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 Citationer (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.

Originalsprog	Engelsk
Tidsskrift	Analytica Chimica Acta
Vol/bind	896
Sider (fra-til)	34-51
Antal sider	18
ISSN	0003-2670
DOI	https://doi.org/10.1016/j.aca.2015.09.030
Status	Udgivet - 8 okt. 2015

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10.1016/j.aca.2015.09.030

Citationsformater

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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.",

author = "{Amigo Rubio}, {Jose Manuel} and Hamid Babamoradi and {Elcoroaristizabal Martin}, Saioa",

year = "2015",

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doi = "10.1016/j.aca.2015.09.030",

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AU - Amigo Rubio, Jose Manuel

AU - Babamoradi, Hamid

AU - Elcoroaristizabal Martin, Saioa

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Y1 - 2015/10/8

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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.

U2 - 10.1016/j.aca.2015.09.030

DO - 10.1016/j.aca.2015.09.030

M3 - Journal article

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VL - 896

SP - 34

EP - 51

JO - Analytica Chimica Acta

JF - Analytica Chimica Acta

ER -

Hyperspectral image analysis. A tutorial

Abstract

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