A method to perform an automatic and quick recognition of peak and baseline regions in a spectrum is presented. Its characteristics make it especially suitable for the treatment of large amounts of data of similar type, such as those coming from a high-throughput instrument. This algorithm is based on the Continuous Wavelet Transform and is effective on any kind of spectrum in which the baseline is smoother than the rest of the signal. Its parameters are automatically determined using the criteria of Shannon entropy and statistical distribution of noise. If the data are properly grouped into sets of analogous measurements, no user intervention is required. This method was assessed on simulated spectra with different noise levels and baseline amplitudes. It can be combined with various fitting methods for baseline correction. In this study, it was used together with an iterative polynomial fitting to successfully process a real Raman image of 40000 pixels in about 2 1/2 hours.
|Publication status||Published - 2013|
|Event||International Conference on Analytical Sciences and Spectroscopy - Mont Tremblant, Canada|
Duration: 26 Jun 2013 → 28 Jun 2013
Conference number: 59
|Conference||International Conference on Analytical Sciences and Spectroscopy|
|Period||26/06/2013 → 28/06/2013|