Supervised and Penalized Baseline Correction

Erik Andries; Ramin Nikzad-Langerodi

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arXiv · 2310.18306

Supervised and Penalized Baseline Correction

Erik Andries·Ramin Nikzad-Langerodi

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Abstract

Spectroscopic measurements can show distorted spectral shapes arising from a mixture of absorbing and scattering contributions. These distortions (or baselines) often manifest themselves as non-constant offsets or low-frequency oscillations. As a result, these baselines can adversely affect analytical and quantitative results. Baseline correction is an umbrella term where one applies pre-processing methods to obtain baseline spectra (the unwanted distortions) and then remove the distortions by differencing. However, current state-of-the art baseline correction methods do not utilize analyte concentrations even if they are available, or even if they contribute significantly to the observed spectral variability. We examine a class of state-of-the-art methods (penalized baseline correction) and modify them such that they can accommodate a priori analyte concentrations such that prediction can be enhanced. Performance will be assessed on two near infra-red data sets across both classical penalized baseline correction methods (without analyte information) and modified penalized baseline correction methods (leveraging analyte information).

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Erik Andries, Ramin Nikzad-Langerodi. 2023-10-27. Supervised and Penalized Baseline Correction. https://arxiv.org/abs/2310.18306

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