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Proceedings Paper

A study of infrared spectroscopy de-noising based on LMS adaptive filter
Author(s): Jia-qing Mo; Xiao-yi Lv; Xiao Yu
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Paper Abstract

Infrared spectroscopy has been widely used, but which often contains a lot of noise, so the spectral characteristic of the sample is seriously affected. Therefore the de-noising is very important in the spectrum analysis and processing. In the study of infrared spectroscopy, the least mean square (LMS) adaptive filter was applied in the field firstly. LMS adaptive filter algorithm can reserve the detail and envelope of the effective signal when the method was applied to infrared spectroscopy of breast cancer which signal-to-noise ratio (SNR) is lower than 10 dB, contrast and analysis the result with result of wavelet transform and ensemble empirical mode decomposition (EEMD). The three evaluation standards (SNR, root mean square error (RMSE) and the correlation coefficient (ρ)) fully proved de-noising advantages of LMS adaptive filter in infrared spectroscopy of breast cancer.

Paper Details

Date Published: 14 December 2015
PDF: 8 pages
Proc. SPIE 9815, MIPPR 2015: Remote Sensing Image Processing, Geographic Information Systems, and Other Applications, 98151S (14 December 2015); doi: 10.1117/12.2205800
Show Author Affiliations
Jia-qing Mo, Xinjiang Univ. (China)
Xiao-yi Lv, Xinjiang Univ. (China)
Academy of Military Medical Science (China)
Xiao Yu, Xinjiang Univ. (China)


Published in SPIE Proceedings Vol. 9815:
MIPPR 2015: Remote Sensing Image Processing, Geographic Information Systems, and Other Applications
Jianguo Liu; Hong Sun, Editor(s)

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