Method of Vector Data Compression Based on Sector Screening
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摘要: 针对具有预测功能的矢量数据压缩方法效率低下的问题,提出一种基于扇形筛选法的矢量数据压缩方法。在预测区域内利用扇形筛选法,能显著减少待选点,从而提高压缩效率。实验结果证明,该方法的效率与改进前方法相比提升了30%~40%。此外,与传统的Douglas-Peucker算法相比,该方法在相同阈值下可以得到更大的压缩比,且在较小阈值下具有更高的计算效率。
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关键词:
- 矢量地图数据 /
- 时间效率 /
- 预测算法 /
- 扇形筛选法 /
- Douglas-Peucker算法
Abstract: The compression of vector data is very important for reducing the space needed for data storage and improving the efficiency of data transmission and processing in WebGIS. This paper focuses on the time efficiency of vector data compression with prediction functions and proposes a vector data compression method based on sector screening that significantly reduces the quantity of candidate vertices in prediction areas to improve time efficiency. Experimental results show that the time efficiency improved by 30%-40%. Our method was compared with the conventional Douglas-Peucker method. The tests confirmed that our method can achieve a larger compression ratio when using the same compression threshold value, while obtain greater time efficiency with relatively small threshold values. -
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