小波阈值降噪算法中最优分解层数的自适应选择

Adaptive Selection of Optimal Decomposition Level in Threshold De-noising Algorithm Based on Wavelet

小波阈值降噪算法是一种去除数字信号中白噪声的有效算法.针对加性高斯白噪声的情况,提出一种自适应小波降噪算法,用于语音信号的增强.它能根据带噪信号的特点,自适应选择小波变换的最优分解层数.实验结果表明,该算法比经典的小波降噪算法具有更好的降噪效果,能有效提高算法的实用性能.

Threshold de-noising in wavelet domain is an efficient algorithm to reduce the white noise in digital signal, In the presence of additive white Gaussian noise, an adaptive wavelet-based de-noising algorithm for speech enhancement applications is proposed. It can adaptively select the optimal decomposition level of wavelet transformation according to the characteristics of noisy speech. The experimental results demonstrate that this proposed algorithm outperforms the classical wavelet thresholding method and effectively improves the practicability.