智能交通系统中基于二维DCT算法的空时信号处理
首发时间:2004-05-31
摘要:在传统的智能交通系统数据处理中,其方法主要集中于原始数据在时域的统计特性,因此不能有效地消除观测数据中不需要的干扰,如空时感应器噪声。智能交通数据的处理之所以比较困难主要是由于以下的三个原因:1 数据处理量非常大;2 数据具有空时特性;3 数据的异质性。如果对含有异质成分的交通数据不能进行有效的压缩的去噪,那么智能交通系统将很难用于城市的交通控制。本文提出用二维离散余弦变换(2-D DCT)算法同时在时间域和空间域对交通数据进行处理,实验结果表明该算法能有效压缩智能交通系统中的实时数据,并能很好地消除数据中的噪声。
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The Space-Time Processing of Intelligent Traffic System (ITS) Data Based on the 2-D DCT
Abstract:The conventional data processing approaches concentrated on statistical nature of the raw data in time domain for Intelligent Traffic System (ITS), so they cannot effectively eliminated the undesired information, such as space-time sensor error and noise. The difficulty for ITS data processing lies on three hands: the data is abundant, the data is of space-time and the data is of heterogeneity in the ITS. If the abundant heterogeneity data cannot effectively be aggregated, the ITS will be difficult to put into effect for city traffic control. In this paper we introduce the 2-D (two-dimensional) Discrete Cosine Transform (DCT) to process the traffic data both in time domain and space domain. As shown in the paper, the space-time 2-D DCT can effectively compress the real-time heterogeneity data and eliminate the undesired information in the ITS.
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