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Asymmetric least squares for multiple spectra baseline correction - ScienceDirect
Source: sciencedirect.com
Article summary:
1. Fourier transform infrared spectroscopy is a valuable tool for qualitative and quantitative analysis, but the presence of baselines can hamper interpretation.
2. There are numerous proposals for automatic baseline correction, such as derivative methods, frequency analysis based methods, wavelet transform methods, morphological operators, curve fitting methods, and background estimation methods.
3. Recently, an asymmetric least squares smoothing algorithm has been proposed to estimate a baseline from multiple spectra by penalizing the differences in the baseline corrected spectra.
Article analysis:
The article provides a comprehensive overview of various approaches to automatic baseline correction for Fourier transform infrared spectroscopy. The article is well-structured and clearly explains each method in detail with relevant references provided for further reading. The authors also provide an introduction to their proposed algorithm which uses asymmetric least squares smoothing to estimate a baseline from multiple spectra by penalizing the differences in the baseline corrected spectra.
The article does not appear to be biased or one-sided in its reporting of the various approaches to automatic baseline correction. All potential risks associated with each approach are noted and discussed in detail. Furthermore, all claims made are supported by evidence from relevant sources and there are no unsupported claims or missing points of consideration. The authors have also explored counterarguments where appropriate and presented both sides of the argument equally without any promotional content or partiality.
In conclusion, this article is reliable and trustworthy due to its comprehensive coverage of various approaches to automatic baseline correction as well as its unbiased reporting and lack of unsupported claims or missing points of consideration.