Design and Implementation of filters in Empirical Data Decomposition
Xiaoqin Wu, Hongke Zhang · Signal Processing · 2009
The algorithm of Empirical Data Decomposition(EDD) is been studied.In terms of reconstructing requirement,the relation between the parameters of EDD filters and those of bi-orthogonal filter banks is analyzed and the condition that the analysis filter and the synthesis filter are FIR filters is discussed.The analysis high-pass filter can be feasibly designed according to different applications and at the same time the reconstructing filter is surely FIR filter.The coefficients of the analysis high-pass filter are predicted by use of optimal filtering and predicting technology of discrete linear system.The optimal predicting filter coefficients are decided through testing on spectrum image data.The spectrum image data is processed by the algorithm proposed in the paper and the kernel algorithm of JPEG2000,that is Embedded Block Coding with Optimized Truncation(EBCOT).The comparison between the output code rate of the EDD algorithm and that JPEG2000 loss-less compression shows the output code rate of lossless compression declines 0.217bpp on the average with EDD algorithm,and proved EDD is an effective analysis method for non-stationary image data.