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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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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 alterna-tives 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:实现了用于在保持信号信息的同时改善拉曼光谱信号的降噪算法。基于小波去噪和卡尔曼滤波的算法作为众所周知的SAVITKY-GOLAY算法,将其作为替代替代品呈现。基于在分散光谱仪中使用CCD检测器获取的实际信号的噪声统计,设计了小波和卡尔曼算法。实验结果表明,数据采集中产生的随机噪声由子泊松统计管辖。已经使用真实和合成数据测试了所提出的算法,并使用均方的均方误差(MSE)和Infinity Norm(L_‖)进行比较,并彼此和标准Savitky-Golay算法。结果表明,基于小波的去噪能力在MSE和L_∞中表现更好。

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