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Improved Baseline Correction Method Based on Polynomial Fitting for Raman Spectroscopy

机译:基于多项式拟合的改进拉曼光谱基线校正方法

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Raman spectrum, as a kind of scattering spectrum, has been widely used in many fields because it can characterize the special properties of materials. However, Raman signal is so weak that the noise distorts the real signals seriously. Polynomial fitting has been proved to be the most convenient and simplest method for baseline correction. It is hard to choose the order of polynomial because it may be so high that Runge phenomenon appears or so low that inaccuracy fitting happens. This paper proposes an improved approach for baseline correction, namely the piecewise polynomial fitting (PPF). The spectral data are segmented, and then the proper orders are fitted, respectively. The iterative optimization method is used to eliminate discontinuities between piecewise points. The experimental results demonstrate that this approach improves the fitting accuracy.
机译:拉曼光谱作为一种散射光谱,由于可以表征材料的特殊性能,因此已在许多领域得到了广泛应用。但是,拉曼信号是如此微弱,以至于噪声严重扭曲了真实信号。多项式拟合已被证明是最便捷,最简单的基线校正方法。多项式的阶数很难选择,因为它可能太高而导致出现Runge现象,或者太低而导致不精确拟合发生。本文提出了一种用于基线校正的改进方法,即分段多项式拟合(PPF)。分割光谱数据,然后分别拟合适当的阶数。迭代优化方法用于消除分段点之间的不连续性。实验结果表明,该方法提高了拟合精度。

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