Abstract

A hyperspectral image is a large dataset in which each pixel corresponds to a spectrum, thus providing high-quality detail of a sample surface. Hyperspectral images are thus characterised by dual information, spectral and spatial, which allows for the acquisition of both qualitative and quantitative information from a sample. A hyperspectral image, commonly known as a “hypercube”, comprises two spatial dimensions and one spectral dimension. The data of such a file contain both chemical and physical information. Such files need to be analysed with a computational “chemometric” approach in order to reduce the dimensionality of the data, while retaining the most useful spectral information. Time series hyperspectral imaging data comprise multiple hypercubes, each presenting the sample at a different time point, requiring additional considerations in the data analysis. This paper provides a step-by-step tutorial for time series hyperspectral data analysis, with detailed command line scripts in the Matlab and R computing languages presented in the supplementary data. The example time series data, available for download, are a set of time series hyperspectral images following the setting of a cement-based biomaterial. Starting from spectral pre-processing (image acquisition, background removal, dead pixels and spikes, masking) and pre-treatments, the typical steps encountered in time series hyperspectral image processing are then presented, including unsupervised and supervised chemometric methods. At the end of the tutorial paper, some general guidelines on hyperspectral image processing are proposed.

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  1. J.M. Amigo and H. Babamoradi, and S. Elcoroaristizabal. “Hyperspectral image analysis. A tutorial”, Anal. Chim. Acta  896, 34 (2015). doi: http://dx.doi.org/10.1016/j.aca.2015.09.030
  2. H. Huang and L. Liu, and M.O. Ngadi. “Recent developments in hyperspectral imaging for assessment of food quality and safety”, Sensors  14, 7248 (2014). doi: http://dx.doi.org/10.3390/s140407248
  3. Y. Tan, Y. Liu, Z. Zhao, and J.Z. Paxton, and L.M. Grover. “Synthesis and in vitro degradation of a novel magnesium oxychloride cement”, J. Biomed. Mater. Res. A  103, 194 (2014). doi: http://dx.doi.org/10.1002/jbm.a.35166
  4. Z. Li, and C.K. Chau. “Influence of molar ratios on properties of magnesium oxychloride cement”, Cement Concr. Res.  37, 866 (2007). doi: http://dx.doi.org/10.1016/j.cemconres.2007.03.015
  5. A. Gowen, F. Marini, C. Esquerre, C.P. O'Donnell, and G. Downey, and J. Burger. “Time series hyperspectral chemical imaging data: Challenges, solutions and applications”, Anal. Chim. Acta  705, 272 (2011). doi: http://dx.doi.org/10.1016/j.aca.2011.06.031
  6. A. Gowen, J. Burger, C. Esquerre, and G. Downey, and C.P. O'Donnell. “Near infrared hyperspectral image regression: On the use of prediction maps as a tool for detecting model overfitting”, J. Near Infrared Spectrosc.  22, 261 (2014). doi: http://dx.doi.org/10.1255/jnirs.1114
  7. F. Firtha, A. Fekete, T. Kaszab, B. Gillay, M. Nogula-Nagy, and Z. Kovács, and D.B. Kantor. “Methods for improving image quality and reducing data load of NIR hyperspectral images”, Sensors  8, 3287 (2008). doi: http://dx.doi.org/10.3390/s8053287
  8. L. Zhang, and M.J. Henson. “A practical algorithm to remove cosmic spikes in Raman imaging data for pharmaceutical applications”, Appl. Spectrosc.  61, 1015 (2007). doi: http://dx.doi.org/10.1366/000370207781745847
  9. C. Esquerre, A. Gowen, and C.P. O'Donnell, and G. Downey. “Suppressing sample morphology in near infrared spectral imaging of agriculture products by chemometric pre-treatments”, Chemometr. Intell. Lab. Syst.  117, 129 (2012). doi: http://dx.doi.org/10.1016/j.chemolab.2012.02.006
  10. J. Burger, and A. Gowen. “Data handling in hyperspectral image analysis”, Chemometr. Intell. Lab. Syst.  108, 13 (2011). doi: http://dx.doi.org/10.1016/j.chemolab.2011.04.001
  11. P. Dardenne. “Some considerations about NIR spectroscopy: Closing speech at NIR-2009” , https://www.impublications.com/content/some-considerations-about-nir-spectroscopy (2009).

2015 (1)

J.M. Amigo and H. Babamoradi, and S. Elcoroaristizabal. “Hyperspectral image analysis. A tutorial”, Anal. Chim. Acta  896, 34 (2015). doi: http://dx.doi.org/10.1016/j.aca.2015.09.030

J.M. Amigo and H. Babamoradi, and S. Elcoroaristizabal. “Hyperspectral image analysis. A tutorial”, Anal. Chim. Acta  896, 34 (2015). doi: http://dx.doi.org/10.1016/j.aca.2015.09.030

2014 (3)

H. Huang and L. Liu, and M.O. Ngadi. “Recent developments in hyperspectral imaging for assessment of food quality and safety”, Sensors  14, 7248 (2014). doi: http://dx.doi.org/10.3390/s140407248

H. Huang and L. Liu, and M.O. Ngadi. “Recent developments in hyperspectral imaging for assessment of food quality and safety”, Sensors  14, 7248 (2014). doi: http://dx.doi.org/10.3390/s140407248

Y. Tan, Y. Liu, Z. Zhao, and J.Z. Paxton, and L.M. Grover. “Synthesis and in vitro degradation of a novel magnesium oxychloride cement”, J. Biomed. Mater. Res. A  103, 194 (2014). doi: http://dx.doi.org/10.1002/jbm.a.35166

