Hyperspectral image analysis. A tutorial

Jose Manuel Amigo Rubio; Hamid Babamoradi; Saioa Elcoroaristizabal Martin

doi:10.1016/j.aca.2015.09.030

Hyperspectral image analysis. A tutorial

Jose Manuel Amigo Rubio, Hamid Babamoradi, Saioa Elcoroaristizabal Martin

Food Analytics and Biotechnology

122 Citations (Scopus)

Abstract

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.

Original language	English
Journal	Analytica Chimica Acta
Volume	896
Pages (from-to)	34-51
Number of pages	18
ISSN	0003-2670
DOIs	https://doi.org/10.1016/j.aca.2015.09.030
Publication status	Published - 8 Oct 2015

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title = "Hyperspectral image analysis. A tutorial",

abstract = "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.",

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AU - Babamoradi, Hamid

AU - Elcoroaristizabal Martin, Saioa

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AB - 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.

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JO - Analytica Chimica Acta

JF - Analytica Chimica Acta

ER -

Hyperspectral image analysis. A tutorial

Abstract

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