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- W3023850908 abstract "This chapter concentrates on the construction of Huffman's codes and their efficiency. Universal coding techniques assume only a nonincreasing distribution. Coding is characterized by the distribution of symbols they are meant to code. Golomb coding assumes a geometrical distribution, whereas Fiala and Green assume a three-step even distribution. There are ways to deal with the situation where there is no direct relation between the symbol number and its frequency rank. A permutation function that maps the symbol numbers to their corresponding frequency ranks. This will effectively give a nonincreasing distribution and then one of the aforementioned codes could be used for coding. However, Huffman's codes are more general and assume that all probabilities are nonzero. Therefore, they are suitable for all distributions, including those that have no symbol number and probability, as in the case of text, where it moves from “a” to “z.” He was also the first to give an exact, optimal algorithm to code symbols from arbitrary distribution. His codes solve the problem of finding an optimal codebook for an arbitrary probability distribution of symbols. In memory-efficient algorithms, if we opt for a tree representation to maintain the Huffman code information in memory, the choices are a classical binary tree with three pointers and the other is heap-type storage. In conclusion, it is pointed that Huffman codes are rarely used as a sole means of compression." @default.
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- W3023850908 date "2003-01-01" @default.
- W3023850908 modified "2023-10-18" @default.
- W3023850908 title "Huffman Coding" @default.
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