Signal‐to‐noise ratio enhancement for Raman spectra based on optimized Raman spectrometer and convolutional denoising autoencoder

The signal‐noise ratio plays a key role in acquiring plentiful chemical structural information in the Raman spectrometer. The miniature spectrometer is generally compact at the expense of performance. In this work, we proposed a compact, signal‐to‐noise ratio (SNR) enhancement of the Raman spectrome...

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Vydáno v:	Journal of Raman spectroscopy Ročník 52; číslo 4; s. 890 - 900
Hlavní autoři:	Fan, Xian‐guang, Zeng, Yingjie, Zhi, Yu‐Liang, Nie, Ting, Xu, Ying‐jie, Wang, Xin
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Bognor Regis Wiley Subscription Services, Inc 01.04.2021
Témata:	Algorithms autoencoder convolutional neural network Czerny‐Turner denoising Noise Noise reduction Optimization Raman spectra Raman spectrometer Raman spectroscopy Spectrometers
ISSN:	0377-0486, 1097-4555
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Abstract	The signal‐noise ratio plays a key role in acquiring plentiful chemical structural information in the Raman spectrometer. The miniature spectrometer is generally compact at the expense of performance. In this work, we proposed a compact, signal‐to‐noise ratio (SNR) enhancement of the Raman spectrometer by the optimization of optical structure and a noise reduction method. Concerning its optical structure, the Raman spectrometer is increasing the intensity by adding an off‐the‐shelf cylindrical lens. On the other side of the algorithm, a relevant automatic denoising method of convolutional denoising autoencoder (CDAE) is proposed to further advance the SNR in Raman spectra without manual intervention. The results indicate the performance of the compact Raman spectrometer could increase to a certain extent by testing with 785 nm laser and Ne/Ar source. Besides, by using CDAE to deal with contaminated Raman spectra, a higher SNR is obtained. The results demonstrate that the improvement of the hardware and algorithm is effective for removing the noisy Raman signal and achieving higher SNR. This result may be helpful in further improving the performance of integrated Raman spectrometers and research on miniaturized instruments. In consideration of signal to noise ratio(SNR) is related to signal intensity and noise level, we hope to improve SNR through optic structure optimization and develop a denoising algorithm. A cylindrical lens has been used to enhance intensity. The convolutional denoising autoencoder (CDAE) algorithm is acquired for the reduction of the noise.
AbstractList	The signal‐noise ratio plays a key role in acquiring plentiful chemical structural information in the Raman spectrometer. The miniature spectrometer is generally compact at the expense of performance. In this work, we proposed a compact, signal‐to‐noise ratio (SNR) enhancement of the Raman spectrometer by the optimization of optical structure and a noise reduction method. Concerning its optical structure, the Raman spectrometer is increasing the intensity by adding an off‐the‐shelf cylindrical lens. On the other side of the algorithm, a relevant automatic denoising method of convolutional denoising autoencoder (CDAE) is proposed to further advance the SNR in Raman spectra without manual intervention. The results indicate the performance of the compact Raman spectrometer could increase to a certain extent by testing with 785 nm laser and Ne/Ar source. Besides, by using CDAE to deal with contaminated Raman spectra, a higher SNR is obtained. The results demonstrate that the improvement of the hardware and algorithm is effective for removing the noisy Raman signal and achieving higher SNR. This result may be helpful in further improving the performance of integrated Raman spectrometers and research on miniaturized instruments. The signal‐noise ratio plays a key role in acquiring plentiful chemical structural information in the Raman spectrometer. The miniature spectrometer is generally compact at the expense of performance. In this work, we proposed a compact, signal‐to‐noise ratio (SNR) enhancement of the Raman spectrometer by the optimization of optical structure and a noise reduction method. Concerning its optical structure, the Raman spectrometer is increasing the intensity by adding an off‐the‐shelf cylindrical lens. On the other side of the algorithm, a relevant automatic denoising method of convolutional denoising autoencoder (CDAE) is proposed to further advance the SNR in Raman spectra without manual intervention. The results indicate the performance of the compact Raman spectrometer could increase to a certain extent by testing with 785 nm laser and Ne/Ar source. Besides, by using CDAE to deal with contaminated Raman spectra, a higher SNR is obtained. The results demonstrate that the improvement of the hardware and algorithm is effective for removing the noisy Raman signal and achieving higher SNR. This result may be helpful in further improving the performance of integrated Raman spectrometers and research on miniaturized instruments. In consideration of signal to noise ratio(SNR) is related to signal intensity and noise level, we hope to improve SNR through optic structure optimization and develop a denoising algorithm. A cylindrical lens has been used to enhance intensity. The convolutional denoising autoencoder (CDAE) algorithm is acquired for the reduction of the noise. image The signal‐noise ratio plays a key role in acquiring plentiful chemical structural information in the Raman spectrometer. The miniature spectrometer is generally compact at the expense of performance. In this work, we proposed a compact, signal‐to‐noise ratio (SNR) enhancement of the Raman spectrometer by the optimization of optical structure and a noise reduction method. Concerning its optical structure, the Raman spectrometer is increasing the intensity by adding an off‐the‐shelf cylindrical lens. On the other side of the algorithm, a relevant automatic denoising method of convolutional denoising autoencoder (CDAE) is proposed to further advance the SNR in Raman spectra without manual intervention. The results indicate the performance of the compact Raman spectrometer could increase to a certain extent by testing with 785 nm laser and Ne/Ar source. Besides, by using CDAE to deal with contaminated Raman spectra, a higher SNR is obtained. The results demonstrate that the improvement of the hardware and algorithm is effective for removing the noisy Raman signal and achieving higher SNR. This result may be helpful in further improving the performance of integrated Raman spectrometers and research on miniaturized instruments. In consideration of signal to noise ratio(SNR) is related to signal intensity and noise level, we hope to improve SNR through optic structure optimization and develop a denoising algorithm. A cylindrical lens has been used to enhance intensity. The convolutional denoising autoencoder (CDAE) algorithm is acquired for the reduction of the noise.
Author	Xu, Ying‐jie Zhi, Yu‐Liang Zeng, Yingjie Fan, Xian‐guang Nie, Ting Wang, Xin
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Snippet	The signal‐noise ratio plays a key role in acquiring plentiful chemical structural information in the Raman spectrometer. The miniature spectrometer is...
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SubjectTerms	Algorithms autoencoder convolutional neural network Czerny‐Turner denoising Noise Noise reduction Optimization Raman spectra Raman spectrometer Raman spectroscopy Spectrometers
Title	Signal‐to‐noise ratio enhancement for Raman spectra based on optimized Raman spectrometer and convolutional denoising autoencoder
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