应用小波Firm阈值滤波实现光谱实时采集

提出了一种利用小波域Firm阈值滤波去除随机噪声的方法,以提高微型光谱仪的光谱采集精度。首先,采集2次光谱谱线,取均值作为待处理谱线;然后,计算出这两次谱线的噪声标准差取代传统小波去噪中的噪声标准差估计,运用通用阈值法确定上阈值。调整下阈值对待处理谱线进行小波Firm阈值滤波,并判断滤波后偏差是否在计算的噪声方差内。选用标准溶液以2种浓度做相对吸光度实验(标准值是A=0.3204),分别用传统10次平均方法和Firm阈值滤波法进行去噪。实验结果表明,提出的方法优于传统10次平均法,标准差从0.00796降低到了0.00697,提高了采集速度。在以光纤光谱仪为主体的微型生化分析仪样品检测过程中的应用表明:该方法提高了检测精度,减少了检测时间,提高效率4～5倍。

Spectral data real-time acquisition with wavelet Firm shrinkage filtering

A method for spectral data real-time acquisition with Firm shrinkage wavelet filtering was presented in this paper to improve the performance of biochemical analyzers. Firstly, two spectral lines were acquired and their average spectrum was taken to be processed. Then, the noise variance from two spectral lines was calculated to be used as the next threshold to replace the noise variance estimation based on traditional wavelet denoising. Furthermore, by adjusting the threshold on the line, the average spectrum was processed with Firm wavelet filtering and evaluation criteria were obtained. A relative spectral absorbance experiment was carried out based on the traditional 10 times average method and proposed Firm wavelet filtering method, and the experiment results indicate that the standard deviation of spectral signals obtained from the proposed method has decreased from 0.007 96 to 0.006 97,which means the acquired speed of the proposed method is higher than that of the traditional method. Moreover, the method has been used in a micro biochemical analyzer, tested results show that it optimizes the detection accuracy, reduces the detection time and the detection efficiency has improved by 4-5 times.