lossy

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Exploring Hidden JPEG Features

July 24, 2026 by 25 Comments

The lossy compression algorithm used by JPEG was useful for those on the early Internet not only because it enabled pictures to be shared easier, but because it allows a low-resolution version of the image to load first. This meant that users could make out the gist of an image before it finished downloading. This was a great feature for those on slow connections, but it hides some other capabilities of this image format as well.

Rather than effectively splitting up the image into chunks, each with successive amounts of detail, [maurycyz]’s project shows that this can be exploited to load more than one picture. The first is loaded into this lower-resolution area, with a second unrelated picture showing up once the higher-resolution information is available. Essentially this makes a one-way .gif of sorts. Though this method is only capable of loading about nine frames, which is not enough for much animation. Further limiting things is that there’s no way to encode timing data, so on fast computers with fast connections the animation could load faster than a user could see.

Still, it’s an interesting quirk of this older image standard, one which still is in widespread use today. And it’s also true that it’s hard to say in what ways various technologies will be used in the future. JPEG images have also been the subject of some artistic projects that might not have been possible without the JPEG standard itself, and even as other formats have tried to supplant it, it still maintains its firm grip on the images on the Internet. More JPEG, please!

Your Text Needs More JPEG

March 19, 2024 by 22 Comments

We’ve all been victims of bad memes on the Internet, but they’re not all just bad jokes gone wrong. Some are simply bad as a result of being copies-of-copies, as each reposter adds another layer of compression to an already lossy image format like JPEG. Compression can certainly be a benefit in areas like images and videos, but [Michal] had a bit of a fever dream imagining this process applied to text. Rather than let the idea escape, he built the Lossifizer to add JPEG-like compression to text.

JPEG compression uses a system similar to the fast Fourier transform (FFT) called the discrete cosine transform (DCT) to reduce the amount of data in an image by essentially removing some frequency information. The data lost is often not noticeable to the human eye, at least until it gets out of hand. [Michal]’s system performs the same transform on text instead, with a slider to control the “amount of JPEG” in the output text. The code for this script uses a “perceptual” character map, clustering similarly-looking and similarly-sounding characters next to each other, resembling “leet speak” from days of yore, although at high enough compression this quickly gets out of hand.

One of the quirks that [Michal] discovered is that certain AI chat bots have a much less difficult time interpreting this JPEG-ified text than a human probably would have, which provides a bit of insight into how some of these algorithms might be functioning under the hood. For some more insight into how JPEG actually works on images, we posted about a deep dive into the image format a while back.