Raman Spectral Data De-noising based on Wavelet Analysis

Nowadays, most analytical instruments in modern laboratories are computerized, partly owing to the rapid development of advanced micro-electronic technology. Digitalized spectroscopic data can be exported from these instruments very easily for subsequent signal processing. Raman Spectroscopy is widely recognized as powerful, non-destructive techniques for characterizing materials. The key to realize the qualitative and quantitative analysis is data processing and analysis. But signals in Raman spectral analysis often have noise, which greatly influences the achievement of accurate analytical results. The de-noising of Raman spectral is an important part of de-noising. Wavelet functions are localized both time and frequency (or scale) and in time, via dilations and translations of the mother wavelet, respectively, both time and frequency information are maintained after transformation. This paper presents wavelet based de-noising method for Raman Spectral data of Sr2+ modified PMN-PZT and compared the results with Daubechies, Coiflet, Symlet.