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Automatic morphology-based cubic p-spline fitting methodology for smoothing and baseline-removal of Raman spectra

机译:基于自动形态的立方P样条拟合方法,用于平滑和基线移除拉曼光谱

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摘要

Noise filtering is considered a crucial step for the proper interpretation of Raman spectra. In this work, we present a new denoising procedure which enhances the Raman information whilst reducing unwanted contributions from the most frequent noise sources, i.e. the shot noise and the fluorescence's baseline. The procedure increases the signal-to-noise ratio whilst preserving simultaneously the shapes, positions and intensity ratios of the Raman bands. The method relies on cubic penalized spline fitting and mathematical morphology and requires no user input. We describe the details of this method and include a benchmark to study the performance of the presented approach compared with the most commonly used denoising techniques. The method has been successfully applied to improve the signal quality of Raman spectra from artistic pigments. The reliable results that were obtained make the methodology a useful tool to help the analyst in the interpretation of Raman spectra from pigments in artworks. Copyright © 2017 John Wiley & Sons, Ltd.
机译:噪声滤波被认为是正确解释拉曼光谱的关键步骤。在这项工作中,我们提出了一种新的去噪程序,该程序增强了拉曼信息,同时减少了来自最常见的噪声源的不需要的贡献,即射击噪声和荧光的基线。该过程提高了信噪比,同时保留了拉曼带的形状,位置和强度比。该方法依赖于立方惩罚样条拟合和数学形态,不需要用户输入。我们描述了该方法的细节,并包括研究所提出的方法的性能的基准与最常用的去噪技术相比。该方法已成功应用于改善艺术性颜料的拉曼光谱的信号质量。获得的可靠结果使方法是有用的工具,以帮助分析师在艺术品中从颜料解释Raman Spectra。版权所有©2017 John Wiley&Sons,Ltd。

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