We believe thatĮvaluating compression algorithms based on theoretical and non-intuitive quantities is like gauging the success of your new cookie recipe by measuring how much the cookie deviates from a perfect circle. The key to this approach is figuring out what aspects of an image matter most to human viewers, that is, how much they actually care about the visual information that is thrown out. Because if indeed it does, then perhaps it's possible to use the descriptive power of human language to compress images more efficiently than the algorithms used today, which work with brightness and color information at the pixel level rather than attempting to understand the contents of the image. So, inspired by the aphorism, we decided to test whether it really takes about a thousand words to describe an image. In fact, a thousand digital words contain far fewer bits than any of the images we generate with our smartphones and sling around daily. We started our effort to improve image compression by considering the adage: 'a picture is worth a thousand words.' While that expression is intended to imply that a thousand words is a lot and an inefficient way to convey the information contained in a picture, to a computer, a thousand words isn't much data at all. So we decided to take a step back from the standard image compression tools, and see if there is a path to better compression that, to date, hasn't been widely traveled. But, as engineers, we are trained to ask if we can do better. Still, today's compressors provide pretty good savings in space with acceptable losses in quality. But when we push the compression envelope further, artifacts emerge, including blurring, blockiness, and staircase-like bands. JPEG files that we all have floating around on our hard drives and shared albums in the cloud-can reduce image sizes between 5 and 100 times.

State-of-the-art image compressors-like the ones resulting in the ubiquitous These compressors aim to preserve certain visual properties while glossing over others, determining what visual information can be thrown away without being noticeable. Computer algorithms are constantly making choices about what visual details matter, and, based on those choices, generating lower-quality images that take up less digital space.

Most users don't think about it, but every image posted to Facebook, Instagram or TikTok is compressed before it shows up on your feed or timeline. And we love to share our photos, so we end up storing them in multiple places. We live in an age in which it's cheap to take photos but will eventually be costly to store them en masse, as backup services set limits and begin charging for overages. Why would I bother to do that, you ask? I can just send the whole picture to the cloud and keep it forever. Now imagine which of those details you'd choose to keep if you only had enough storage space for one of those features, instead of the entire photo. What's in the picture that you care about most? Is it your friends who were present? Is it the food you were eating? Or is it the amazing sunset in the background that you didn't notice at the time you took the picture, but looks like a painting? Picture your favorite photograph, say, of an outdoor party.

Compress picture