基于协同滤波的尖峰噪声抑制方法

针对旋转磁共振探测方法易受尖峰噪声干扰的问题, 提出一种协同滤波消除核磁共振探测数据中尖峰噪声的方法. 先通过3σ法则判断一个脉冲矩下测量数据是否存在尖峰噪声, 将测量数据分为有尖峰噪声和无尖峰噪声两组； 再分别对其进行离散余弦和Hadamard变换, 得到两组变换域系数, 用无尖峰噪声数据的变换系数计算Wiener滤波系数, 利用该系数对含尖峰噪声的数据进行滤波; 最后, 对滤波后含尖峰噪声数据的系数进行Hadamard和离散余弦逆变换, 实现尖峰噪声的消除. 仿真实验结果表明, 该方法对地面核磁共振数据中尖峰噪声的消除准确度较高, 提高了信号特征参数的提取精度.

Peak Noise Suppression Method Based on Collaborative Filtering

Aiming at the problem that the detection method of rotational magnetic resonance was easy disturbed by the peak noise, we proposed  a collaborative filtering method to eliminate the peak noise in nuclear magnetic resonance (NMR) data. Firstly, the method of 3σ was used to determine whether the re was peak noise in the measured data under a pulse moment. The measured data were divided into two groups: peak noise and non-peak noise. Secondly, the discrete cosine transform and the Hadamard transform were performed respectively to obtain two groups of transform domain coefficients. Wiener filtering coefficient was calculated by using the transform coefficient of non-peak noise data, and the coefficient was used to filter the data containing peak noise. Finally, the filtered coefficient containing the peak noise data was inversely converted by Hadamard and discrete cosine to eliminate the peak noise. The simulation results show that the method has high accuracy in eliminating the peak noise in the ground NMR data and improves the extraction precision of signal characteristic parameters.