A Method for Urban Traffic Data Compression Based on Wavelet-PCA

Abstract

Due to limitation of storage space and cost, the massive amount of urban detected traffic data becomes a great burden. How to efficiently reduce these data and store them becomes more and more urgent. In this paper, an effective method for urban traffic data compression based on Wavelet-PCA is proposed. After preprocessing, the dataset is decomposed using wavelet and then multi-scale PCA is applied to reduce them to different dimensions. Simulation results prove that this method can greatly compress original data at the cost of acceptable recovery error and outperforms conventional PCA. Finally, we develop a prototype system specifically for urban traffic data compression using Visual C#.NET and Matlab.