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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.
JPEG-LS was developed with the aim of providing a low-complexity lossless and near-lossless image compression standard that could offer better compression efficiency than lossless JPEG. It was developed because at the time, the Huffman coding -based JPEG lossless standard and other standards were limited in their compression performance.
This is an accepted version of this page This is the latest accepted revision, reviewed on 31 December 2024. Lossy compression method for reducing the size of digital images For other uses, see JPEG (disambiguation). "JPG" and "Jpg" redirect here. For other uses, see JPG (disambiguation). JPEG A photo of a European wildcat with the compression rate, and associated losses, decreasing from left ...
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.
Quantization, involved in image processing, is a lossy compression technique achieved by compressing a range of values to a single quantum (discrete) value. When the number of discrete symbols in a given stream is reduced, the stream becomes more compressible.
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]