2013
DOI: 10.1039/c3ja50239b
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Wavelet denoising method for laser-induced breakdown spectroscopy

Abstract: aThe wavelet threshold denoising method is an effective noise suppression approach for noisy laser-induced breakdown spectroscopy spectrum. The wavelet threshold denoising method is influenced by several key issues such as the choice of wavelet, the choice of decomposition level, threshold selection, and the choice of thresholding functions. In this paper, the double threshold optimization models of semi-soft thresholding function are established firstly. Next, on the basis of grey relational analysis and Eucl… Show more

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Cited by 46 publications
(20 citation statements)
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“…Zhang et al utilized WTD with double thresholds correction scheme for noise suppression, and the optimal decomposition level was obtained by the white noise testing method [24]. When the decomposition level (DL) is too small, the power compression of the useful signal is not obvious so that the result of noise reduction is not ideal; when DL is too excessive, the obvious power compression of the useful signal causes the loss of useful information and results in the decreased of the SNR and the increased of the mean square error (MSE).…”
Section: Introductionmentioning
confidence: 99%
“…Zhang et al utilized WTD with double thresholds correction scheme for noise suppression, and the optimal decomposition level was obtained by the white noise testing method [24]. When the decomposition level (DL) is too small, the power compression of the useful signal is not obvious so that the result of noise reduction is not ideal; when DL is too excessive, the obvious power compression of the useful signal causes the loss of useful information and results in the decreased of the SNR and the increased of the mean square error (MSE).…”
Section: Introductionmentioning
confidence: 99%
“…Therefore, using the appropriate data processing methods to reduce spectra noise is very desirable, especially for liquid samples. Recently, Schlenke et al (2012) and Zhang et al (2013a) carried out theoretical studies on LIBS data's de-noising using wavelet theory. They have shown significant improvements for LOD and signal-to-noise ratio after data processing.…”
Section: Data Processingmentioning
confidence: 99%
“…Wiens et al used WTD for removing noise and obtained satisfying denoising results; however, they gave no details about the method used to select the optimal DL. Zhang et al constructed double‐threshold optimization models for wavelet denoising, and the model was verified by means of the denoising effect of both the synthetic and observed LIBS signal. When the DL is too small, the power compression of the useful signal is not obvious; thus, the result of noise reduction is not ideal.…”
Section: Spectral Data Preprocessingmentioning
confidence: 99%