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.
['Peng Jiang', 'Qingbo Huang', 'Yaguang Kong', 'Li Chai']
Research on Compression Method Based on Integer Wavelet Transform and SPIHT for Historical Data in Process Industry