PPM:向实用性迈出一步

D. A. Shkarin
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引用次数: 182

摘要

PPM是一种利用d阶马尔可夫源模型的最有前途的无损数据压缩算法,其本质是在上下文树的一个内部节点上编码一个新的(在给定的上下文中)符号;一个特殊转义符号序列用于描述该节点。在现实中,大多数符号都是在内部节点中编码的,马尔可夫模型变得相当传统。尽管PPM算法与其他算法相比取得了最好的结果,但由于其较高的计算复杂度,在实际应用中很少使用。本文研究了基于LZ77、LZ78和BWT算法的PPM算法的实现,其复杂度可与广泛应用的压缩方案相媲美。这一方案是由Shkarin提出的(见《信息传输问题》,第34卷,第5期)。并将其命名为带信息继承的PPM (PPMII)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
PPM: one step to practicality
PPM is one of the most promising lossless data compression algorithms using Markov source model of order D. Its main essence is the coding of a new (in the given context) symbol in one of inner nodes of the context tree; a sequence of the special escape symbols is used to describe this node. In reality, the majority of symbols is encoded in inner nodes and the Markov model becomes rather conventional. In spite of the fact that the PPM algorithm achieves the best results in comparison with others, it is used rarely in practical applications due to its high computational complexity. This paper is devoted to the PPM algorithm implementation that has a complexity comparable with widespread practical compression schemes based on LZ77, LZ78 and BWT algorithms. This scheme has been proposed by Shkarin (see Problems of Information Transmission, vol.34, no.3, p.44-54, 2001) and named PPM with information inheritance (PPMII).
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