This paper applied the wavelet transform algorithm to denoise music signals. To improve its noise reduction effect, the threshold function was improved. Finally, simulation trials were conducted to test the performance of the improved wavelet transform noise reduction algorithm under different wavelet basis functions and decomposition scales. Then, it was compared with the Fourier transform, traditional wavelet transform, and independent component analysis algorithms. The results showed that it was most suitable when Symlets was adopted as the wavelet basis function and the decomposition scale was set to 6; the performance of the improved algorithm was better than the other three algorithms.
ChoiHLeeJHKimSM, et al.Speckle noise reduction in ultrasound images using a discrete wavelet transform-based image fusion technique. Biomed Mater Eng2015; 26(s1): 1587–1597.
2.
ChenXLiJ. Noise reduction for ultrasonic lamb wave signals by empirical mode decomposition and wavelet transform. J Vibroeng2016; 15(3): 1157–1165.
3.
WangQLiuY. Seismic wavelet signal noise reduction algorithm of blind source separation optimization. Metall Min Ind2015; 7(6): 275–280.
4.
KhmagARamliARbin HashimSJ, et al.Additive noise reduction in natural images using second-generation wavelet transform hidden Markov models. IEEJ Transactions Elec Engng2016; 11(3): 339–347.
5.
SongPTanYGengX, et al.Noise reduction on received signals in wireless ultraviolet communications using wavelet transform. IEEE Access2020; 8: 131626–131635.
6.
LependinAAIlyashenkoIDNasretdinovRS. Use of trainable wavelet transform with adaptive threshold filtering for noise reduction of speech signals. J Phys: Conf Ser2020; 1615(1): 1–8.
7.
GaoGZhouSYangS, et al.Accurate identification partial discharge of cable termination for high-speed trains based on wavelet transform and convolutional neural network. Elec Power Syst Res2023; 225: 1.1–1.12.
8.
ChoiHJeongJ. Despeckling images using a preprocessing filter and discrete wavelet transform-based noise reduction techniques. IEEE Sens J2018; 18(8): 3131–3139.
9.
HussainNHasanzadeMBreibyDW, et al.Performance comparison of wavelet families for noise reduction and intensity thresholding in Fourier ptychographic microscopy. Opt Commun2022; 519: 1–10.
10.
GhribiKDjendiMBerkaniD. A wavelet-NLMS algorithm implemented in FBSS for acoustic noise reduction and speech enhancement. In: 2018 2nd international conference on natural language and speech processing (ICNLSP), Algiers, Algeria, 25–26 April 2018, pp. 1–5.
11.
LiuJGuYChouY, et al.Seismic random noise reduction using adaptive threshold combined scale and directional characteristics of shearlet transform. IEEE Geosci Remote Sens Lett2019; 17(9): 1637–1641.
12.
AnvariRNazari SiahsarMAGholtashiS, et al.Seismic random noise attenuation using synchrosqueezed wavelet transform and low-rank signal matrix approximation. IEEE Trans Geosci Remote Sens2017; 55(11): 6574–6581.
13.
AlamAMukulMKThakuraP. Wavelet transform-based EMI noise mitigation in power converter topologies. IEEE Trans Electromagn Compat2016; 58(5): 1662–1673.
14.
ChenQZhangJLiB. Research on 3D MFL testing of wire rope based on empirical wavelet transform and SRCNN. J Vibroeng2022; 24(4): 779–792.
15.
YangJZFengZWangXD, et al.Research on noise reduction method based on CEEMD-WT-SVD and its application in acoustic signal of pipeline blockage. Comput J2019; 30(2): 224–239.
