A study of infrared spectroscopy de-noising based on LMS adaptive filter

Jia-qing Mo; Xiao-yi Lv; Xiao Yu

doi:10.1117/12.2205800

14 December 2015 A study of infrared spectroscopy de-noising based on LMS adaptive filter

Jia-qing Mo, Xiao-yi Lv, Xiao Yu

Proceedings Volume 9815, MIPPR 2015: Remote Sensing Image Processing, Geographic Information Systems, and Other Applications; 98151S (2015) https://doi.org/10.1117/12.2205800
Event: Ninth International Symposium on Multispectral Image Processing and Pattern Recognition (MIPPR2015), 2015, Enshi, China

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.

Citation Download Citation

Jia-qing Mo, Xiao-yi Lv, and Xiao Yu "A study of infrared spectroscopy de-noising based on LMS adaptive filter", Proc. SPIE 9815, MIPPR 2015: Remote Sensing Image Processing, Geographic Information Systems, and Other Applications, 98151S (14 December 2015); https://doi.org/10.1117/12.2205800

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