红外光谱预处理中去噪的研究

Study on Denoising in Pretreatment of Infrared Spectrum

红外(IR)光谱由于包含了噪声等各种外界干扰因素。应该先进行光谱预处理,以便降噪,提高分析准确度。本文采用了一种基于最优小波包基的信号去噪算法,该算法根据最小代价原理,采用不同的阈值算法对光谱的高频和低频信号进行量化处理,用量化后的系数重构得到去噪信号,从而达到较好的去噪效果。实验表明,本方法处理后光谱曲线非常光滑、噪声消除效果明显。

IR spectroscopic data of samples are confused by a series of noise, which greatly influences the achievement of accurate analytical result. An algorithm based on best wavelet packet groups with least cost principle was used to deal with the spectrum data in high and low frequency regions by different methods. The denoised signal indicates that the algorithm can increase the accuracy of spectral analysis ,smooth the spectra perfectly, and eliminate noises obviously.