by quietbritishjim
1 subcomments
- > The final piece of the puzzle is gamma correction. Applying gamma correction to these RGB coordinates produces a new set of values which we call (R', G', B') that are related to the original by a transfer function 6 ... The reason this is done is to account for how our eyes perceive brightness nonlinearly. We can distinguish changes in dark shades much more easily than light shades because a linear increase R in has much more of a relative effect when R is small. Switching to (R', G', B') therefore provides more resolution in dark regions of the image where the eye is more sensitive to variations in brightness.
I'm surprised that this isn't mentioned much earlier and much more prominently. Instead, it's practically a footnote.
Maybe I'm mistaken, but I would bet 90% of the awkwardness in the very first image is from averaging these values (R', G', B') for the gradients rather than switching to the true linear values, averaging, then converting back. This classic MinutePhysics video covers it well:
https://www.youtube.com/watch?v=LKnqECcg6Gw
- There's something that tends to go unrecognized, a function of the way our monitors work. Any color that is made of multiple primaries, such as magenta, cyan, or yellow, will naturally be brighter because more photons are emitted from the display. Not twice as bright, since our eye response is non-linear, but noticeably brighter.
by mncharity
1 subcomments
- > The right approach would have been to select a color appearance model (CIECAM02 is the standard), convert all our colors to this coordinate system, do the mixing in this coordinate system and then convert back to RGB. That being said, I did not want to deal with all the extra complexity that would have come along with this. Instead, I opted for a much simpler approach.
Python's nice `colour` package supports several color appearance models.[1]
[1] https://colour.readthedocs.io/en/master/colour.appearance.ht...
by strogonoff
2 subcomments
- It is very interesting that whereas an incandescent lightbulb and a white LED (e.g., that Macbook screen) appear to us the same colour, their underlying spectra are very different (a solid black body radiation spectrum from the former and a choppy one from the latter).
I vaguely recall this is also known to cause a phenomenon where certain material can appear a false colour under certain light (especially a problem in case of, say, physical paintings and their various pigments), if whatever bands it reflects would align with the spectrum of emitted light in an unfortunate way.
(NB: even though the topic is relevant to his field of work, the author of the paper is not the digital videographer and YouTuber Brandon Li.)
- These wavelength-indexed spectra always seem a bit weird... the blue is so cramped! When you plot them by frequency they feel just right. We say "ultraviolet" and "infrared" for a reason; never "infraviolet" or "ultrared".
It's like a piano that had the high notes to the left.
- If you are interested in this topic, we have a fully feature colour science Python package that can of course render the visible spectrum: https://github.com/colour-science/colour?tab=readme-ov-file#...
by vismit2000
0 subcomment
- https://ciechanow.ski/color-spaces/
- > we write the color associated with a spectral distribution as C[S] where C is the function that takes a distribution and outputs the corresponding color.
Unrelated, but can anyone tell me the purpose of using the square bracket notation here, instead of the usual parentheses?
- One thing peculiar about the final image is how desaturated it is. It doesn't actually represent the spectrum, which is by definition the pure, fully saturated colors. It's rather a gradient of a bunch of desaturated hues. For example, where is pure yellow on this gradient?
- I would say that most depictions of the visible light spectrum on the internet, and in textbooks, are not for physicists, but for "average" folk who simply want the gist of the visible light spectrum. Most of us don't need the exactness the author provides in his write up.
- Very well put together set of fidgeting. I really appreciated the addition of the P3 color space sample at the end. For seeming like such a small addition in terms of area on the chromaticity diagram the extra stretch at the extremes goes a really long way.
- This doesn't account for Tetrachromacy does it
https://en.wikipedia.org/wiki/Tetrachromacy
It would be interesting to learn more about colours spaces developed with Tetrachromacy in mind. I guess the rest of us should be classed as visually impaired.
- is nobody going to comment on the fact that this page seems to be written entirely in latex?
- Interpolate between the spectral color and gray for existing distortion.
Designating 460nm blue in terms of the Abney affect to render a realistic spectrum.
- Screw, me, I was reading the title as "Rendering the Vibe Spectrum". I clearly need a break.
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