Joint sparse representation and denoising method for Raman spectrum

作     者：Fang, Zheng Tao, Yu Wang, Wen Zhang, Wenxin Duan, Lingfeng Liu, Ying Yan, Changchun Qu, Lulu Han, Caiqin 

作者机构：Jiangsu Normal Univ Sch Phys & Elect Engn Jiangsu Key Lab Adv Laser Mat & Devices Xuzhou Jiangsu Peoples R China Changshu Inst Technol Sch Phys & Elect Engn Changshu Jiangsu Peoples R China Jiangsu Normal Univ Jiangsu Collaborat Innovat Ctr Adv Laser Technol Xuzhou 221116 Jiangsu Peoples R China Hangzhou Normal Univ Qianjiang Coll Hangzhou Zhejiang Peoples R China Jiangsu Normal Univ Sch Chem & Mat Sci Xuzhou Jiangsu Peoples R China 

出 版 物：《JOURNAL OF RAMAN SPECTROSCOPY》 (喇曼光谱学杂志)

年 卷 期：2018年第49卷第12期

页      面：1972-1977页

核心收录：

学科分类：070207[理学-光学] 07[理学] 08[工学] 0703[理学-化学] 0803[工学-光学工程] 0702[理学-物理学] 

基　　金：Natural Science Foundation of Jiangsu Province [BK20150227, BK20151164] National Natural Science Foundation of China [21505057, 61575087, 61771227] 

主　　题：denoise algorithm orthogonal matching pursuit Raman spectroscopy sparse representation 

摘      要：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.