拉曼光谱
降噪
像素
稳健性(进化)
信号(编程语言)
化学
人工智能
模式识别(心理学)
分析物
相似性(几何)
光学
生物系统
计算机科学
图像(数学)
物理
生物
基因
物理化学
生物化学
程序设计语言
作者
Zhen Liu,Mohamed A. Ettabib,Bethany M. Bowden,Philip N. Bartlett,James S. Wilkinson,M.N. Zervas
标识
DOI:10.1016/j.saa.2024.123931
摘要
A method for denoising Raman spectra is presented in this paper. The approach is based on the principle that the original signal can be restored by averaging pixels based on structure similarity. Similarity searching and averaging are not limited to the neighbouring pixels but extended throughout the entire signal range across different frames. This approach is distinguished from the conventional single-frame neighbour pixel-based filtering. The effectiveness and robustness of the proposed method are demonstrated through denoising simulated and experimental Raman data sets with fixed denoising parameters. Several denoised results and statistical indicators are presented for the simulated data. Recovery of the experimental Raman spectrum from our newly developed cost-effective waveguide-enhanced Raman spectroscopy system is also presented and compared to the spectrum from a conventional expensive Raman microscope for the same analyte.
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