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JPEG XL beats AVIF for higher quality images, but AVIF will often outperform JPEG XL on low quality images in low-fidelity, high-appeal compression: low quality AVIF images will smooth out details and hide compression artifacts better, making them more visually appealing than JPEG XL images of the same size.
Image compression is a type of data compression applied to digital images, to reduce their cost for storage or transmission. Algorithms may take advantage of visual perception and the statistical properties of image data to provide superior results compared with generic data compression methods which are used for other digital data.
Besides uncompressed formats and lossless compression formats that can usually be interconverted without any loss of detail, there are compressed formats such as JPEG, which lose detail on nearly every compress. While a conversion from a compressed to an uncompressed format is in general without loss, this is not true the other way around.
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Jon Sneyers, one of the developers of FLIF, since combined it with ideas from various lossy compression formats to create a successor called the Free Universal Image Format (FUIF), which itself was combined with Google's PIK format to create JPEG XL. As a consequence, FLIF is no longer being developed. [1]
Lossless compression of digitized data such as video, digitized film, and audio preserves all the information, but it does not generally achieve compression ratio much better than 2:1 because of the intrinsic entropy of the data. Compression algorithms which provide higher ratios either incur very large overheads or work only for specific data ...