Research On Raman Spectral Preprocessing And Raman Imaging Interpolation Algorithm

Noise and fluorescent background are two major problems for acquiring and analyzing Raman spectra from samples,which blur Raman spectra and make Raman detection or imaging difficult.In this paper,a novel algorithm based on wavelet transform that contains denoising and baseline correction is presented to automatically extract Raman signal.For the denoising section,the improved conventional scale correlation denoising method is proposed.The baseline correction section,which is performed after denoising,basically consists of five aspects: 1)Detection of peak position;2)Approximate second derivative calculation based on continuous wavelet transform using Haar wavelet function is performed to find peaks and background areas;3)The threshold is estimated from the peak intensive area(PIA)for identification of peaks;4)Correction of endpoints,spectral peaks and peak position;5)Determine the endpoints of the peak after subtracting the background.We tested this algorithm for simulated and experimental Raman spectra,and a satisfactory denoising effect and a good capability to correct background are observed.It is noteworthy that this algorithm requires few human interventions,which enables automatically denoising and background removal.Raman imaging is an important option for Raman detection because it provides rich information of the concentration,distribution and changes of a certain substance component in the detection area.Raman spectrum for imaging construction obtained through experiments usually contains a limited number of pixels and the imaging effect is poor,so it is urgent to interpolate it.Based on the special significance of Gaussian beam in Raman imaging,here we theoretically propose a new interpolation method which is suitable for Raman imaging.After setting a specific acquisition interval to make sure that the acquisition area at the adjacent collection point is tangent,based on the information contained at the collection point for interpolation,we design a function which meets the interpolation requirement.By comparing the imaging before and after interpolation,it is found that the new interpolation method has a good amplification effect.By using this interpolation amplification the acquisition time can be greatly saved for imaging construction with similar resolution ratio and information,thereby saving experimental resources.Here,we present the interpolation method in detail by taking double magnification of image as an example.In reality,the corresponding interpolation amplification can be performed according to the specific requirements.