一种改进的矢量数据压缩算法

Cheng Feixiang, Qi Jiandong, Zhao Ming
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引用次数: 2

摘要

矢量数据压缩在地形环境模拟、综合制图、GIS等领域的研究中发挥着重要作用。增加移动设备的存储容量,提高矢量数据的网络传输效率是一项非常重要的工作。针对这两类矢量数据压缩,本文分别提出了基于遗传算法的矢量数据压缩模型和基于动态规划算法的矢量数据压缩改进方法。前者通过对曲线上的节点进行二进制编码,以减少压缩后的节点数和误差为目标。此外,它还使用Douglas-Peucker算法来控制选项、变异和交叉的效率,最优解中值为1的基因对应于压缩后的曲线节点。后者构造一条条带,通过参考路径形成误差最小的搜索范围,该条带的宽度可以自行调整。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An Improved Algorithm of Vector Data Compression
Vector data compression plays an important role in the research of terrain environment simulation, comprehensive mapping, GIS etc. It is a very important work to increase the storage capacity of mobile devices and improve the network transmission efficiency of vector data. Based on the two types of the vector data compression, this article respectively proposed the vector data compression model based on genetic algorithm and the improved method of vector data compression based on dynamic programming algorithm. The former take the fewer nodes and error after the compression as the goal through the binary encoding to the nodes on the curve. Besides, it also uses the Douglas-Peucker algorithm to control the efficiency of the options, variations and cross, and the gene whose value is one in the optimal solution corresponds to the curve node after the compression. The latter constructed a strip to form a search range with a minimum error through a reference path, and the breadth of this strip can be adjustment itself.
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