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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.
Lossless compression is a class of data compression that allows the original data to be perfectly reconstructed from the compressed data with no loss of information. Lossless compression is possible because most real-world data exhibits statistical redundancy. [1] By contrast, lossy compression permits reconstruction only of an approximation of ...
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).
Lempel–Ziv–Markov chain algorithm. The Lempel–Ziv–Markov chain algorithm (LZMA) is an algorithm used to perform lossless data compression. It has been under development since either 1996 or 1998 by Igor Pavlov [citation needed] and was first used in the 7z format of the 7-Zip archiver. This algorithm uses a dictionary compression scheme ...
The dictionary describes the properties of the image, and the stream contains the image data. (Less commonly, small raster images may be embedded directly in a page description as an inline image.) Images are typically filtered for compression purposes. Image filters supported in PDF include the following general-purpose filters:
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.
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