Infrared spectral data denoising method based on stationary wavelet transform

Jingguo Zong; Hanlin Qin; Delian Liu; Shengchun Yuan

doi:10.1117/12.978284

15 October 2012 Infrared spectral data denoising method based on stationary wavelet transform

Jingguo Zong, Hanlin Qin, Delian Liu, Shengchun Yuan

Proceedings Volume 8419, 6th International Symposium on Advanced Optical Manufacturing and Testing Technologies: Optoelectronic Materials and Devices for Sensing, Imaging, and Solar Energy; 84192T (2012) https://doi.org/10.1117/12.978284
Event: 6th International Symposium on Advanced Optical Manufacturing and Testing Technologies (AOMATT 2012), 2012, Xiamen, China

Abstract

For the sake of effectively alleviating the effect of noise in infrared spectral data, a method of infrared spectral data denoising based on stationary wavelet transform is proposed in this paper. Firstly, stationary wavelet transform is adopted to decompose the original infrared spectral data, which extracts data of multi-scale specific characteristic. Secondly, according to difference between spectral signal and noise in different scales, the improved variational method is introduced to adjust each sub-band coefficients. Finally, denoised signal was reconstructed through inverse stationary wavelet transform. Several groups of experimental results are demonstrated that the proposed method not only effectively extract noise but also decreases Mean Squared Error and preserve character of signal. It can be utilized in the actual infrared spectral data denosing and achieved perfect effectiveness.

Citation Download Citation

Jingguo Zong, Hanlin Qin, Delian Liu, and Shengchun Yuan "Infrared spectral data denoising method based on stationary wavelet transform", Proc. SPIE 8419, 6th International Symposium on Advanced Optical Manufacturing and Testing Technologies: Optoelectronic Materials and Devices for Sensing, Imaging, and Solar Energy, 84192T (15 October 2012); https://doi.org/10.1117/12.978284

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