Research on Compression Method Based on Integer Wavelet Transform and SPIHT for Historical Data in Process Industry

Peng Jiang, Qingbo Huang, Yaguang Kong, Li Chai
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引用次数: 1

Abstract

To compress historical data in process industry and reduce data storage, a new compression method based on integer wavelet transform and SPIHT (set partitioning in hierarchical trees) was proposed. Wavelet coefficients and temporal orientation trees were obtained by utilizing integer wavelet transform to decompose the original data into five layers. Encoding the wavelet coefficient by SPIHT, the bit plane was exported. After encoding the bit plane by adaptive arithmetic encoder yielded higher compression ratio. The method doesn't need float operation and uses the comparability of wavelet coefficients in each scale. Simulation results show that the features of the method were low computation complexity, fast compression rate, high compression ratio and small reconstruction difference, when it is applied to the compression decompression process of temperature signals from a paper mill
基于整数小波变换和SPIHT的过程工业历史数据压缩方法研究
为了压缩过程工业历史数据,减少数据存储量,提出了一种基于整数小波变换和分层树集划分的压缩方法。利用整数小波变换将原始数据分解为5层,得到小波系数和时间方向树。对小波系数进行SPIHT编码,导出位平面。采用自适应算法编码器对位平面进行编码后,获得了更高的压缩比。该方法不需要浮点运算,利用了各尺度小波系数的可比性。仿真结果表明,将该方法应用于某造纸厂温度信号的压缩解压缩过程,具有计算复杂度低、压缩速率快、压缩比高、重构差小的特点
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