For memory constrained high-order entropy coding, (i) the number of Huffman tables and (ii) the size of each Huffman table have to be appropriately reduced. Recently, we developed a Huffman table sharing and a memory allocation methods, each of which efficiently reduces either (i) or (ii) to meet the given memory constraint while keeping the increase in average bitrate as small as possible. However, given a memory constraint, the Huffman table sharing and the memory allocation methods have to be employed at the same time to achieve the better result. This paper presents several efficient schemes for combining the two methods along with simulation results.
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