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Raman Spectral Data De-noising Based on Wavelet Analysis

机译:基于小波分析的拉曼光谱数据降噪

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As one kind of molecule scattering spectroscopy, Raman spectroscopy (RS) is characterized by the frequency excursion that can show the information of molecule. RS has a broad application in biological, chemical, environmental and industrial fields. But signals in Raman spectral analysis often have noise, which greatly influences the achievement of accurate analytical results. The de-noising of RS signals is an important part of spectral analysis. Wavelet transform has been established with the Fourier transform as a data-processing method in analytical fields. The main fields of application are related to de-noising, compression, variable reduction, and signal suppression. In de-noising of Raman Spectroscopy, wavelet is chosen to construct de-noising function because of its excellent properties. In this paper, bior wavelet is adopted to remove the noise in the Raman spectra. It eliminates noise obviously and the result is satisfying. This method can provide some bases for practical de-noising in Raman spectra.
机译:作为一种分子散射光谱,拉曼光谱(RS)的特征在于可以显示分子信息的频率偏移。 RS在生物,化学,环境和工业领域具有广泛的应用。但是拉曼光谱分析中的信号经常会产生噪声,这极大地影响了准确分析结果的实现。 RS信号的降噪是频谱分析的重要组成部分。小波变换已经建立了傅立叶变换作为分析领域中的一种数据处理方法。应用的主要领域涉及降噪,压缩,变量减少和信号抑制。在拉曼光谱的去噪中,由于其优异的性能,选择小波来构造去噪功能。本文采用bior小波去除拉曼光谱中的噪声。明显消除噪音,效果令人满意。该方法可以为拉曼光谱的实际降噪提供一些依据。

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