Probability estimation in arithmetic and adaptive-Huffman entropy coders
Entropy coders, such as Huffman and arithmetic coders, achieve compression by exploiting nonuniformity in the probabilities under which a random variable to be coded takes on its possible values. Practical realizations generally require running adaptive estimates of these probabilities. An analysis...
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| Veröffentlicht in: | IEEE transactions on image processing 1995-03, Vol.4 (3), p.237-246 |
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| container_title | IEEE transactions on image processing |
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| creator | Duttweiler, D.L. Chamzas, C. |
| description | Entropy coders, such as Huffman and arithmetic coders, achieve compression by exploiting nonuniformity in the probabilities under which a random variable to be coded takes on its possible values. Practical realizations generally require running adaptive estimates of these probabilities. An analysis of the relationship between estimation quality and the resulting coding efficiency suggests a particular scheme, dubbed scaled-count, for obtaining such estimates. It can optimally balance estimation accuracy against a need for rapid response to changing underlying statistics. When the symbols being coded are from a binary alphabet, simple hardware and software implementations requiring almost no computation are possible. A scaled-count adaptive probability estimator of the type described in this paper is used in the arithmetic coder of the JBIG and JPEG image coding standards.< > |
| doi_str_mv | 10.1109/83.366473 |
| format | Article |
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| ispartof | IEEE transactions on image processing, 1995-03, Vol.4 (3), p.237-246 |
| issn | 1057-7149 1941-0042 |
| language | eng |
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| source | IEEE Electronic Library (IEL) |
| subjects | Applied sciences Arithmetic Coding, codes Decoding Entropy coding Exact sciences and technology Hardware Image coding Information, signal and communications theory Probability Random variables Signal and communications theory Standards development Statistics Telecommunications and information theory Transform coding |
| title | Probability estimation in arithmetic and adaptive-Huffman entropy coders |
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