Improved wavelet threshold denoising algorithm

DU Shi-qiang; SONG Yu-kun; ZHANG Xuan; ZHANG Duo-li

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Improved wavelet threshold denoising algorithm

更新时间：2026-09-04

- Improved wavelet threshold denoising algorithm
- Vol. 38, Issue 2, Pages: 40-46(2021)
- 作者机构：
  
  合肥工业大学电子科学与应用物理学院,安徽,合肥,230009
- 作者简介：
- 基金信息：
- DOI：
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- Published：2021
- 稿件说明：
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杜诗强, 宋宇鲲, 张玄, 张多利. 一种改进的小波阈值去噪算法[J]. 微电子学与计算机, 2021, 38(2): 40-46.

DU Shi-qiang, SONG Yu-kun, ZHANG Xuan, et al. Improved wavelet threshold denoising algorithm[J]. 2021, 38(2): 40-46.
杜诗强, 宋宇鲲, 张玄, 张多利. 一种改进的小波阈值去噪算法[J]. 微电子学与计算机, 2021, 38(2): 40-46. DOI：

DU Shi-qiang, SONG Yu-kun, ZHANG Xuan, et al. Improved wavelet threshold denoising algorithm[J]. 2021, 38(2): 40-46. DOI：

摘要

小波变换具有低熵性、多分辨率性和去相关性等优点，在信号去噪方面得到广泛应用.本文在传统小波阈值去噪算法的基础上，结合已有改进的阈值函数和阈值选取方式，提出一种改进的小波阈值去噪算法.改进阈值函数具有更好的连续性和更小的系数偏差；新的阈值选取方式结合了信号的Lipschitz特性，具有更高的噪声信号去除率.通过去噪仿真实验表明，改进的小波阈值去噪算法在信噪比(SNR)和均方误差(MSE)上相较于传统算法提升了14.4%和58.3%，相较于已有算法提升了8.4%和36.5%，具有更优的去噪效果，证明了本文提出的去噪算法的性能优势和工程应用价值.

Abstract

Wavelet transform is widely used in signal denoising because of its advantages such as low entropy

multi-resolution and de-correlation. Based on the traditional wavelet threshold denoising algorithm

this paper proposes an improved wavelet threshold denoising algorithm based on the existing improved threshold function and threshold selection method. The improved threshold function has better continuity and smaller coefficient deviation; the new threshold selection method combines the Lipschitz characteristic of the signal and has a higher noise signal removal rate. Denoising simulation experiments show that the improved wavelet threshold denoising algorithm improves the signal-to-noise ratio (SNR) and mean square error (MSE) by 14.4% and 58.3% compared with the traditional algorithm

and improves by comparing with existing algorithms 8.4% and 36.5% have better denoising effect

which proves the performance advantages and engineering application value of the proposed denoising algorithm.

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Keywords

references

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