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  2. Shannon–Fano coding - Wikipedia

    en.wikipedia.org/wiki/ShannonFano_coding

    Unfortunately, ShannonFano coding does not always produce optimal prefix codes; the set of probabilities {0.35, 0.17, 0.17, 0.16, 0.15} is an example of one that will be assigned non-optimal codes by ShannonFano coding. Fano's version of ShannonFano coding is used in the IMPLODE compression method, which is part of the ZIP file format ...

  3. Shannon coding - Wikipedia

    en.wikipedia.org/wiki/Shannon_coding

    ShannonFano coding methods gave rise to the field of information theory and without its contributions, the world would not have any of the many successors; for example Huffman coding, or arithmetic coding.

  4. Shannon–Fano–Elias coding - Wikipedia

    en.wikipedia.org/wiki/ShannonFano–Elias_coding

    ShannonFano–Elias coding produces a binary prefix code, allowing for direct decoding. Let bcode(x) be the rational number formed by adding a decimal point before a binary code. For example, if code(C) = 1010 then bcode(C) = 0.1010. For all x, if no y exists such that

  5. Huffman coding - Wikipedia

    en.wikipedia.org/wiki/Huffman_coding

    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".

  6. Entropy coding - Wikipedia

    en.wikipedia.org/wiki/Entropy_coding

    More precisely, the source coding theorem states that for any source distribution, the expected code length satisfies ⁡ [(())] ⁡ [⁡ (())], where is the number of symbols in a code word, is the coding function, is the number of symbols used to make output codes and is the probability of the source symbol. An entropy coding attempts to ...

  7. Data compression - Wikipedia

    en.wikipedia.org/wiki/Data_compression

    Entropy coding originated in the 1940s with the introduction of ShannonFano coding, [31] the basis for Huffman coding which was developed in 1950. [32] Transform coding dates back to the late 1960s, with the introduction of fast Fourier transform (FFT) coding in 1968 and the Hadamard transform in 1969. [33]

  8. LZ77 and LZ78 - Wikipedia

    en.wikipedia.org/wiki/LZ77_and_LZ78

    Then as the search pointer proceeds past the search window and forward, as far as the run pattern repeats in the input, the search and input pointers will be in sync and match characters until the run pattern is interrupted. Then L characters have been matched in total, L > D, and the code is [D, L, c]. Upon decoding [D, L, c], again, D = L R.

  9. Modified Huffman coding - Wikipedia

    en.wikipedia.org/wiki/Modified_Huffman_coding

    Modified Huffman coding is used in fax machines to encode black-on-white images . It combines the variable-length codes of Huffman coding with the coding of repetitive data in run-length encoding . The basic Huffman coding provides a way to compress files with much repeating data, like a file containing text, where the alphabet letters are the ...