JOURNAL ARTICLE

Application of wavelet transform in signal denoising

Abstract

The signal, which involves noise, is adverse for signal analyzing. The noise can be removed from the stationary signal by using wavelet transform or Fourier transform. But it is more advantage to remove noise from non-stationary signal with wavelet transform because of the local characteristic of the wavelet transform. Aiming at the character of the noise, this article describes, analyses, and compares several methods of removing noise from the angles of the wavelet decomposition, the wavelet reconstruction and the maximum values of the wavelet transform.

Keywords:
Harmonic wavelet transform Second-generation wavelet transform Stationary wavelet transform Wavelet transform Wavelet packet decomposition Discrete wavelet transform Wavelet Lifting scheme Computer science Constant Q transform Artificial intelligence Pattern recognition (psychology) Noise (video) Mathematics Image (mathematics)

Metrics

14
Cited By
0.00
FWCI (Field Weighted Citation Impact)
5
Refs
0.36
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Image and Signal Denoising Methods
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Machine Fault Diagnosis Techniques
Physical Sciences →  Engineering →  Control and Systems Engineering
Advanced Image Fusion Techniques
Physical Sciences →  Engineering →  Media Technology

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