基于二维离散小波变换的智能交通系统数据去噪声压缩

Traffic Data Denoising Compression for Intelligent Traffic Systems Based on 2-D Discrete Wavelet Transformation

研究了基于二维离散小波变换的交通数据压缩与解压缩技术,建立了交通数据的空—时模型,所提出的二维离散小波变换算法利用交通数据的二维空—时特征,去除传感器噪声,得到良好的数据压缩结果,压缩比为20～40.同时给出了基于二维离散小波变换的交通数据压缩编码原理.采用北京市三环路检测断面测得的交通数据,验证所提出的算法是有效的.

The traffic data denoising compression and decompression based on 2_D discrete wavelet transformation technology have been studied, and the pace_time model of traffic data has been established. The algorithm of 2_D discrete wavelet transformation provided by the paper utilizes the two_dimensional space_time characteristics of the traffic data, removed sensor noise and obtained good compression results, and the compression rate is 20～40. The principle of traffic data compression based on wavelet transformation coding is introduced. The traffic data from a measured section of Beijing's third_wreath road has been adopted to verify the algorithm presented in the paper to be effective.