Abstract

The task of proper baseline or continuum removal is common to nearly all types of spectroscopy. Its goal is to remove any portion of a signal that is irrelevant to features of interest while preserving any predictive information. Despite the importance of baseline removal, median or guessed default parameters are commonly employed, often using commercially available software supplied with instruments. Several published baseline removal algorithms have been shown to be useful for particular spectroscopic applications but their generalizability is ambiguous. The new Custom Baseline Removal (Custom BLR) method presented here generalizes the problem of baseline removal by combining operations from previously proposed methods to synthesize new correction algorithms. It creates novel methods for each technique, application, and training set, discovering new algorithms that maximize the predictive accuracy of the resulting spectroscopic models. In most cases, these learned methods either match or improve on the performance of the best alternative. Examples of these advantages are shown for three different scenarios: quantification of components in near-infrared spectra of corn and laser-induced breakdown spectroscopy data of rocks, and classification/matching of minerals using Raman spectroscopy. Software to implement this optimization is available from the authors. By removing subjectivity from this commonly encountered task, Custom BLR is a significant step toward completely automatic and general baseline removal in spectroscopic and other applications.

© 2017 The Author(s)

Removing baseline flame’s spectrum by using advanced recovering spectrum techniques

Luis Arias, Daniel Sbarbaro, and Sergio Torres
Appl. Opt. 51(25) 6111-6116 (2012)

Baseline correction method based on doubly reweighted penalized least squares

Degang Xu, Song Liu, Yaoyi Cai, and Chunhua Yang
Appl. Opt. 58(14) 3913-3920 (2019)

Baseline correction for Raman spectra using a spectral estimation-based asymmetrically reweighted penalized least squares method

Yixin Guo, Weiqi Jin, Weilin Wang, Yuqing He, and Su Qiu
Appl. Opt. 62(18) 4766-4776 (2023)

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

Andrew Atiogbe Huzortey, Benjamin Anderson, and Alfred Owusu
OSA Continuum 4(9) 2468-2480 (2021)

Prescription AR: a fully-customized prescription-embedded augmented reality display

Jui-Yi Wu and Jonghyun Kim
Opt. Express 28(5) 6225-6241 (2020)