Hyperspectral image analysis. A tutorial.
This tutorial aims at providing guidelines and practical tools to assist with the analysis of hyperspectral images. Topics like hyperspectral image acquisition, image pre-processing, multivariate exploratory analysis, hyperspectral image resolution, classification and final digital image processing will be exposed, and some guidelines given and discussed. Due to the broad character of current applications and the vast number of multivariate methods available, this paper has focused on an industrial chemical framework to explain, in a step-wise manner, how to develop a classification methodology to differentiate between several types of plastics by using Near infrared hyperspectral imaging and Partial Least Squares - Discriminant Analysis. Thus, the reader is guided through every single step and oriented in order to adapt those strategies to the user's case.
Spectroscopy and Chemometrics Group, Department of Food Sciences, Faculty of Science, University of Copenhagen, Rolighedsvej 30, Frederiksberg C DK-1958, Denmark. Electronic address: jmar@food.ku.dk.
José Manuel
JM
Amigo
Spectroscopy and Chemometrics Group, Department of Food Sciences, Faculty of Science, University of Copenhagen, Rolighedsvej 30, Frederiksberg C DK-1958, Denmark.
Hamid
H
Babamoradi
Spectroscopy and Chemometrics Group, Department of Food Sciences, Faculty of Science, University of Copenhagen, Rolighedsvej 30, Frederiksberg C DK-1958, Denmark; Chemical and Environmental Engineering Department, School of Engineering, University of the Basque Country, Alameda de Urquijo s/n, E-48013 Bilbao, Spain.
Saioa
S
Elcoroaristizabal
Chemometrics; Classification; Flame retardant; Hyperspectral; Near infrared; Plastic sorting