Richardson–Lucy blind deconvolution of spectroscopic data with wavelet regularization

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 convenient for extracting the spectral feature and interpreting the unknown chemical mixtures.