"That's why we're excited to announce Guetzli, a new open source algorithm that creates high quality JPEG images with file sizes 35% smaller than now available methods, enabling webmasters to create webpages that can load faster and use even less data".
"Butteraugli takes into account. properties of vision that most JPEG encoders do not make use of", Google researchers said in a Guetzli research paper (PDF). In fact, in experiments comparing compressed images, human raters preferred the Guetzli-produced images over those created by libjpeg, even when the latter's images were a larger file size.
Images pushed through the Guetzli encoder are still available in a regular JPEG format, making them compatible with just about every application and browser now on the market. It is an open-sourced algorithm can also be used in an alternative way, that is, you can also use it for increasing the image quality while keeping the same file size.
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The encoding process for a JPEG can be broken down into six distinct parts: color space transformation, downsampling, block splitting, discrete cosine transform, quantization, and entropy coding. The algorithm used by the company allows it to compress JPEGs by up to 35% more than now available methods. It serves up images that look great, but their file size is 35 percent smaller.
JPEG is a lossy compression method for images, which allows a tradeoff to occur between file size and the final quality of the images.
However, it's worth noting that Guetzli is slower than other options out there. If you want to try it, Google released Guetzli for free as open-source software. There is no debating the fact that images from a majority of the size of any web page, thus, shrinking the size of these filed will result in improved browsing experiences. That's a big deal because right now, many web-based image programs (and even stand alone image processing apps) use the libjpeg encoder because it is free and tends to do a good enough job.
The downside to this methodology is that compression takes significantly longer than now available methods.