Hyperspectral image analysis. A tutorial

Research output: Contribution to journal › Journal article › Research › peer-review

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Hyperspectral image analysis. A tutorial. / Amigo Rubio, Jose Manuel; Babamoradi, Hamid; Elcoroaristizabal Martin, Saioa.

In: Analytica Chimica Acta, Vol. 896, 2015, p. 34-51.

Research output: Contribution to journal › Journal article › Research › peer-review

Harvard

Amigo Rubio, JM, Babamoradi, H & Elcoroaristizabal Martin, S 2015, 'Hyperspectral image analysis. A tutorial', Analytica Chimica Acta, vol. 896, pp. 34-51. https://doi.org/10.1016/j.aca.2015.09.030

APA

Amigo Rubio, J. M., Babamoradi, H., & Elcoroaristizabal Martin, S. (2015). Hyperspectral image analysis. A tutorial. Analytica Chimica Acta, 896, 34-51. https://doi.org/10.1016/j.aca.2015.09.030

Vancouver

Amigo Rubio JM, Babamoradi H, Elcoroaristizabal Martin S. Hyperspectral image analysis. A tutorial. Analytica Chimica Acta. 2015;896:34-51. https://doi.org/10.1016/j.aca.2015.09.030

Author

Amigo Rubio, Jose Manuel ; Babamoradi, Hamid ; Elcoroaristizabal Martin, Saioa. / Hyperspectral image analysis. A tutorial. In: Analytica Chimica Acta. 2015 ; Vol. 896. pp. 34-51.

Bibtex

@article{76e2abfd21a047589dea799609f44828,
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",
note = "Copyright {\textcopyright} 2015 Elsevier B.V. All rights reserved.",
year = "2015",
doi = "10.1016/j.aca.2015.09.030",
language = "English",
volume = "896",
pages = "34--51",
journal = "Analytica Chimica Acta",
issn = "0003-2670",
publisher = "Elsevier",

}

RIS

TY - JOUR

T1 - Hyperspectral image analysis. A tutorial

AU - Amigo Rubio, Jose Manuel

AU - Babamoradi, Hamid

AU - Elcoroaristizabal Martin, Saioa

N1 - Copyright © 2015 Elsevier B.V. All rights reserved.

PY - 2015

Y1 - 2015

N2 - 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.

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

C2 - 26481986

VL - 896

SP - 34

EP - 51

JO - Analytica Chimica Acta

JF - Analytica Chimica Acta

SN - 0003-2670

ER -

ID: 147580692