基于平移不变的小波去噪方法及应用

Denoise Based On Translation Invariance Wavelet TransformAnd Its Applications

基于传统的小波变换去噪算法可能使信号的急剧变化部分产生人为的振荡现象 ,产生这种现象的一个直接原因是小波缺乏平移不变性。提出了基于平移不变的小波去噪方法 ,对所分析的信号进行循环平移 ,再利用软或硬门限对该信号的小波系数进行压缩 ,重构信号 ,再进行相反的循环平移 ,通过多次的平移—消噪—平移 ,平均所获得的结果 ,从而消除小波基的平移依赖性。该方法能有效地消除人为的振荡现象 ,使消噪后的信号更加光滑 ,更好地逼近真实信号。

De_noising algorithm based on traditional wavelet transform may produce artifacts on discontinuities of the signal. The reason is that the de_noising algorithm lacks of wavelet translation invariant. This paper proposes a de_noising method based on translation invariant. The method performs the cycle_spinning for the signal to be analyzed. And then, the soft (hard) thresholding is used to shrink the wavelet coefficient of the signal and reconstruct the signal. Consequently, the shift dependence of wavelet basis is eliminated. This method can suppress the artifacts effectively so that de_noised signal is more smooth and has better approximation to original signal.