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The idea came from the need for their families to compress and send large documents via email. [4] The initial version of the site featured a standalone PDF compression tool. [5] Since then, the online platform has introduced over 16 PDF tools to convert, compress and edit PDF documents. [6]
The Weissman score is a performance metric for lossless compression applications. It was developed by Tsachy Weissman, a professor at Stanford University, and Vinith Misra, a graduate student, at the request of producers for HBO's television series Silicon Valley, a television show about a fictional tech start-up working on a data compression algorithm.
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 ...
Definition. 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.
In computer science and information theory, a Huffman code is a particular type of optimal prefix code that is commonly used for lossless data compression.The process of finding or using such a code is Huffman coding, an algorithm developed by David A. Huffman while he was a Sc.D. student at MIT, and published in the 1952 paper "A Method for the Construction of Minimum-Redundancy Codes".
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 [1] and was first used in the 7z format of the 7-Zip archiver. This algorithm uses a dictionary compression scheme somewhat ...
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