块排序压缩的上下文树

N. Larsson
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引用次数: 52

摘要

Burrows-Wheeler(1994)变换(BWT)和块排序压缩与PPM的上下文树密切相关。通常将BWT仅仅视为一种排列的方法不能充分利用这种关系。我们表明,通过取相应后缀树的一个子集,识别利用其结构中的中心问题,并跟踪上下文树对常见移到前面方案的影响,可以有效地生成BWT的显式上下文树。我们通过实验获得了使用构造树的压缩限制,并且,作为利用完整上下文树的尝试,提出了一种压缩方案,将上下文树明确地表示为压缩数据的一部分。我们认为有意识地处理上下文树应该能够实现PPM的全部压缩性能,同时保持BWT的计算效率。因此,具有显式上下文树的BWT是强大的通用压缩的有力候选,特别是对于大型数据文件。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The context trees of block sorting compression
The Burrows-Wheeler (1994) transform (BWT) and block sorting compression are closely related to the context trees of PPM. The usual approach of treating BWT as merely a permutation is not able to fully exploit this relation. We show that an explicit context tree for BWT can be efficiently generated by taking a subset of the corresponding suffix tree, identifying the central problems in exploiting its structure, and tracing the influence of the context tree on the common move-to-front schemes. We experimentally obtain limits for compression using the constructed trees, and, as an attempt at utilizing the full context tree, present a compression scheme that represents the context tree explicitly as part of the compressed data. We argue that a conscious treatment of the context tree should be able to achieve the full compression performance of PPM while maintaining the computational efficiency of BWT. Thus, BWT with explicit context trees is a strong candidate for powerful general compression, especially for large data files.
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