Design and analysis of dynamic Huffman codes
Journal of the ACM (JACM)
Text compression
Elements of information theory
Elements of information theory
Introduction to coding and information theory
Introduction to coding and information theory
Handbook of formal languages, vol. 1
JPEG Still Image Data Compression Standard
JPEG Still Image Data Compression Standard
Theory of Codes
Optimal Maximal Encoding Different from Huffman Encoding
ITCC '01 Proceedings of the International Conference on Information Technology: Coding and Computing
IEEE Transactions on Information Theory
Existence of optimal prefix codes for infinite source alphabets
IEEE Transactions on Information Theory
Improved Huffman code tables for JPEG's encoder
IEEE Transactions on Circuits and Systems for Video Technology
Improving Information Retrieval System Security via an Optimal Maximal Coding Scheme
EurAsia-ICT '02 Proceedings of the First EurAsian Conference on Information and Communication Technology
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Novel coding schemes are introduced and relationships between optimal codes and Huffman codes are discussed. It is shown that, for finite source alphabets, the Huffman coding is the optimal coding, and conversely the optimal coding needs not to be the Huffman coding. It is also proven that there always exists the optimal coding for infinite source alphabets. We show that for every random variable with a countable infinite set of outcomes and finite entropy there exists an optimal code constructed from optimal codes for truncated versions of the random variable. And the average code word lengths of any sequence of optimal codes for the truncated versions converge to that of the optimal code. Furthermore, a case study of data compression is given. Comparing with the Huffman coding, the optimal coding is a more flexible compression method used not only for statistical modeling but also for dictionary schemes.