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Color: From Hex codes to Eyeballs

jamie-wong.com

11–20 of 55 posts

Re: Color: From Hex codes to Eyeballs

#13

I've been trying to build my own mental model that's easy to visualize how your eyes build color. Imagine 3 people (r,g,b) standing across from each other playing a 3 way tug of war with a bowling ball in the center. They each can feed on certain ranges of radiation to help them pull the ball towards them, color is determined by where the ball ends up. If red and green pull equally the ball moves sideways out of the…

> Additionally there is no such thing as pure green, because all radiation that green feeds on will also feed either red or blue as well.

You can exploit cone fatigue to experience a greener green: make the red and blue people play tug of war by themselves with high intensity, then if you immediately call in green's fresh strength, red and blue will be easily overpowered.

(Slight model inaccuracy: the cells themselves aren't the colors, they're just cells with low-, medium-, and high- frequency sensitivity. Interestingly, the color experience you get from activating just one type of cell is different from the one you get from monochromatic light at their respective spectral peaks. I find deep (long-wavelength) red, for example, to be rather different.)

Re: Color: From Hex codes to Eyeballs

#14
post #7

How can an image properly illustrate (in RGB) what colors are outside of the RGB gamut? That image must be inaccurate? Should I assume the image is technically incorrect but a good illustration of what the RGB gamut does look like?

From the article: "All of the diagrams in this blog post are in sRGB color space. That means that all colors outside of the sRGB gamut aren’t accurately reproduced in the diagrams in this post!"

Re: Color: From Hex codes to Eyeballs

#16

The part where he takes the human sensitivity into account has grabbed my attention. It looks a little suspicious to me the way he simply just multiplies the normalized relative sensitivity measure with the spectral fluxes. The way it is calculated now, the only way for a spectral flux (SLF) to be optimal considering its spectral luminous flux (LF) is to be entirely concentrated at ~550nm, laser-like. However, such a…

> the only way for a spectral flux (SLF) to be optimal considering its spectral luminous flux (LF) is to be entirely concentrated at ~550nm, laser-like.

Yes, that's correct. For maximum brightness given a limited amount of energy, you want all the light to be emitted at a wavelength matching the maximum of the eye's luminosity function. Of course, if the light is very bright, it will saturate your green cones, at which point you would want to stop adding 550nm light and switch to a wavelength that matches one of your other cones.

Re: Color: From Hex codes to Eyeballs

#18

I have been working on a video game with a puzzle mechanic involving mixing paint to create trails in a racetrack, and I have learned a lot about the intuition gaps in light/color physics theory while testing with people. I was going to make a post about it but this is an even more in-depth exploration of the whole thing from the bottom up. I will be referencing this on our game site when it's up!

Could you elaborate on the intuition gaps that people have? I have a pretty good understanding of color theory and the physics/biology behind it, but I have no knowledge on the pedagogy of it. Hence learning about the more common false beliefs sounds fascinating.

Re: Color: From Hex codes to Eyeballs

#20

The part where he takes the human sensitivity into account has grabbed my attention. It looks a little suspicious to me the way he simply just multiplies the normalized relative sensitivity measure with the spectral fluxes. The way it is calculated now, the only way for a spectral flux (SLF) to be optimal considering its spectral luminous flux (LF) is to be entirely concentrated at ~550nm, laser-like. However, such a…

> It looks a little suspicious to me the way he simply just multiplies the normalized relative sensitivity measure with the spectral fluxes.

What is suspicious about it? This is how all response functions work mathematically, both for humans and animals, as well as for mechanical sensors.

The response function is the measured ratio of the input value to the output response (for a given wavelength in this case, but it could be for any measurement at all.) Because it's a ratio, simulating the response is a multiplication, no other operation will be correct.

> I would expect a LF to be optimal when it matches the relative human sensitivity in shape

Arriving at that idea does make some intuitive sense, but it would not be optimal. For the best possible response, you'd put all your energy into the maximum of the response function and nowhere else.

Imagine you could bet on a coin toss where the coin is known to land on heads 2/3rds of the time and tails 1/3 of the time. You can guess the tosses in advance, and for every correct guess you win $1. Should you bet on heads 2/3rds of the time and tails 1/3rd of the time, because that matches the roll probability? Or should you bet on heads all the time? It's simple to show that always betting on heads will net more money, statistically speaking.

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