Open AccessApplication of Weak Signal Denoising Based on Improved Wavelet Threshold
Author(s) -
Ning Zhang,
Pengfei Lin,
Lei Xu
Publication year - 2020
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/751/1/012073
Subject(s) - noise reduction , wavelet , wavelet packet decomposition , signal (programming language) , pattern recognition (psychology) , noise (video) , mathematics , video denoising , step detection , algorithm , artificial intelligence , computer science , wavelet transform , computer vision , filter (signal processing) , object (grammar) , video tracking , multiview video coding , image (mathematics) , programming language
In this Study, the application of wavelet threshold denoising in weak signal detection of underwater targets under complex sea conditions is discussed. Firstly, the basic principle and steps of wavelet threshold denoising method based on Mallat decomposition are analyzed. Then a new threshold function is proposed to overcome the shortcomings of traditional Donoho hard and soft thresholds. The denoising effects of wavelet and wavelet packet threshold denoising methods under hard threshold, soft threshold and new threshold functions are simulated, and the signal-to-noise ratio (SNR) and mean square error (MSE) after denoising are taken as evaluation indexes. The results show that the improved threshold denoising method outperforms the traditional threshold denoising methods.