We know the typical LMS responses for human cones (e.g., Stockman-Sharpe) that could easily be plotted instead of the bell-curve-like things they use here - why? Is it good enough for illustration? You could say, kind of but then all the colors are kind of wrong too. For example, D65 is very blue here.
The article takes a really long time to get to the thing everyone should know: which is that our cones responses overlap a lot, and we get color sensations by (kind of) differencing them. Doing a matrix transform after ten pages to get to chromaticity is technically correct, but it's not the most accessible/intuitive way to teach this.
Nice effort but it would be better if it were closer to "real" color math.
Oh I didn’t know about Stockman-Sharpe, but FWIW the article acknowledges your point:
“The sensitivity curves shown here are normalized approximations (for simpler visualizations and calculations), and are not accurate. In reality, the sensitivity curves are less smooth, and different types of cones have differing levels of sensitivity. For example, the sensitivity of S-cones is significantly lower compared to the other cones. Similarly, rods are more sensitive to light than any of the cones.”
I was thinking to myself this article approaches color better than the majority of color articles I see on the HN front page. Many of them start from RGB and work backwards, often awkwardly with conceptual gaps; at least this start with SPD right out of the gate. The cone response overlap is implied via plots right at the beginning, and the first equation is an integral, and the correct integral… it might not be the most accessible, that may be true, but it’s getting across the right physics concepts first and cleanly separating perception and leaving that murky pit for after the physics is established.
Author here. Yes, as mentioned, all the colours and curves are approximations. I created it in a rush during my last summer break, to be able to submit it before the SoME4 [0] deadline.
I agree that working from RGB backwards results in a lot of back-and-forth between concepts, sometimes leaving unanswered questions. Starting with the SPD means getting to matrix transforms and chromaticity is a much longer route, but I feel is ultimately more intuitive — at least compared to most of the other ways to present it. Also, I wrote this for an audience with some (basic high school) background in math, but zero background in colours. So I'd rather it be drawn-out than underexplained. I myself didn't know much about cone fundamentals before deciding to write about it :)
There is a Knuth/TeX like elegance in the diagrams that you don't see on the web. More than the content that is amazing; and the visualizations that clearly took a very long time to make; it is a fabulous piece of art. Really really nice.
This is all dimensionality reduction down 3 with compact bump-like filters. But if you ran PCA on natural spectra you'd get some different kind of filters! Fourier-like things. I want fourier eyes
This is both interesting and weird!
We know the typical LMS responses for human cones (e.g., Stockman-Sharpe) that could easily be plotted instead of the bell-curve-like things they use here - why? Is it good enough for illustration? You could say, kind of but then all the colors are kind of wrong too. For example, D65 is very blue here.
The article takes a really long time to get to the thing everyone should know: which is that our cones responses overlap a lot, and we get color sensations by (kind of) differencing them. Doing a matrix transform after ten pages to get to chromaticity is technically correct, but it's not the most accessible/intuitive way to teach this.
Nice effort but it would be better if it were closer to "real" color math.
Oh I didn’t know about Stockman-Sharpe, but FWIW the article acknowledges your point:
“The sensitivity curves shown here are normalized approximations (for simpler visualizations and calculations), and are not accurate. In reality, the sensitivity curves are less smooth, and different types of cones have differing levels of sensitivity. For example, the sensitivity of S-cones is significantly lower compared to the other cones. Similarly, rods are more sensitive to light than any of the cones.”
I was thinking to myself this article approaches color better than the majority of color articles I see on the HN front page. Many of them start from RGB and work backwards, often awkwardly with conceptual gaps; at least this start with SPD right out of the gate. The cone response overlap is implied via plots right at the beginning, and the first equation is an integral, and the correct integral… it might not be the most accessible, that may be true, but it’s getting across the right physics concepts first and cleanly separating perception and leaving that murky pit for after the physics is established.
Author here. Yes, as mentioned, all the colours and curves are approximations. I created it in a rush during my last summer break, to be able to submit it before the SoME4 [0] deadline.
I agree that working from RGB backwards results in a lot of back-and-forth between concepts, sometimes leaving unanswered questions. Starting with the SPD means getting to matrix transforms and chromaticity is a much longer route, but I feel is ultimately more intuitive — at least compared to most of the other ways to present it. Also, I wrote this for an audience with some (basic high school) background in math, but zero background in colours. So I'd rather it be drawn-out than underexplained. I myself didn't know much about cone fundamentals before deciding to write about it :)
[0] https://some.3b1b.co/
There is a Knuth/TeX like elegance in the diagrams that you don't see on the web. More than the content that is amazing; and the visualizations that clearly took a very long time to make; it is a fabulous piece of art. Really really nice.
It did take a while to make, and thanks for the kind words!
Thank you for enriching us and the web <3 !
very interesting, didn't know my weekend was going to be filled with color science but happier for it, brilliant presentation too
This is all dimensionality reduction down 3 with compact bump-like filters. But if you ran PCA on natural spectra you'd get some different kind of filters! Fourier-like things. I want fourier eyes