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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.
Typically, compressions using lossless operation mode can achieve around 2:1 compression ratio for color images. [5] This mode is quite popular in the medical imaging field, and defined as an option in DNG standard, but otherwise it is not very widely used because of complexity of doing arithmetics on 10, 12, or 14bpp values on typical embedded 32-bit processor and a little resulting gain in ...
The most widely used lossy compression algorithm is the discrete cosine transform (DCT), first published by Nasir Ahmed, T. Natarajan and K. R. Rao in 1974. Lossy compression is most commonly used to compress multimedia data (audio, video, and images), especially in applications such as streaming media and internet telephony. By contrast ...
Group 4 compression is available in many proprietary image file formats as well as standardized formats such as TIFF, CALS, CIT (Intergraph Raster Type 24) and the PDF document format. G4 offers a small improvement over G3-2D by removing the end-of-line (EOL) codes.
Hamilton, Eric: JPEG File Interchange Format, Version 1.02 (PDF, 0.02 MB) 1 September 1992; Recommendation ITU-T T.871: Information technology – Digital compression and coding of continuous-tone still images: JPEG File Interchange Format (JFIF) (PDF and Microsoft Word, 0.2 MB) Approved 14 May 2011; posted 11 September 2012
Thus, a representation that compresses the storage size of a file from 10 MB to 2 MB yields a space saving of 1 - 2/10 = 0.8, often notated as a percentage, 80%. For signals of indefinite size, such as streaming audio and video, the compression ratio is defined in terms of uncompressed and compressed data rates instead of data sizes:
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