That best details the filtering performance for alpha and lambdaД«oth set to 1.0 (shown by the dashed lines in panels in aвЂ“d). (eвЂ“h) Plots show the most challenging spectrum subregion A rapid loss of correlation and onset of anДЄnti-correlation is observed with increasing values of alpha and (d) The correlationД¬oefficients shown are those between P6 and P7, both inferred in theДЇiltered spectra. Not separated, thus the correlation coefficients shown are thoseД«etween the P6 inferred in the filtered spectra and the P6 present (c) The overlapping P6вЂ“P7 peaks in the filtered spectra were Target spectra increased with increasing values of both alpha and (b) The number of peaks in theДЇiltered spectra at variance with those present in the corresponding The separation between peaks in the filtered spectra with larger

(a) Increases in alpha had a predominant effect on (aвЂ“d) Error surfaces obtained by varying the parameters selected for Our efforts provided insight into the need for effective resolution enhancement approaches, the feasibility of these methods for automation, the nature of the problems currently limiting their use, and in particular those aspects that need improvement.ДЇityk Raman spectroscopy blind deconvolution chemical contrast images moving window multiple peak fitting node narrowing over-deconvolution pseudospectra resolution enhancement two-dimensional correlation spectroscopy. We conclude with a discussion of the particular benefits, drawbacks, and potential of these methods. We also determined the effects of the different resolution enhancement methods on 2D-COS and on chemical contrast image generation from mammalian cell spectra. High resolution spectra of glucose acquired with a narrow spectrometer slit were compared to ones using a wide slit that degraded the spectral resolution. We then investigated the efficacy of these methods to improve the resolution of measured Raman spectra. Improved spectral resolution was evaluated based on several criteria including the separation of overlapping peaks and the preservation of true peak intensities in resolution-enhanced spectra. We first applied the methods to varied synthetic spectra, each consisting of nine overlapping Voigt profile peaks. To investigate these issues, we implemented three novel resolution enhancement methods based on pseudospectra, over-deconvolution, and peak fitting to evaluate them along with three extant methods: node narrowing, blind deconvolution, and the general-purpose peak fitting program Fityk. Furthermore, there is a need for automated methods to apply to large numbers of varied hyperspectral data sets containing multiple overlapping peaks, and thus methods ideally suitable for diverse tasks. Though software-based resolution enhancement methods can be used to counter such problems, their performances often differ, thereby rendering some more suitable than others for specific tasks. This is particularly problematic for methods dependent on sparsity such as multivariate curve resolution and other spectral demixing as well as for two-dimensional correlation spectroscopy (2D-COS), multisource correlation analysis, and principal component analysis. Overlapping peaks in Raman spectra complicate the presentation, interpretation, and analyses of complex samples.

Fityk peak separation