Low-Complexity Compression with Random Access

Srikanth Kamparaju, Shaik Mastan, Shashank Vatedka
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引用次数: 1

Abstract

We investigate the problem of variable-length compression with random access for stationary and ergodic sources, wherein short substrings of the raw file can be extracted from the compressed file without decompressing the entire file. It is possible to design compressors for sequences of length n that achieve compression rates close to the entropy rate of the source, and still be able to extract individual source symbols in time $\theta(1)$ under the word-RAM model. In this article, we analyze a simple well-known approach used for compression with random access. We theoretically show that this is suboptimal, and design two simple compressors that simultaneously achieve entropy rate and constant-time random access. We then propose dictionary compression as a means to further improve performance, and experimentally validate this on various datasets.
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随机访问的低复杂度压缩
我们研究了随机访问固定和遍历源的变长压缩问题,其中原始文件的短子字符串可以从压缩文件中提取,而无需解压缩整个文件。有可能为长度为n的序列设计压缩器,使其压缩率接近源的熵率,并且仍然能够在time $\theta(1)$中提取单个源符号。在本文中,我们将分析一种用于随机访问压缩的简单方法。我们从理论上证明这是次优的,并设计了两个简单的压缩器,同时实现熵率和恒定时间随机访问。然后,我们提出字典压缩作为进一步提高性能的一种手段,并在各种数据集上进行实验验证。
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