期刊论文

Liu, Hai

英文

Measurement Science And Technology

0957-0233

2015

26

8

085502

10.1088/0957-0233/26/8/085502

National Social Science Fund of China [14BGL131]; National Key Technology Research and Development ProgramNational Key Technology R&D Program [2013BAH72B01, 2013BAH18F02]; Self-determined Research Funds of CCNU from the Colleges 'basic Research and Operation of MOE [CCNU15A05009, CCNU15A05010, CCNU14A05020]; Scientific R&D Project of State Education Ministry and China Mobile [MCM20121061]; Hubei province natural science foundationNatural Science Foundation of Hubei Province [2013CFB209]; Project of the Program for New Century Excellent Talents in University [NCET-11-0654]; Chinese Ministry of EducationMinistry of Education, China

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Raman spectrum often suffers from band overlap and Poisson noise. This paper presents a new blind Poissonian Raman spectrum reconstruction method, which incorporates the L0-sparse prior together with the total variation constraint into the maximum a posteriori framework. Furthermore, the greedy analysis pursuit algorithm is adopted to solve the L0-based minimization problem. Simulated and real spectrum experimental results show that the proposed method can effectively preserve spectral structure and suppress noise. The reconstructed Raman spectra are easily used f...