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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.
In 2019, libjpeg-turbo became the ISO and ITU endorsed reference implementation for the JPEG format. [14] In April 2024, Google introduced Jpegli, a new JPEG coding library that offers enhanced capabilities and a 35% compression ratio improvement at high quality compression settings, while the coding speed is comparable with MozJPEG. [15]
Continuously varied JPEG compression (between Q=100 and Q=1) for an abdominal CT scan. JPEG (/ ˈ dʒ eɪ p ɛ ɡ / JAY-peg, short for Joint Photographic Experts Group and sometimes retroactively referred to as JPEG 1) [2] [3] is a commonly used method of lossy compression for digital images, particularly for those images produced by digital photography.
The JPEG filename extension is JPG or JPEG. Nearly every digital camera can save images in the JPEG format, which supports eight-bit grayscale images and 24-bit color images (eight bits each for red, green, and blue). JPEG applies lossy compression to images, which can result in a significant reduction of the file size.
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]
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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