地球信息科学学报 ›› 2015, Vol. 17 ›› Issue (8): 883-888.doi: 10.3724/SP.J.1047.2015.00883

• •    下一篇

平均误差控制下的频率域矢量数据压缩方法

黄伟明(), 杨建宇*(), 岳彦利, 杜萌, 张超, 朱德海   

  1. 1. 中国农业大学信息与电气工程学院,北京 100083;2. 国土资源部农用地质量与监控重点实验室,北京 100035
  • 收稿日期:2015-01-14 修回日期:2015-02-19 出版日期:2015-08-10 发布日期:2015-08-05
  • 通讯作者: 杨建宇 E-mail:huangweim@hotmail.com;ycjyyang@cau.edu.cn
  • 作者简介:

    作者简介:黄伟明(1990-),男,山东济南人,硕士生,研究方向为地理信息系统。E-mail: huangweim@hotmail.com

  • 基金资助:
    国家自然科学基金项目(41171309)

Vector Data Compression of Frequency Domain Based on Tolerance of Average Error

HUANG Weiming(), YANG Jianyu*(), YUE Yanli, DU Meng, ZHANG Chao, ZHU Dehai   

  1. 1. College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China;2. Key Laboratory for Agriculture Land Quality, Monitoring and Control of the Ministry of Land and Resources, Beijing 100035, China
  • Received:2015-01-14 Revised:2015-02-19 Online:2015-08-10 Published:2015-08-05
  • Contact: YANG Jianyu E-mail:huangweim@hotmail.com;ycjyyang@cau.edu.cn
  • About author:

    *The author: SHEN Jingwei, E-mail:jingweigis@163.com

摘要:

矢量数据压缩对于受网络带宽限制的WebGIS有着重要意义,其可减少数据存储空间,提高网络传输与处理效率。传统的矢量数据压缩方法主要从空间关系的角度出发,根据原始矢量数据点之间的距离、角度等指标,判断如何对矢量线要素或面要素进行化简,略去冗余的端点。而本文则利用已在图像压缩领域被广泛应用的变换编码的频率域压缩技术,利用能实现能量保持的离散余弦变换和特殊的量化方法,以及无损熵编码,对矢量数据实现了能控制压缩后平均误差的有损压缩。该方法无需事先根据不同的误差限值设计量化表,且能处理指定过大平均误差限值时所出现的问题,有很强的适应能力。最后,使用C#实现了该方法,并验证了方法的可靠性,完成了方法的性能测试。实验结果表明,本文提出的矢量数据压缩方法能获得较大的压缩比,且能较好地保持原始矢量数据所具有的地理形态结构特征。

关键词: 矢量地图数据, WebGIS, 离散余弦变换, 平均误差, 空间数据压缩

Abstract:

With the constant enhancement of data acquisition capability, an increasing amount of spatial data is available to WebGIS. However, the efficiency of spatial data transmission cannot meet the current need for fast access to spatial data. In such a context, the compression of spatial data is important for reducing the space of data storage and improving the efficiency of data transmission and processing for WebGIS. Traditional methods of vector data compression are usually based on spatial relations, such as the distances or angles between different vertices, to determine which vertices are redundant. Whereas in the field of image compression, the method based on the techniques of transform coding (in frequency domain) is more frequently-used. This paper proposes a novel method of spatial vector data compression in frequency domain. This method is composed of several steps. To be specific, we transform the coordinate values of x and y to frequency domain coefficients respectively using Discrete Cosine Transform (DCT), and quantize these coefficients according to the relevant specific thresholds, which could restrict the average distortions (root-mean-square error, RMSE) of the reconstructed vector data. This quantizing method does not need quantization tables and is adaptive to large thresholds that often cause problems such as compressing a polygon or line feature into a point or a polygon feature into a line. In the final stage of the proposed vector data compression method, the Huffman coding is used in a similar way to the corresponding part of JPEG standard. The proposed compression method was implemented by C#.NET and was applied to compress vector data to test its performance from the aspects of compression ratio and geometric shape distortion. The results of the tests show that the proposed method is a feasible solution for vector data compression. It is flexible in terms of restricting distortion, and it can achieve large compression ratios as well as retain the main geographic shape´s characteristics which are derived from the original vector data, within the compressed vector data.

Key words: vector data map, WebGIS, DCT, average error, spatial data compression