Introducing Iris for WebP
Today we're excited to announce the Iris project, our in-house image encoder. We've begun work on Iris's first codec, Iris-WebP: A WebP encoder that brings impressive gains over the reference encoder.
Why WebP?
WebP was introduced in 2010 with the goal of providing better compression for Web images. While it claimed to offer significant efficiency advantages over JPEG, in practice this wasn't always true. Its adoption was also slow due to an initial lack of widespread browser support and further lackluster support outside of the Web ecosystem. This led to WebP being perceived as a confusing addition to the Web.
Despite its reputation and unclear benefits, WebP has gained significant traction on the Web. It is available in over 95% of Web browsers, and large digital asset management companies serve billions of WebP images every day.
Iris-WebP is a WebP encoder tuned for the human eye. At the same encode time, it produces smaller files than the reference encoder at equal visual quality, and it narrows most of the gap between WebP and slower formats like AVIF.
Our Encoder
Our primary goals building Iris-WebP are speed, compression efficiency, and consistency. We want to consistently output high-quality results from our encoder quickly, and in doing so provide an implementation that delivers on WebP's initial quality promises without compromise.
In order to meet our goals, we've developed robust tooling to measure visual fidelity with SSIMULACRA2 and Butteraugli. Visual performance is paramount, and we work hard to ensure Iris-WebP isn't just overfit for metrics. Our featureset includes new compression techniques that came out of our own psychovisual research.
To learn more about Iris-WebP and how it may benefit your workflow, visit the Iris project page. Metrics were not ready when this post went up; they are now published on the Iris page, along with the cases where Iris loses.