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  2. Smallpdf.com - Wikipedia

    en.wikipedia.org/wiki/Smallpdf.com

    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]

  3. zstd - Wikipedia

    en.wikipedia.org/wiki/Zstd

    Data compression. License. BSD-3-Clause or GPL-2.0-or-later (dual-licensed) Website. facebook.github.io /zstd /. Zstandard is a lossless data compression algorithm developed by Yann Collet at Facebook. Zstd is the corresponding reference implementation in C, released as open-source software on 31 August 2016. [3][4]

  4. Lossless compression - Wikipedia

    en.wikipedia.org/wiki/Lossless_compression

    Lossless compression. 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 ...

  5. bzip2 - Wikipedia

    en.wikipedia.org/wiki/Bzip2

    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.

  6. Data compression ratio - Wikipedia

    en.wikipedia.org/wiki/Data_compression_ratio

    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.

  7. Data compression - Wikipedia

    en.wikipedia.org/wiki/Data_compression

    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.