ΔRLE

IF 0.3 Q4 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Journal of Information and Organizational Sciences Pub Date : 2021-06-15 DOI:10.31341/jios.45.1.15
Branslav Mados, Z. Bilanová, J. Hurtuk
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引用次数: 0

摘要

与原始未压缩数据相比,无损数据压缩算法可以使用统计冗余来表示使用较少位数的数据。就其原理和软件实现以及时间和空间复杂性而言,运行长度编码(RLE)是最简单的无损压缩算法之一。如果将此原则应用于原始未压缩数据的单个比特而不考虑字节边界,则这种方法称为位级游程编码。本文提出的用于无损数据压缩的轻量级算法优化了比特级RLE数据压缩,使用重复数据块的特殊编码,并在必要时将其与增量数据转换或原始形式的数据表示相结合,与传统的比特级RLE方法相比,旨在提高压缩效率。与经典的位级RLE方法相比,本文提出的算法的优点是具有较低的时间和内存消耗,这是RLE的基本特征,同时压缩比也有所提高。
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ΔRLE
Lossless data compression algorithms can use statistical redundancy to represent data using a fewer number of bits in comparison to the original uncompressed data. Run-Length Encoding (RLE) is one of the simplest lossless compression algorithms in terms of understanding its principles and software implementation, as well as in terms of temporal and spatial complexity. If this principle is applied to individual bits of original uncompressed data without respecting the byte boundaries, this approach is referred to as bit-level Run-Length Encoding. Lightweight algorithm for lossless data compression proposed in this paper optimizes bit-level RLE data compression, uses special encoding of repeating data blocks, and, if necessary, combines it with delta data transformation or representation of data in its original form intending to increase compression efficiency compared to a conventional bit-level RLE approach. The advantage of the algorithm proposed in this paper is in its low time and memory consumption which are basic features of RLE, along with the simultaneous increase of compression ratio, compared to the classical bit-level RLE approach.
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来源期刊
Journal of Information and Organizational Sciences
Journal of Information and Organizational Sciences COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS-
CiteScore
1.10
自引率
0.00%
发文量
14
审稿时长
12 weeks
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