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.
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12 Facts About Huffman code
2.
The process of finding or using such a code proceeds by means of Huffman coding, an algorithm developed by David A Huffman while he was a Sc.
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3.
However, although optimal among methods encoding symbols separately, Huffman code coding is not always optimal among all compression methods - it is replaced with arithmetic coding or asymmetric numeral systems if a better compression ratio is required.
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4.
Huffman coding is such a widespread method for creating prefix codes that the term "Huffman code" is widely used as a synonym for "prefix code" even when such a code is not produced by Huffman's algorithm.
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5.
Once the Huffman tree has been generated, it is traversed to generate a dictionary which maps the symbols to binary codes as follows:.
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6.
However, Huffman code coding is usually faster and arithmetic coding was historically a subject of some concern over patent issues.
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7.
Huffman code coding is optimal among all methods in any case where each input symbol is a known independent and identically distributed random variable having a probability that is dyadic.
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8.
However, blocking arbitrarily large groups of symbols is impractical, as the complexity of a Huffman code is linear in the number of possibilities to be encoded, a number that is exponential in the size of a block.
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9.
Many variations of Huffman coding exist, some of which use a Huffman-like algorithm, and others of which find optimal prefix codes .
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10.
Variation called adaptive Huffman code coding involves calculating the probabilities dynamically based on recent actual frequencies in the sequence of source symbols, and changing the coding tree structure to match the updated probability estimates.
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11.
Length-limited Huffman coding is a variant where the goal is still to achieve a minimum weighted path length, but there is an additional restriction that the length of each codeword must be less than a given constant.
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12.
The Huffman–Shannon–Fano code corresponding to the example is, which, having the same codeword lengths as the original solution, is optimal.
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