Abstract:The dual-tree complex wavelet is introduced into the de-noising of the deformation monitoring data. The feasibility and effectiveness are comprehensively evaluated by the signal decomposition, de-noising process and de-noising quality. The theoretical analysis and examples show that the quality of signal-to-noise separation will have a great impact on threshold estimation, threshold de-noising and signal reconstruction. To a certain extent, the signal with better signal-to-noise separation can weaken the defect of threshold function. The decomposition effect of dual-tree complex wavelet is better than that of traditional discrete wavelet, and it can better display the frequency information of the detail part, so that the characteristic variation of deformation signal is more obvious. The dual-tree complex wavelet can be applied in deformation monitoring data analysis.