Abstract：Raman spectroscopy occupies an important position in modern spectroscopy technique due to its numerous advantages such as non-invasive, high-sensitivity, etc. Meanwhile baseline correction is one of the key technologies of Raman qualitative and quantitative analysis, thus it is meaningful to develop high performance algorithms for baseline correction for the purpose to improve the effectiveness and accuracy of analytical results. Because of the defect of traditional algorithms for the problem to correct baselines of a group of Raman spectra which have a similar background, this paper proposed a fast Raman baseline correction algorithm (FRBCA) based on automatic linear fitting for this problem and demonstrated its fundamental ideas and the implementation process of this algorithm. In the FRBCA algorithm, firstly one of the spectra was selected automatically as a reference spectrum and estimated its baseline and the mask points by the automatic linear fitting algorithm, then the baselines of other spectra which have a high relativity to the selected spectrum were estimated quickly based on the mask points of reference spectrum. Separate treatment was called for those spectra which does not satisfy the condition. This innovation makes the algorithm has strong robustness and can be suitable for the complex Raman spectrum baseline correction scenario. In addition, some actual Raman spectral data were used to test performance of the algorithm and make a comparison between the proposed algorithm and the traditional algorithm. The results show that fast Raman baseline correction algorithm proposed in this article allows a fast Roman baseline correction for a number of Raman spectral data. It reduces the consuming time more than 30% while has a similar performance at the correction result no worse than the algorithm correcting the Raman spectroscopy individually. The method presented in this article is conceptually simple, easy to implement, fully automated and doesn’t need additional parameters, making it suitable for the fully automated baseline correction of large numbers of spectra which have a similar background.
Key words：Raman spectroscopy; Fast baseline correction; Automatic linear fitting
基金资助: the National Natural Science Foundation of China (61178075)
通讯作者:
赵军武
E-mail: jwzhao@mail.xjtu.edu.cn
作者简介: ZHANG Wan-li，(1993—)，Master Degree Candidate, The School of Life Science and Technology, Xi’an Jiaotong University
e-mail:
zhangwanli1993@stu.xjtu.edu.cn
引用本文:
张万里，朱 键，李剑君，赵军武. 基于自动线性拟合的快速拉曼基线校正算法[J]. 光谱学与光谱分析, 2017, 37(08): 2632-2637.
ZHANG Wan-li, ZHU Jian, LI Jian-jun, ZHAO Jun-wu. A Fast Raman Baseline Correction Algorithm Based on Automatic Linear Fitting. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2017, 37(08): 2632-2637.
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