Including noise characteristics in MCR to improve mapping and component extraction from spectral images-Reference-Cited by-同舟云学术

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Including noise characteristics in MCR to improve mapping and component extraction from spectral images

Published:2016-04 Issue: Volume:153 Page:40-50
ISSN:0169-7439
Container-title:Chemometrics and Intelligent Laboratory Systems
language:en
Short-container-title:Chemometrics and Intelligent Laboratory Systems

Author:

Lavoie Francis B.,Braidy Nadi,Gosselin Ryan

Funder

NSERC

Publisher

Elsevier BV

Subject

Spectroscopy,Process Chemistry and Technology,Computer Science Applications,Software,Analytical Chemistry

Reference42 articles.

1. Techniques and Applications of Hyperspectral Image Analysis;Grahn,2007

2. Multivariate curve resolution: a review of advanced and tailored applications and challenges;Ruckebusch;Anal. Chim. Acta,2013

3. Handbook of Chemometrics and Qualimetrics: Handbook of Chemometrics and Qualimetrics: Part A;Massart,1997

4. Principal Component Analysis;Jolliffe,2002

5. Accounting for Poisson noise in the multivariate analysis of ToF-SIMS spectrum images;Keenan;Surf. Interface Anal.,2004

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