Skeleton trees for the efficient decoding of huffman encoded texts

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A new data structure is investigated, which allows fast decoding of texts encoded by canonical Huffman codes. The storage requirements are much lower than for conventional Huffman trees, O(log2n) for trees of depth O(log n), and decoding is faster, because a part of the bit-comparisons necessary for the decoding maybe saved. Empirical results on large real-life distributions show a reduction of up to 50% and more in the number of bit operations. The basic idea is then generalized, yielding further savings.

Original languageEnglish
Pages (from-to)7-23
Number of pages17
JournalInformation Retrieval
Issue number1
StatePublished - 2000


  • Canonical huffman codes
  • Decoding © 2000 kluwer academic publishers
  • Huffman trees
  • Skeleton trees


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