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  2. Huffman coding - Wikipedia

    en.wikipedia.org/wiki/Huffman_coding

    Huffman tree generated from the exact frequencies of the text "this is an example of a huffman tree". Encoding the sentence with this code requires 135 (or 147) bits, as opposed to 288 (or 180) bits if 36 characters of 8 (or 5) bits were used (This assumes that the code tree structure is known to the decoder and thus does not need to be counted as part of the transmitted information).

  3. Canonical Huffman code - Wikipedia

    en.wikipedia.org/wiki/Canonical_Huffman_code

    The normal Huffman coding algorithm assigns a variable length code to every symbol in the alphabet. More frequently used symbols will be assigned a shorter code. For example, suppose we have the following non-canonical codebook: A = 11 B = 0 C = 101 D = 100 Here the letter A has been assigned 2 bits, B has 1 bit, and C and D both have 3 bits.

  4. File:Huffman coding example.svg - Wikipedia

    en.wikipedia.org/.../File:Huffman_coding_example.svg

    The picture is an example of Huffman coding. Colors make it clearer, but they are not necessary to understand it (according to Wikipedia's guidelines): probability is shown in red, binary code is shown in blue inside a yellow frame. For a more detailed description see below (I couldn't insert a table here). Date: 18 May 2007: Source: self-made

  5. Greedy algorithm - Wikipedia

    en.wikipedia.org/wiki/Greedy_algorithm

    Examples of such greedy algorithms are Kruskal's algorithm and Prim's algorithm for finding minimum spanning trees and the algorithm for finding optimum Huffman trees. Greedy algorithms appear in the network routing as well. Using greedy routing, a message is forwarded to the neighbouring node which is "closest" to the destination.

  6. Adaptive Huffman coding - Wikipedia

    en.wikipedia.org/wiki/Adaptive_Huffman_coding

    It is an online coding technique based on Huffman coding. Having no initial knowledge of occurrence frequencies, it permits dynamically adjusting the Huffman's tree as data are being transmitted. In a FGK Huffman tree, a special external node, called 0-node, is used to identify a newly coming character. That is, whenever new data is encountered ...

  7. Deflate - Wikipedia

    en.wikipedia.org/wiki/DEFLATE

    As an alternative to including the tree representation, the "static tree" option provides standard fixed Huffman trees. The compressed size using the static trees can be computed using the same statistics (the number of times each symbol appears) as are used to generate the dynamic trees, so it is easy for a compressor to choose whichever is ...

  8. 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 ...

  9. Talk:Canonical Huffman code - Wikipedia

    en.wikipedia.org/wiki/Talk:Canonical_Huffman_code

    But look at the canonical code book that we generated in the example: By following these three rules, the canonical version of the code book produced will be: B = 0 A = 10 C = 110 D = 111 But "the symbols are in sequential alphabetical order" does not hold. We could reorder them, but "that a later code will always be higher in value" would not ...