In the low-field medical magnetic resonance imaging (MRI) system, the original digital MR signal is generated with high
sampling rate and a large amount of noise. In this paper, we propose a wavelet transform-based preprocessing algorithm
for this MR signal, in order to eliminate the noise, reduce the sampling rate and compress the memory of data. We select
Daubechies filter as our decomposition filter and perform multi-level wavelet decomposition on the MR signal. The
scaling function coefficients are obtained at the levels of decomposition, and taken as the low-frequency signal
component. So that fast filtering and multistage decimation without spectrum-aliasing are realized. The experiment based
on the permanent magnetism resonance imaging system proves the efficiency and practicability of this algorithm.