块LZSS压缩算法

Wei-ling Chang, Xiao-chun Yun, Binxing Fang, Shupeng Wang
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引用次数: 2

摘要

主流的压缩算法,如LZ、Huffman、PPM等,近年来得到了广泛的研究。然而,对这些算法中的块算法的关注却很少。因此,本研究的目的是研究阻断LZSS。我们研究了块LZSS的压缩比与索引值或长度的关系。我们发现比特长度对LZSS块的压缩性能影响不大,而索引比特对压缩比有显著影响。实验结果表明,为了从LZSS块中获得更好的效率,一个大于32KiB的中等大小的块可能是最优的,并且最优的块大小与文件类型无关。我们还研究了影响最佳块大小的因素。我们使用平均块标准差(MBS)和参考的局部性来衡量压缩比。我们发现,良好的数据局部性意味着数据分布的大偏差,数据分布偏差或MBS越大,压缩比越好。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The Block LZSS Compression Algorithm
The mainstream compression algorithms, such as LZ, Huffman, PPM etc., have been extensively studied in recent years. However, rather less attention has been paid to the block algorithm of those algorithms. The aim of this study was therefore to investigate the block LZSS. We studied the relationship between the compression ratio of block LZSS and the value of index or length. We found that the bit of length has little effect on the compression performance of block LZSS, and the bit of index has a significant effect on the compression ratio. Results of the experiment show that to obtain better efficiency from block LZSS, a moderate sized block which is greater than 32KiB, may be optimal, and the optimal block size does not depend on file types. We also investigated factors which affect the optimal block size. We use the mean block standard deviation (MBS) and locality of reference to measure the compression ratio. we found that good data locality implies a large skew in the data distribution, and the greater data distribution skew or the MBS, the better the compression ratio.
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