Application of Wavelet Threshold Denoising Algorithm in Photodetector Signal Processing

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 layerby-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.