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  2. Lossless compression - Wikipedia

    en.wikipedia.org/wiki/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 ]

  3. Data compression - Wikipedia

    en.wikipedia.org/wiki/Data_compression

    Data compression aims to reduce the size of data files, enhancing storage efficiency and speeding up data transmission. K-means clustering, an unsupervised machine learning algorithm, is employed to partition a dataset into a specified number of clusters, k, each represented by the centroid of its points.

  4. LZ77 and LZ78 - Wikipedia

    en.wikipedia.org/wiki/LZ77_and_LZ78

    In the implementation used for many games by Electronic Arts, [9] the size in bytes of a length–distance pair can be specified inside the first byte of the length–distance pair itself; depending on whether the first byte begins with a 0, 10, 110, or 111 (when read in big-endian bit orientation), the length of the entire length–distance ...

  5. 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:

  6. Brotli - Wikipedia

    en.wikipedia.org/wiki/Brotli

    Brotli is a lossless data compression algorithm developed by Google. It uses a combination of the general-purpose LZ77 lossless compression algorithm, Huffman coding and 2nd-order context modelling. Brotli is primarily used by web servers and content delivery networks to compress HTTP content, making internet websites

  7. Lossy compression - Wikipedia

    en.wikipedia.org/wiki/Lossy_compression

    Basic information theory says that there is an absolute limit in reducing the size of this data. When data is compressed, its entropy increases, and it cannot increase indefinitely. For example, a compressed ZIP file is smaller than its original, but repeatedly compressing the same file will not reduce the size to nothing. Most compression ...