It always tends to assume that the noise contained in signal spread over high frequency domain in the traditional wavelet threshold de-noising techniques.However

it doesn't hold for different noise categories

and threshold de-noising methods in most literatures rarely mention the noise influence spread over low frequency domain.Thus

a new framework for noise reduction base on full frequency domain using wavelet decomposition and noise-type detection are proposed.In this framework

the noise type is firstly to be detected by analyzing autocorrelation coefficient for different noise

and then noise reduction is performed both in low and high frequency domain.The experimental results show that:(1) when signal-to-noise ratio is low

our method not only always achieves better de-nosing performance

but needs fewer decomposition layers than the traditional methods;(2) when the signal-to-noise ratio is high

our method can obtain the same performance as the traditional methods

but our method needs less decomposition layers.