Lifting wavelet de-noising method with dual-threshold based on PSO algorithm
Sheng Liu, Qingchun Zhang, Mingming Gu · Chinese Control Conference · 2013
To remove the noise of signal and improve the signal-to-noise ratio, we present a lifting wavelet de-noising method with flexible dual-threshold based on PSO algorithm. We use the lifting wavelet instead of traditional wavelet to decompose the signal, in order to improve the operation speed. we use the quantization function by flexible dual-threshold to quantify the detail coefficients. By doing this, we preferably retained the fine features of the signal, while preventing the signal oscillation. PSO algorithm is used to optimize the dual-threshold, in order to get the optimal threshold value, to improve the signal-to-noise ratio. The simulation and experimental results show that this new de-noising method can effectively suppress the noise, and get a higher signal-to-noise ratio and faster processing speed compared to the traditional denoising method.