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Proceedings Paper

Photoacoustic signals denoising of the glucose aqueous solutions using an improved wavelet threshold method
Author(s): Zhong Ren; Guodong Liu; Zhihua Xiong
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Paper Abstract

The photoacoustic signals denoising of glucose is one of most important steps in the quality identification of the fruit because the real-time photoacoustic singals of glucose are easily interfered by all kinds of noises. To remove the noises and some useless information, an improved wavelet threshld function were proposed. Compared with the traditional wavelet hard and soft threshold functions, the improved wavelet threshold function can overcome the pseudo-oscillation effect of the denoised photoacoustic signals due to the continuity of the improved wavelet threshold function, and the error between the denoised signals and the original signals can be decreased. To validate the feasibility of the improved wavelet threshold function denoising, the denoising simulation experiments based on MATLAB programmimg were performed. In the simulation experiments, the standard test signal was used, and three different denoising methods were used and compared with the improved wavelet threshold function. The signal-to-noise ratio (SNR) and the root-mean-square error (RMSE) values were used to evaluate the performance of the improved wavelet threshold function denoising. The experimental results demonstrate that the SNR value of the improved wavelet threshold function is largest and the RMSE value is lest, which fully verifies that the improved wavelet threshold function denoising is feasible. Finally, the improved wavelet threshold function denoising was used to remove the noises of the photoacoustic signals of the glucose solutions. The denoising effect is also very good. Therefore, the improved wavelet threshold function denoising proposed by this paper, has a potential value in the field of denoising for the photoacoustic singals.

Paper Details

Date Published: 19 October 2016
PDF: 9 pages
Proc. SPIE 10153, Advanced Laser Manufacturing Technology, 101530A (19 October 2016); doi: 10.1117/12.2244281
Show Author Affiliations
Zhong Ren, Jiangxi Science and Technology Normal Univ. (China)
Nanchang Univ. (China)
Guodong Liu, Jiangxi Science and Technology Normal Univ. (China)
Zhihua Xiong, Jiangxi Science and Technology Normal Univ. (China)


Published in SPIE Proceedings Vol. 10153:
Advanced Laser Manufacturing Technology
Bingheng Lu; Huaming Wang, Editor(s)

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