一种实时数据有损压缩的优化算法

2010 IEEE International Conference on Intelligent Computing and Intelligent Systems Pub Date : 2010-12-06 DOI:10.1109/ICICISYS.2010.5658770

Gang Chen, Li Li

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引用次数: 10

摘要

swing Door趋势算法和Douglas-Peucker算法都是主要的有损压缩算法。前者广泛应用于工业实时数据库软件中，而后者则多用于空间数据处理。本文首先对这两种算法进行比较，总结其优缺点。然后，以“搜索最远可行点”为策略，提出了一种优化的实时数据有损压缩算法及其在一定约束条件下的改进算法。实验结果表明，新算法在压缩率、总误差和效率方面都优于传统的swing Door趋势算法和Douglas-Peucker算法。

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An optimized algorithm for lossy compression of real-time data

The Swinging Door Trending algorithm and the Douglas-Peucker algorithm are both staple lossy compression algorithms. The former one is widely used in real-time database software of industry, while the latter one is more popular for spatial data processing. In this paper, these two algorithms are compared first to summarize their advantages and disadvantages. And then, an optimized lossy compression algorithm for real-time data as well as a variant of it under certain constraints is proposed with the strategy “searching the farthest feasible point”. The experimental results show that the new algorithm is better than the conventional Swinging Door Trending algorithm and Douglas-Peucker algorithm at compression rate, overall error, and efficiency.

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来源期刊

2010 IEEE International Conference on Intelligent Computing and Intelligent Systems

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