Robust Raman Spectral Decomposition with Wavenumber Shifts Parametric Modelling

摘要

Nonlinearity in Raman spectral mixtures caused by wavenumber shifts, has been investigated in this paper. The spectral shifts are mainly caused by the existence of multiple chemicals in the mixtures, with complex molecular interactions, which can change the spectral features of each constituent. While such non-linear behaviour may be negligible in some mixtures, it may lead to incorrect identification of chemicals in some instances. We investigate some real spectra and demonstrate the nature of such nonlinearity in Raman spectra. We then mathematically formulate such spectral behaviour and present an approach to compensate the nonlinearity artifacts. The nonlinearity has been modelled as a smooth transition in a parametric space, which can be locally modelled using first order approximation. Such a first order approximation can be translated to some augmented spectral libraries to be used with a linear generative model. A convex sparse approximation program, with nonlinearity considerations, has finally been introduced to decompose the spectral mixtures. Such decomposition has been used for chemical fingerprinting and quantification. The effect of new approach has been demonstrated with some real and synthetic spectra.