使用光谱仪采集到的信号难免受到不同噪声源的影响。为了提高光谱信号解析的精准度, 通过分析小波应用于信号降噪的原理以及经典的软、硬阈值降噪法存在的缺陷, 提出了一种改进的阈值降噪法。该方法既克服了硬阈值法产生间断点, 软阈值法产生恒定偏差的缺陷, 又尽量地保留了有用信号。实验选用的小波基函数为SymletsA, 分解层数为4, 结合Birge-Massart策略模型确定的分层阈值对硒化镉量子点荧光光谱信号进行降噪处理。结果表明, 与经典的软、硬阈值降噪法相比, 通过改进阈值降噪法得到重构信号的信噪比(SNR=47.550 2)、能量占比(PER=0.973 3)和均方误差(MSE=149.421 3)均有提高和改善。

The signal collected by using the spectrometer is inevitably affected by different noise sources. In order to increase the analytical accuracy of spectrum signal, an improved denoising method with threshold was presented by analyzing the principle of applying the wavelet to signal denoising and the defects existed in classical denoising methods by using soft and hard thresholds. The improved method can overcome both the defects, that the hard threshold method generates discontinuities and the soft threshold method generates a constant variation, and can retain the useful signals as much as possible. In experiment, the SymletsA wavelet was selected as the wavelet function with 4 series, through combining with the per-level threshold determined by the Birge-Massart tactics pattern,the denoising process was conducted for the fluorescence spectrum signal of CdSe quantum dots . Simulation results demonstrate that the rebuilt signal by the improved denoising method with threshold can has a increased signal-to-noise ratio(SNR=47.550 2) and a energy accounting(PER=0.973 3), as well as an improved mean squared error(MSE=149.421 3) compared with the classical denoising methods by using soft and hard thresholds.