Joint sparse representation and denoising method for Raman spectrum. (23rd September 2018)

• Record Type: Journal Article
• Authors: Fang, Zheng; Tao, Yu; Wang, Wen; Zhang, Wenxin; Duan, Lingfeng; Liu, Ying; Yan, Changchun; Qu, Lulu; Han, Caiqin
• Is Part Of: Journal of Raman spectroscopy. Volume 49:Number 12(2018)
• Page Start: 1972
• Page End: 1977
• Publication Date: 2018-09-23
• Subjects: denoise algorithm -- orthogonal matching pursuit -- Raman spectroscopy -- sparse representation; Raman spectroscopy -- Periodicals; 535.846
• DOI: 10.1002/jrs.5485
• Languages: English
• ISSNs: 0377-0486

Abstract

Abstract: A new method based on joint sparse representation is developed to recover the peak information from high‐noise Raman signal. This method used the sparsity of Raman spectrum to recover the signals and preserve its useful peak information. The peak information is then reconstructed by using an orthogonal matching pursuit algorithm. The joint sparse representation method is found to be an effective approach to analyze the Raman spectrum, especially Raman spectrum that have high noise, thus improving the detection limit of Raman spectroscopy. Experimental results demonstrate that this approach is better than other approaches in case of low signal‐to‐noise ratios. Abstract : Noise is a severe problem in Raman spectral analysis, which often obscures the characteristic Raman bands. We propose a spectral processing method using joint sparse representation recovery by the orthogonal matching pursuit (OMP) algorithm. The method has strong anti‐noise capability, and the limit of detection (LOD) can be improved. The LOD of 4‐chloroaniline was determined to be and obtained after processing.