Memory-constrained high-order entropy coding by Huffman table sharing and memory allocation

Seung Jun Lee, J. Song, ChoongWoong Lee
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Abstract

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.
基于Huffman表共享和内存分配的内存约束高阶熵编码
对于内存受限的高阶熵编码,(i)霍夫曼表的数量和(ii)每个霍夫曼表的大小必须适当减少。最近,我们开发了一种Huffman表共享和一种内存分配方法,每种方法都可以有效地减少(i)或(ii)以满足给定的内存约束,同时保持平均比特率的增长尽可能小。然而,在给定内存约束的情况下,为了获得更好的结果,必须同时使用Huffman表共享和内存分配方法。本文给出了两种方法结合的几种有效方案,并给出了仿真结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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