Assessment of Essential Information in the Fourier Domain to Accelerate Raman Hyperspectral Microimaging.

ABSTRACT: In the context of multivariate curve resolution (MCR) and spectral unmixing, essential information (EI) corresponds to the most linearly dissimilar rows and/or columns of a two-way data matrix. In recent works, the assessment of EI has been revealed to be a very useful practical tool to select the most relevant spectral information before MCR analysis, key features being speed and compression ability. However, the canonical approach relies on the principal component analysis to evaluate the convex hull that encapsulates the data structure in the normalized score space. This implies that the evaluation of the essentiality of each spectrum can only be achieved after all the spectra have been acquired by the instrument. This paper proposes a new approach to extract EI in the Fourier domain (E

SUBMITTER: Coic L 

PROVIDER: S-EPMC10603605 | biostudies-literature | 2023 Oct

REPOSITORIES: biostudies-literature