Show HN: High End Color Quantizer
111 big-nacho 30 6/10/2025, 11:50:15 AM github.com ↗
This is a personal project I've been working on for a long time now.
I stumbled upon the color quantization problem while doing something related for work. I then found an interesting paper for which I could find no implementations online, and the thing went from "let's implement this paper" to getting pretty obsessed with the whole thing.
It's at an early, eaaaarly stage. There's a lot of work to be done, and it's a memory hog, but generally speaking works quite well, and the output is for the most part very high quality, so I'm happy to share it as beta.
If your goal is for users to adopt the use of the software, then you can easily increase acceptance by going the proverbial extra mile:
1. Make it installable via `uv tool install patolette` with the optimisations taken care of automatically. 2. Compare its results in the documentation/on the project Web site against the incumbents. https://news.ycombinator.com/item?id=26646035 Find standard test images https://ddg.gg/?q=color+quantization+test+corpus , copy the split-image/slider technique from https://uprootlabs.github.io/poly-flif/
The rationale for this is that each interested user should not have to replicate this work on his own.
sRGB is a nonlinear colour space and so you can't do linear operations in that space (because a^2 + b^2 isn't (a+b)^2 in general).
Gifski uses the png-quant library, and I wonder how this compares?
(I guess APNG is supported in many browsers, but uploading one often results in deleterious resizing/recompressing operations that ruins the animation. Discord uses APNG and webp for stickers afaik)
Colour quantisation is still one of the best lossy image compression formats for when you have almost no memory or CPU.
Still, color quantization is a really interesting rabbit hole to go down if you're new to graphics programming, or at least it was for me. It's a mixed blessing that almost nobody has to confront the problem anymore.
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I'd say that showing full example results are the most important part of showcasing a "high end" color quantizer.
Regarding full examples, because some other projects seem to have cherry picked cases where they perform very well, I wanted to go for a "try it out yourself" approach, at least for now. Maybe in the future I'll add a proper showcase. Thanks for the feedback :)
the quant frog [2] is interesting since it has an artificial single pixel line at the top with a ton of colors to trip quantizers up.
[1] https://github.com/leeoniya/RgbQuant.js/
[2] https://github.com/leeoniya/RgbQuant.js/blob/master/demo/img...
Does it also support colour spaces other than RGB, CIEDE (I think I saw that in the source), i.e CMYK for paint mixing, and similar ilk?
I have a few personal projects that would benefit from a library that is wide ranging in the colour space, dither algorithms (I only saw riezsma) and quantizations.
Typically these are all usually implemented in different libraries :(
Thanks!
The optional K-Means step just grabs whatever palette the original method yielded and uses it as initial state for a final refinement step. This gives you (or gets you closer) to a local optimum. In a lot of cases it makes little difference, but it can bump up quality sometimes.
Something that always bugged me about palette generators I've used is how they end up not picking any colors intense enough for the deepest highlights/shadows, because they use colors close to the average of various sets of pixels.
The result is that the most eye-catching parts of an image end up washed out, reducing the appeal.
My hack to address this has always been making a larger image with big white/black bars around the original image to push the palette generator to include a few really bright or dark colors.
From the look of your examples, your project addresses this too, right?
Btw, I opened an issue about the graphs in your readme because, as a programmer, they don't tell me if your program is fast or not. From a user's perspective that thinks in terms of the side length of an image, the numbers presented are very useful, but they might be even more useful in table format.
https://news.ycombinator.com/item?id=9213955
see that whole thread, too
https://github.com/OpenPrinting/libcupsfilters/pull/92