Google’s Guetzli JPEG Encoder Shrinks Sizes Up to 35% With Little Quality Loss

Google has announced that their new Guetzli JPEG encoder is an open source algorithm that is capable of shrinking JPEG file size up to 35% with very little quality degradation penalty compared to other methods. The new compression method is extremely useful for websites so that pages can load faster, especially if keeping the picture quality is extremely necessary such as in a photo or a promotional website.

The name Guetzli is derived from Swiss German, meaning cookie. It is essentially the JPEG equivalent of the Zopfli algorithm which produces smaller PNG files without needing to introduce a new format, and different than the techniques used in RNN-based image compression, RAISR, and WebP, which all need client and ecosystem changes to be internet-ready.

16×16 pixel synthetic example of a phone line hanging against a blue sky — traditionally a case where JPEG compression algorithms suffer from artifacts. Uncompressed original is on the left. Guetzli (on the right) shows less ringing artefacts than libjpeg (middle) and has a smaller file size.

Most of the image degredation happens at the quantization stage and that is what Guetzli targets. According to Google, Guetzli tackles this by “employing a search algorithm that tries to overcome the difference between the psychovisual modeling of JPEG’s format, and Guetzli’s psychovisual model, which approximates color perception and visual masking in a more thorough and detailed way than what is achievable by simpler color transforms and the discrete cosine transform.”

The downside, however, is that compression takes longer using Guetzli because of the search algorithms compared to other methods but the trade-off is worth it if the quality is maintained. Google has conducted blind tests in their labs that revealed many users preferred the compression of Guetzli over the usual libjpeg method, even when the libjpeg file sizes were much larger. This innovation has become critical with the increase of mobile web browsing and the need for more optimal compression methods. Google also hopes that this new method inspires others to look for other more efficient ways to compress media and further photo/video compression research.