Algorithms and Performance Bounds for Chemical Identification under a Poisson Model for Raman Spectroscopy

Abstract – Many methods have previously been devised to estimate the relative amounts of chemicals present in a mea-sured Raman spectrum. However, relatively little work has been done on developing physics-based probabilistic models for the measurement system. Drawing from previous work in astronomical image restoration, we model the acquired data based on the physics of two key components in our Raman instrumentation: the spectrometer and the charge-coupled device (CCD) detector. Under this model, we de-rive Cramér-Rao lower bounds for the mixing coefficients of the target spectra. This bound is compared against the performance of several classification algorithms