14 Facts About Huffman coding

1.

In computer science and information theory, a Huffman coding code is a particular type of optimal prefix code that is commonly used for lossless data compression.

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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 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 uses a specific method for choosing the representation for each symbol, resulting in a prefix code .

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5.

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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6.

Once the Huffman coding tree has been generated, it is traversed to generate a dictionary which maps the symbols to binary codes as follows:.

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7.

However, Huffman coding is usually faster and arithmetic coding was historically a subject of some concern over patent issues.

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8.

Huffman 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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9.

The worst case for Huffman coding can happen when the probability of the most likely symbol far exceeds 2 = 0.

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10.

However, blocking arbitrarily large groups of symbols is impractical, as the complexity of a Huffman coding 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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11.

However, run-length Huffman coding is not as adaptable to as many input types as other compression technologies.

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12.

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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13.

Variation called adaptive Huffman 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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14.

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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