[mpais]

> Lossless ones are basically just ZIP

Lossless image compression is a vast field with myriad different requirements and solutions, and generalizing like that is just plain wrong. Most lossless image codecs for photographic or similar rendered content don't use a Lempel-Ziv stage like PNG does, they exploit the spatial and possibly spectral correlations to form predictions, be it with simple linear predictors or more complex approaches. However, for simple non-photographic images like cartoons or some such, the LZ-based stage can provide significantly better compression than the simpler prediction-based methods.

Even if the premise of the post is flawed, it's always nice to see people interested in data compression and trying to learn more about it, so I'm all for more "nonsense" posts if it helps draw attention to the field.

[crazygringo]

I could have been more specific -- I meant the currently common lossless formats of GIF, PNG and TIFF. In other words, I was just thinking about lossless image compression available to the average user.

It's true there are newcomers. WebP is slightly more advanced in lossless mode but still follows the same basic Lempel-Ziv principles, and I've never found a good explanation of how JPEG XL implements lossless mode but that hasn't gained widespread adoption yet anyways. HEIC is sometimes advertised as having a lossless mode but it doesn't really (its "lossless" is really just "maximum possible quality lossy" from everything I've seen). And obviously there are lots of niche/experimental codecs that work along different principles such as what you describe. And PNG does have a special mode for solid-color line art that references the previous row.

But the average person encoding a photographic image losslessly is probably using something based on Lempel-Ziv probably 99.99+% of the time -- not something built on top of spatial correlations.

[lifthrasiir]

For JPEG XL, refer to its format overview [1]. In short its lossless mode uses a combination of multiple techniques: the rANS coding with an alias table, LZ77, reversible color transforms, a general vector quantization that subsumes palettes, a modified Haar transform and a learnable meta-adaptive decision tree for context modelling.

One good thing about JPEG XL is that its lossy mode also largely uses the same tool, with a major addition of specialized quantization and context modelling for low- and high-frequenty components.

[1] https://github.com/libjxl/libjxl/blob/main/doc/format_overvi...