Raman spectra recovery using a second derivative technique and range independent baseline correction algorithm

Abstract

We report on a computational technique that recovers Raman peaks embedded in highly fluorescent contaminated spectra. The method uses a second derivative technique to identify the most intense Raman peak, and a modified Savisty Golay algorithm to filter and recover the embedded Raman peaks iteratively. This technique is an improvement on existing background removal algorithms in both performance and user objectivity.

UV-Nanoimprint Lithography for Predefined SERS Nanopatterns Which Are Reproducible at Low Cost and High Throughput

“…Each time, the SERS spectra were measured in five different locations on the chip, in the corners, and the center of the chip. A baseline correction was applied to the collected SERS spectra using a second derivative technique and range independent baseline correction algorithm discussed in Reference [ 31 ]. The SERS signal measured in five different locations of the substrate shows very good uniformity over the whole chip area ( Figure 6 b).…”

An adaptive extended Gaussian peak derivative reweighted penalised least squares method for baseline correction

“…The length of extended data N is 1/10 of the total length of raw spectral data M. The linear parts are obtained by expanding by linear tting of the rst N and last N data from raw spectra. The linear t is performed using eqn (13).…”

“…11 In recent years, several research results in BC have been presented. [12][13][14] Common BC methods include polynomial tting, 15 segmented tting, 16 derivative spectroscopy, 17 wavelet transformation, 18 moving-window averaging, 19 robust baseline estimation, 20 penalised least squares (PLS), 21 morphological operators, 22 sparse representation, 23 and deep learning. 24 These methods have been widely used in pre-processing of spectral data and have effectively improved the accuracy of spectral analysis.…”

Confocal Raman microscopy to evaluate anisotropic structures and hydration development. Methodological considerations

“…Polynomial fittings are predominantly applied in treatment of spectroscopic data, due to their efficiency and simplicity, yet experience is required in choosing a suitable polynomial order. 26,27 It is recommended to report which polynomial order and noise threshold is applied, to ensure reproducibility in Raman data processing. In this work, the 2nd polynomial with a noise threshold of 2, was found suitable for all line-and area scans, due to the interest in the evaluation of the water peak distribution.…”