An automated approach for fringe frequency estimation and removal in infrared spectroscopy and hyperspectral imaging of biological samples. Issue 12 (20th September 2021) - Solheim, Johanne Heitmann; Borondics, Ferenc; Zimmermann, Boris; Sandt, Christophe; Muthreich, Florian; Kohler, Achim
Abstract: In infrared spectroscopy of thin film samples, interference introduces distortions in spectra, commonly referred to as fringes. Fringes may alter absorbance peak ratios, which hampers the spectral analysis. We have previously introduced extended multiplicative signal correction (EMSC) for fringes correction. In the current article, we provide a robust open‐source algorithm for fringe correction in infrared spectroscopy and propose several improvements to the Fringe EMSC model. The suggested algorithm achieves a more precise fringe frequency estimation by mean centering of the measured spectrum and applying a window function prior to the Fourier transform. It selects two frequencies from a user defined number of maxima in the Fourier domain. The improved Fringe EMSC algorithm is validated on two experimental datasets, one of them being a hyperspectral image. Techniques for separating sample spectra from background spectra in hyperspectral images, and techniques to identify spectra affected by fringes are also provided. Abstract : In infrared spectroscopy of thin film samples, multiple internal reflection causes sine wave signatures in the absorbance spectra. These signatures are referred to as fringes, and they impede the chemical analysis of the samples. In this study, an algorithm based on extended multiplicative signal correction (EMSC) is presented for estimating and removing interference fringes in infrared spectroscopy and imaging. The Fringe EMSC algorithm is made openly accessible on GitHub.