Abstract

Increasingly voluminous Fourier transform infrared (FT-IR) spectroscopic imaging data sets are being generated with the advent of both faster array detectors and the implementation of time-resolved imaging techniques, resulting in data processing becoming the limiting step in visualizing sample heterogeneity and temporal profile evolution. We report the application of a Gram–Schmidt vector orthogonalization procedure in interferogram space to provide a significant time saving advantage in processing of one to two orders of magnitude in comparison to conventional spectral processing. Illustrative data from human skin biopsies and from dynamic molecular reorganizations within liquid crystalline microdomains is employed to discuss the capabilities and limitations of this information-extraction approach.

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