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  2. Lempel–Ziv–Oberhumer - Wikipedia

    en.wikipedia.org/wiki/Lempel–Ziv–Oberhumer

    Requires an additional buffer during compression (of size 8 kB or 64 kB, depending on compression level) Requires no additional memory for decompression other than the source and destination buffers Allows the user to adjust the balance between compression ratio and compression speed, without affecting the speed of decompression

  3. Data compression ratio - Wikipedia

    en.wikipedia.org/wiki/Data_compression_ratio

    Lossless compression of digitized data such as video, digitized film, and audio preserves all the information, but it does not generally achieve compression ratio much better than 2:1 because of the intrinsic entropy of the data. Compression algorithms which provide higher ratios either incur very large overheads or work only for specific data ...

  4. 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].

  5. LZ77 and LZ78 - Wikipedia

    en.wikipedia.org/wiki/LZ77_and_LZ78

    To spot matches, the encoder must keep track of some amount of the most recent data, such as the last 2 KB, 4 KB, or 32 KB. The structure in which this data is held is called a sliding window, which is why LZ77 is sometimes called sliding-window compression. The encoder needs to keep this data to look for matches, and the decoder needs to keep ...

  6. 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)

  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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