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Denoising of Single Scan Raman Spectroscopy Signals

机译:单扫描拉曼光谱信号的去噪

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摘要

Noise reduction algorithms for improving Raman spectroscopy signals while preserving signal information were implemented. Algorithms based on Wavelet denoising and Kalman filtering are presented in this work as alternatives to the well-known Savitky-Golay algorithm. The Wavelet and Kalman algorithms were designed based on the noise statistics of real signals acquired using CCD detectors in dispersive spectrometers. Experimental results show that the random noise generated in the data acquisition is governed by sub-Poisson statistics. The proposed algorithms have been tested using both real and synthetic data, and were compared using Mean Squared Error (MSE) and Infinity Norm (L_∞) to each other and to the standard Savitky-Golay algorithm. Results show that denoising based on Wavelets performs better in both the MSE and L_∞ the sense.
机译:实施了用于降低拉曼光谱信号同时保留信号信息的降噪算法。在这项工作中提出了基于小波去噪和卡尔曼滤波的算法,以替代著名的Savitky-Golay算法。小波和卡尔曼算法是根据色散光谱仪中使用CCD检测器采集的实际信号的噪声统计数据设计的。实验结果表明,数据采集中产生的随机噪声受子泊松统计量控制。所提出的算法已使用真实数据和合成数据进行了测试,并使用均方误差(MSE)和无穷范数(L_∞)进行了比较,并与标准Savitky-Golay算法进行了比较。结果表明,基于小波的去噪在MSE和L_∞方面均表现更好。

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