guetzli VS zopfli

JPEGLI = A small JPEG

The suffix -li is used in Swiss German dialects. It forms a diminutive of the root word, by adding -li to the end of the root word to convey the smallness of the object and to convey a sense of intimacy or endearment.

This obviously comes out of Google Zürich.

Other notable Google projects using Swiss German:

https://github.com/google/gipfeli high-speed compression

Gipfeli = Croissant

https://github.com/google/guetzli perceptual JPEG encoder

Guetzli = Cookie

https://github.com/weggli-rs/weggli semantic search tool

Weggli = Bread roll

https://github.com/google/brotli lossless compression

Brötli = Small bread

A JPEG encoder developed by Jyrki Alakujala, Robert Obryk, and Zoltán Szabadka, and released by Google in 2017. Guetzli specializes in high-end image quality where it is claimed to produce significantly smaller files than prior encoders at equivalent quality, albeit at very low speed. It is named after the Swiss German expression for biscuits, in line with the names of other compression technology from Google. github.com/google/guetzli

I'm a huge fan of AV1 for video, but for images JPEG-XL is simply the better codec than AVIF. If you've not actually looked closely at a comparison and are just on the side of AVIF in this debate because it's based on AV1 (and maybe you hate HEVC / HEIC), I'd urge you to look closer. Jpeg XL is pretty unrelated to Jpeg, Jpeg 2000 and Jpeg XR and instead a successor of Google Guetzli, FLIF and newer research.

I've never had much luck using jpegoptim. In most cases it's only removing the metadata, which isn't much on high-res files.

Guetzli is nice, if you don't have too many images to recompress (quite slow): https://github.com/google/guetzli

If you're going for full re-encoding, it might help to decode the current JPEG with https://github.com/google/knusperli ... but if you re-JPEG that you might have second-order artifacts. Give it a try. Then compress with https://github.com/google/guetzli

You know. I was actually quite annoyed ( to say the least ) with the post. For one the post is lacking a date, and you have to search yourself it was published in April 2017. And without a date the article is completely lacking context because Guetzli [1] hasn't been worked on for 5 years. And as [2] mentioned its work and derivative was ultimately merged into JPEG XL, which is a very decent image format. ( People should definitely check out JPEG XL if it is not on your radar yet )

But then I notice it was Dan luu who submitted it, which likely means there must be something much deeper than is what is shown on the surface. So what is the context here ?

[1] https://github.com/google/guetzli

[2] https://news.ycombinator.com/item?id=30622303

This project uses HTMLMinifier, optipng, and zopfli to create a custom production Elm build pipeline. You can see how I make use of these tools in this build script. Here are the results in case you're interested. I used the same ideas from this project to build and deploy dwayne/elm-conduit, which you can learn more about in my article Yet Another Tour of an Open-Source Elm SPA.

I'm making a 2D game with lots of PNG assets. I recently found that ZopfliPNG regularly reduces the sizes of my assets by ~3x compared to Asesprite's output. I've tried a few other PNG compression tools, but ZopfliPNG consistently outperforms the others.

I mean something better than Google's best engineers trying to optimize LZ77's compression as much as humanly possible, while remaining compatible with the DEFLATE/zlib bitstream.

zopflipng typically beats pngcrus and optipng (on Linux at least) but by default it drops auxillary PNG chunks [0] which can result in browsers (and other applications) using a different color space, causing the resulting images to look more washed out than the original. To prevent this you need to explicitly pass --keepchunks=cHRM,gAMA,pHYs,iCCP,sRGB,oFFs,sTER to zopflipng.

Unfortunately it (and most other tools) don't have APNG support, keeping only the first frame.

[0] https://github.com/google/zopfli/issues/113

I tried going with a lot of different compression algorithms, in the end a lot of iterations of Zopfli delivers the best result. With that, I got the image down to 591 kB.

I tried zopflipng [1] with the very expensive option suggested from the usage and got 2,493 bytes (original 2,740 bytes, nowhere practical as it took 3 minutes) so you don't have to sacrifice the palette, though I'm not sure if 16 or even 4 color palette will significantly alter the visual.

[1] https://github.com/google/zopfli