基于多尺度小波变换的红外光谱谱峰识别算法

Peak Detection for Infrared Spectrum Based on Continuous Wavelet Transform

传统的谱峰检测方法一般分为3个步骤:谱线平滑、基线校正和谱峰识别。现有的基于小波变换的峰值检测方法能较好地将基线校正和谱峰识别两个步骤融为一步。在此基础之上,本研究将谱线平滑也很好地融入到小波变换的峰值检测算法中,使整个峰值检测算法成为一个整体。在峰值提取时,原始谱图直接处理,不再是处理加工过的谱图,减小了谱峰检测结果出错的可能性。另外,对基于小波变换的谱峰检测算法中模极大值检测算法存在不确定阈值的问题进行了修改,使得基于小波变换的谱峰检测算法更为完善。

In spectrum analysis,peak detection is an essential step for subsequent analysis.Traditionally,peak detection procedure is divided into three consequent parts： smoothing,baseline correction and peak finding.The existing peak detection method based on continuous wavelet transform can combine the baseline correction and peak finding into one part.It simplified the traditional peak detection procedure,but this method still has two parts.A method based on continuous wavelet transform which finishes the three parts at a time was proposed in this study.The baseline′s function of original signal is monotone and linear,so after wavelet transform,there is no information of baseline in the wavelet coefficients.What we need do is deal with the coefficients.First,remove the noise in the coefficients based on Liapunov Exponent.Then,find the ridge mentioned in this study.The position of ridge is the peak′s position.The proposed method further simplifies the peak detection procedure.