with the dimensions being r,g,b would actually offer
1) trying to convince content makers to use new custom high-gamut hardware to capture the new spot colors
2) you'd need a full video content production pipeline that can render to that color space
3) finding enough people to care enough to pay the (substantial) premium for niche production numbers.
4) Most content just doesn't warrant high gamut unless it's narrated by David Attenborough.
So, you have both a chicken and egg problem, and not that big of a TAM to warrant the struggle.
> Nearly every species of scorpion intensely fluoresces under UV light. […] Scorpions have photoreceptors in their tails, separate from their eyes. […] It is hypothesized that a scorpion uses this fluorescence to tell whether any bit of its body is left exposed from its hiding place. Its tail “looks” down at its body, and if it sees its own fluorescence, it knows it is exposed to light, and in danger.
And a special call-out to the “Andean Cock-on-a-Rock” :), see a photo in the article.
https://en.wikipedia.org/wiki/Stabilized_images , https://en.wikipedia.org/wiki/Fixation_(visual) , https://en.wikipedia.org/wiki/Microsaccade
We fake the movement of anything we're staring at, by means of tiny automatic eye movements, in order to remain able to see the thing at all.
I wonder if the inaccurate representation of colors by screens, etc, in any way underlies the distinctive color palette of many AI image generators?
I do have a question that the article doesn't seem to attempt to answer, though. The article says (paraphrased in my new understanding) that any spectra which makes the cones in your eyes react the same way will result in seeing the same colour. Do we know of any examples of this?
(Colour-blindness seems like an obvious example; I'm curious though if there are any examples of two common scenarios where it can be demonstrated that there are different spectra in each, and yet most people will see them as the same colour.)
See the first minutes of this video, where he has a spectrum analyser: https://youtu.be/-DyrBDsKA5s?si=mRJPT2ecy6NqpB4N
On one side you have an apple, illuminated by natural sunlight. it fills your eye with a rich texture of subtly mixed frequency's covering the whole gamut of visible and invisible light. On the other a picture of an apple composed of brutal pure frequencies only emitting at 430, 540, 570 Nm. Can you tell the difference?
So there's 3 options you have for rendering the colours outside the sRGB space in this kind of image.
1. Don't. This is usually the most honest, and what all but the first diagram in this article opts for.
2. Clamping. You just set the green component to 255 for every colour beyond green=255, which effectively looks like you extend the edges of the triangle to the edge of the visual range. This is the most common, and the approach used in the article's first image, but it's basically a lie. Some articles will dumb the out of range colors to make it clear they're not the real colour, but this article's first image doesn't.
3. HDR: If the author uses an image format capable of decoding HDR data, and your browser, OS and monitor, and the author's authoring pipeline are all correctly configured to pass through that HDR data, you can get a bit more colour, depending on your monitor. Not the full visible gamut, but up to whatever colorspace your monitor is using.