Project of the Program for New Century Excellent Talents in University [NCET-11-0654]; National Key Technology Research and Development ProgramNational Key Technology R&D Program [2013BAH72B01, 2013BAH18F02]; Scientific R & D Project of State Education Ministry and China Mobile [MCM20121061]; National Social Science Fund of China [14BGL131]; Chinese Ministry of EducationMinistry of Education, China
机构署名：
本校为第一且通讯机构
院系归属：
国家数字化学习工程技术研究中心
摘要：
In this work, we introduce a blind deconvolution approach with wavelet regularization for the Raman spectrum and total variation regularization for instrument function. The proposed algorithm can effectively suppress the Poisson noise as well as preserve the spectral structure information. Moreover, the split Bregman method is adopted to solve the proposed model. The comparative results on the simulated and measured Raman spectra show that the wavelet-based method outperforms the conventional methods. The deconvolution Raman spectrum is more co...
