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Data compression ratio is defined as the ratio between the uncompressed size and compressed size: [1][2][3][4][5] Thus, a representation that compresses a file's storage size from 10 MB to 2 MB has a compression ratio of 10/2 = 5, often notated as an explicit ratio, 5:1 (read "five" to "one"), or as an implicit ratio, 5/1.
Data compression. In information theory, data compression, source coding, [1] or bit-rate reduction is the process of encoding information using fewer bits than the original representation. [2] Any particular compression is either lossy or lossless. Lossless compression reduces bits by identifying and eliminating statistical redundancy.
File size. File size is a measure of how much data a computer file contains or, alternately, how much storage it consumes. Typically, file size is expressed in units of measurement based on the byte. By convention, file size units use either a metric prefix (as in megabyte and gigabyte) or a binary prefix (as in mebibyte and gibibyte).
bzip2 is a free and open-source file compression program that uses the Burrows–Wheeler algorithm. It only compresses single files and is not a file archiver. It relies on separate external utilities for tasks such as handling multiple files, encryption, and archive-splitting. bzip2 was initially released in 1996 by Julian Seward.
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A tar.gz is created by joining the files in tar and then compressing with gzip. In computing, solid compression is a method for data compression of multiple files, wherein all the uncompressed files are concatenated and treated as a single data block. Such an archive is called a solid archive. It is used natively in the 7z [1] and RAR [2 ...
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Image compression. 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 ...