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Proceedings Paper

Infrared spectral data denoising method based on stationary wavelet transform
Author(s): Jingguo Zong; Hanlin Qin; Delian Liu; Shengchun Yuan
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Paper 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.

Paper Details

Date Published: 15 October 2012
PDF: 5 pages
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); doi: 10.1117/12.978284
Show Author Affiliations
Jingguo Zong, Xidian Univ. (China)
Hanlin Qin, Xidian Univ. (China)
Delian Liu, Xidian Univ. (China)
Shengchun Yuan, Xidian Univ. (China)


Published in SPIE Proceedings Vol. 8419:
6th International Symposium on Advanced Optical Manufacturing and Testing Technologies: Optoelectronic Materials and Devices for Sensing, Imaging, and Solar Energy
Yadong Jiang; Junsheng Yu; Zhifeng Wang, Editor(s)

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