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A novel approach to entropy coding is described that provides the coding efficiency and simple probability modeling capability of arithmetic coding at the complexity level of Huffman coding. The key element of the proposed approach is given by a partitioning of the unit interval into a small set of disjoint probability intervals for pipelining the coding process along the probability estimates of binary random variables. According to this partitioning, an input sequence of discrete source symbols with arbitrary alphabet sizes is mapped to a sequence of binary symbols and each of the binary symbols is assigned to one particular probability interval.
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