Interpolated inverse discrete wavelet transforms in additive and non-additive spectral background corrections

We demonstrate the applicability of using interpolated inverse discrete wavelet transforms as a general tool for modeling additive or multiplicative background or error signals in spectra. Additionally, we propose an unsupervised way of estimating the optimal wavelet basis along with the model parameters. We apply the method to experimental Raman spectra of phthalocyanine blue, aniline black, naphthol red, pigment yellow 150, and pigment red 264 pigments to remove their additive background and to CARS spectra of adenosine phosphate, fructose, glucose, and sucrose to remove their multiplicative background signals.Published by Optica Publishing Group under the terms of the Creative Commons Attribution 4.0 License. Further distribution of this work must maintain attribution to the author(s) and the published article's title, journal citation, and DOI.