Binary combinatorial coding
Vito Dai, Avideh Zakhor
Abstract
Vito Dai, Avideh Zakhor
Abstract
Summary form only given. A novel binary entropy code, called combinatorial coding (CC), is presented. The theoretical basis for CC has been described previously under the context of universal coding, enumerative coding, and minimum description length. The code described in these references works as follows: assume the source data are binary of length M, memoryless, and generated with an unknown parameter /spl theta/ (the probability that a "1" occurs). The compression efficiency, and encoding and decoding speed of CC against Huffman and arithmetic coding were tested. Over the entire test, CC achieved the compression efficiency of arithmetic coding, together with the coding speed of Huffman coding.
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Summary form only given. A novel binary entropy code, called combinatorial coding (CC), is presented. The theoretical basis for CC has been described previously under the context of universal coding, enumerative coding, and minimum description length. The code described in these references works as follows: assume the source data are binary of length M, memoryless, and generated with an unknown parameter /spl theta/ (the probability that a "1" occurs). The compression efficiency, and encoding and decoding speed of CC against Huffman and arithmetic coding were tested. Over the entire test, CC achieved the compression efficiency of arithmetic coding, together with the coding speed of Huffman coding.
Key concepts: Huffman coding, Tunstall coding, Variable-length code, Shannon–Fano coding, Arithmetic coding, Context-adaptive binary arithmetic coding, Context-adaptive variable-length coding, Entropy encoding