Denoising Of Single Scan Raman Spectroscopy Signals

Noise reduction algorithms for improving Raman spectroscopy signals while preserving signal information were implemented. Algorithms based on Wavelet denoising and Kalman filtering are presented in this work as alternatives to the well-known Savitky-Golay algorithm. The Wavelet and Kalman algorithms were designed based on the noise statistics of real signals acquired using CCD detectors in dispersive spectrometers. Experimental results show that the random noise generated in the data acquisition is governed by sub-Poisson statistics. The proposed algorithms have been tested using both real and synthetic data, and were compared using Mean Squared Error (MSE) and Infinity Norm (L-infinity) to each other and to the standard Savitky-Golay algorithm. Results show that denoising based on Wavelets performs better in both the MSE and L-infinity the sense.