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  2. Smallpdf.com - Wikipedia

    en.wikipedia.org/wiki/Smallpdf.com

    Smallpdf is a Swiss online web-based PDF software, founded in 2013. [2] It offers free version with limited features to compress, convert and edit PDF documents. [3] And its paid version offers advanced features like OCR, compress, and more [4].

  3. Calgary corpus - Wikipedia

    en.wikipedia.org/wiki/Calgary_Corpus

    This method was used in a benchmark in the online book Data Compression Explained by Matt Mahoney. [5] The table below shows the compressed sizes of the 14 file Calgary corpus using both methods for some popular compression programs. Options, when used, select best compression. For a more complete list, see the above benchmarks.

  4. Data compression ratio - Wikipedia

    en.wikipedia.org/wiki/Data_compression_ratio

    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:

  5. Data compression - Wikipedia

    en.wikipedia.org/wiki/Data_compression

    Introduction to Compression Theory (PDF), Wiley, archived (PDF) from the original on 2007-09-28; EBU subjective listening tests on low-bitrate audio codecs; Audio Archiving Guide: Music Formats (Guide for helping a user pick out the right codec) MPEG 1&2 video compression intro (pdf format) at the Wayback Machine (archived September 28, 2007)

  6. 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 such as tar for tasks such as handling multiple files, and other tools for encryption, and archive splitting.

  7. Lossy compression - Wikipedia

    en.wikipedia.org/wiki/Lossy_compression

    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 ...

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