小波阈值降噪算法在光电探测器信号处理中的应用

Application of Wavelet Threshold Denoising Algorithm in Photodetector Signal Processing

针对光电探测器传统降噪处理中软、硬阈值函数存在的缺点,提出了一种含参数的阈值函数和逐层变化的阈值相结合的小波阈值降噪算法.该算法可以调整参数使生成的阈值函数于软、硬阈值函数之间,且在临界阈值处平滑过渡,保留部分有用信号.应用过程中阈值可随着分解层数的改变而改变,对各个分解层有自适应特征,减少小波系数阈值处理中的固定偏差,从而在保留原有信号的同时减除不必要噪声.仿真及实测结果表明,采用该小波阈值降噪算法处理的信号信噪比较高、均方误差较小,有效地抑制噪声对光电探测器输出信号的干扰.

To overcome the shortcomings of the traditional noise reduction processing in photodetectors,a novel wavelet threshold denoising algorithm is presented.A threshold function with parameters and layer-by-layer threshold are combined in the algorithm.By adjusting the parameters,a threshold function can be generated,which value is between soft and hard threshold functions,and can realize the smooth transition at the critical threshold.During the application,the threshold can be changed with the change of decomposition layers.The individual decomposition layer has adaptive characteristics.So it can reduce the fixed deviation in the wavelet threshold processing,and then the unnecessary noise can be restrained while the original signal is remained.The results of simulation and experiment show that the SNR of signal processed by the wavelet threshold denoising algorithm are relatively high and the mean square error is small.Furthermore,the algorithm can effectively suppress the interference of noise on the output signal of photodetector.