期刊论文

Liu, Hai

英文

Applied Optics

1559-128X

2018

57

22

6461-6469

10.1364/AO.57.006461

National Natural Science Foundation of China (NSFC) (61505064); Hong Kong Scholars Programs (XJ2016063); Natural Science Foundation of Hubei Province (2016CFB497); National Key Research and Development Program (2017YFB1401301, 2017YFB1401303, 2017YFB1401305); Specific Funding for Education Science Research by Self-determined Research Funds of CCNU (CCNU18ZDPY10, CCNU18QN008); Cultivating Excellent Doctoral Dissertations Program of CCNU (2017YBZZ009). The authors thank the handling editor and anonymous reviewers for their helpful comments and suggestions. Also, we thank Prof. Zhu Hu for providing the FSD and φHS methods’ Matlab source codes.

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Raman spectroscopy often suffers from the problems of band overlap and random noise. In this work, we develop a nonlocal low-rank regularization (NLR) approach toward exploiting structured sparsity and explore its applications in Raman spectral deconvolution. Motivated by the observation that the rank of a ground-truth spectrum matrix is lower than that of the observed spectrum, a Raman spectral deconvolution model is formulated in our method to regularize the rank of the observed spectrum by total variation regularization. Then, an effective o...