I work in photographic printing, so am intimately familiar with this.

There's also the matter of self-luminous colors... when others would be
black, very pure reds and blues will still appear colorful. You need to be
careful with this when it comes to user friendliness; dark red and dark
blue text on a black background or inverted is, for practical purposes,
black on black.

This becomes very obvious when you convert an RGB image to only the L*
component!

Even rudimentary CIELab support, for showing a read-only greyscale copy of
a form, would help in identifying accessibility issues.

On the other hand, Lab color is totally unintuitive to work in as input
unless you limit yourself to the brightness component only. I think it
would only confuse users to present it as a color picker, like the HSL
wheel.

On Wed, May 18, 2022, 13:33 tim Rowledge <tim at rowledge.org> wrote:

> From time to time we have to think about how we handle colours and
> gradients; it's a quite complex subject that mixes physics and biology.
>
> An acquaintance at UBC teaches this subject and recently posted to another
> list, and gave me permission to share -
>
> > Hi folks,
> > Delurking for the first time in quite a while to weigh in, I do teach
> about
> > color and color perception.
> >
> > In short:  The right color space to use for interpolating colors is
> CIELAB
> > (aka L*a*b* or LAB or Lab), which is carefully designed to be
> perceptually
> > uniform.  RGB is dramatically non-uniform, do not interpolate in that
> color
> > space because you're in for a world of hurt. Unfortunately, while HSV/HSL
> > is more uniform than RGB in the colorful dimensions, it isn't truly
> uniform
> > either in the black-and-white dimension, so it's not a good bet. If you
> do
> > the math in the CIELAB space you don't need to think about gamma
> > correction, that will just confuse the issue.
> >
> > Tools:
> > Example D3 code plus explanations from Mike Bostock at
> > https://bl.ocks.org/mbostock/3014589
> >
> > Observable notebook with some examples and analysis of interpolation in
> > different color spaces from Zan Armstrong at
> >
> https://observablehq.com/@zanarmstrong/comparing-interpolating-in-different-color-spaces
> >
> > Interactive demos from Carlos Scheidegger at
> > https://cscheid.net/projects/color-interpolation/
> >
> > LAB/Lch  color gradient generator at
> > https://davidjohnstone.net/lch-lab-colour-gradient-picker
> >
> > Older but in-depth post from Gregor Aisch (with a lot of commentary from
> > experts below) at
> > https://www.vis4.net/blog/2011/12/avoid-equidistant-hsv-colors/
> >
> > In long: For more on color here's the three relevant videos from my
> > visualization course. The third one goes a bit into the question of color
> > spaces in the first seven minutes, but it might make more sense if you
> > watch the first one to establish some basics first. The second one is
> > mostly focused on the issue of colorblindness.
> >
> > Color I (19 min)
> >
> https://www.youtube.com/watch?v=QNDd_hvdORw&list=PLT4XLHmqHJBeB5LwmRmo6ln-m7K3lGvrk&index=15
> > Color II (6 min)
> >
> https://www.youtube.com/watch?v=yUsL6a1d9n0&list=PLT4XLHmqHJBeB5LwmRmo6ln-m7K3lGvrk&index=16
> > Color III (18 min)
> >
> https://www.youtube.com/watch?v=zt8uIbSMeFg&list=PLT4XLHmqHJBeB5LwmRmo6ln-m7K3lGvrk&index=17
> >
> > Cheers, Tamara
> > ----
> > Tamara Munzner
> > Professor, Department of Computer Science, University of British Columbia
>
>
> tim
> --
> tim Rowledge; tim at rowledge.org; http://www.rowledge.org/tim
> I majored in Art and Logic. Now I draw my own conclusions
>
>
>
>
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