Y. Tan, Y. Liu, Z. Zhao, and J.Z. Paxton, and L.M. Grover. “Synthesis and in vitro degradation of a novel magnesium oxychloride cement”, J. Biomed. Mater. Res. A  103, 194 (2014). doi: http://dx.doi.org/10.1002/jbm.a.35166

A. Gowen, J. Burger, C. Esquerre, and G. Downey, and C.P. O'Donnell. “Near infrared hyperspectral image regression: On the use of prediction maps as a tool for detecting model overfitting”, J. Near Infrared Spectrosc.  22, 261 (2014). doi: http://dx.doi.org/10.1255/jnirs.1114

A. Gowen, J. Burger, C. Esquerre, and G. Downey, and C.P. O'Donnell. “Near infrared hyperspectral image regression: On the use of prediction maps as a tool for detecting model overfitting”, J. Near Infrared Spectrosc.  22, 261 (2014). doi: http://dx.doi.org/10.1255/jnirs.1114

2012 (1)

C. Esquerre, A. Gowen, and C.P. O'Donnell, and G. Downey. “Suppressing sample morphology in near infrared spectral imaging of agriculture products by chemometric pre-treatments”, Chemometr. Intell. Lab. Syst.  117, 129 (2012). doi: http://dx.doi.org/10.1016/j.chemolab.2012.02.006

C. Esquerre, A. Gowen, and C.P. O'Donnell, and G. Downey. “Suppressing sample morphology in near infrared spectral imaging of agriculture products by chemometric pre-treatments”, Chemometr. Intell. Lab. Syst.  117, 129 (2012). doi: http://dx.doi.org/10.1016/j.chemolab.2012.02.006

2011 (2)

J. Burger, and A. Gowen. “Data handling in hyperspectral image analysis”, Chemometr. Intell. Lab. Syst.  108, 13 (2011). doi: http://dx.doi.org/10.1016/j.chemolab.2011.04.001

J. Burger, and A. Gowen. “Data handling in hyperspectral image analysis”, Chemometr. Intell. Lab. Syst.  108, 13 (2011). doi: http://dx.doi.org/10.1016/j.chemolab.2011.04.001

A. Gowen, F. Marini, C. Esquerre, C.P. O'Donnell, and G. Downey, and J. Burger. “Time series hyperspectral chemical imaging data: Challenges, solutions and applications”, Anal. Chim. Acta  705, 272 (2011). doi: http://dx.doi.org/10.1016/j.aca.2011.06.031

A. Gowen, F. Marini, C. Esquerre, C.P. O'Donnell, and G. Downey, and J. Burger. “Time series hyperspectral chemical imaging data: Challenges, solutions and applications”, Anal. Chim. Acta  705, 272 (2011). doi: http://dx.doi.org/10.1016/j.aca.2011.06.031

2008 (1)

F. Firtha, A. Fekete, T. Kaszab, B. Gillay, M. Nogula-Nagy, and Z. Kovács, and D.B. Kantor. “Methods for improving image quality and reducing data load of NIR hyperspectral images”, Sensors  8, 3287 (2008). doi: http://dx.doi.org/10.3390/s8053287

F. Firtha, A. Fekete, T. Kaszab, B. Gillay, M. Nogula-Nagy, and Z. Kovács, and D.B. Kantor. “Methods for improving image quality and reducing data load of NIR hyperspectral images”, Sensors  8, 3287 (2008). doi: http://dx.doi.org/10.3390/s8053287

2007 (2)

L. Zhang, and M.J. Henson. “A practical algorithm to remove cosmic spikes in Raman imaging data for pharmaceutical applications”, Appl. Spectrosc.  61, 1015 (2007). doi: http://dx.doi.org/10.1366/000370207781745847

L. Zhang, and M.J. Henson. “A practical algorithm to remove cosmic spikes in Raman imaging data for pharmaceutical applications”, Appl. Spectrosc.  61, 1015 (2007). doi: http://dx.doi.org/10.1366/000370207781745847

Z. Li, and C.K. Chau. “Influence of molar ratios on properties of magnesium oxychloride cement”, Cement Concr. Res.  37, 866 (2007). doi: http://dx.doi.org/10.1016/j.cemconres.2007.03.015

Z. Li, and C.K. Chau. “Influence of molar ratios on properties of magnesium oxychloride cement”, Cement Concr. Res.  37, 866 (2007). doi: http://dx.doi.org/10.1016/j.cemconres.2007.03.015

Amigo, J.M.

J.M. Amigo and H. Babamoradi, and S. Elcoroaristizabal. “Hyperspectral image analysis. A tutorial”, Anal. Chim. Acta  896, 34 (2015). doi: http://dx.doi.org/10.1016/j.aca.2015.09.030

Babamoradi, H.

J.M. Amigo and H. Babamoradi, and S. Elcoroaristizabal. “Hyperspectral image analysis. A tutorial”, Anal. Chim. Acta  896, 34 (2015). doi: http://dx.doi.org/10.1016/j.aca.2015.09.030

Burger, J.

A. Gowen, J. Burger, C. Esquerre, and G. Downey, and C.P. O'Donnell. “Near infrared hyperspectral image regression: On the use of prediction maps as a tool for detecting model overfitting”, J. Near Infrared Spectrosc.  22, 261 (2014). doi: http://dx.doi.org/10.1255/jnirs.1114

J. Burger, and A. Gowen. “Data handling in hyperspectral image analysis”, Chemometr. Intell. Lab. Syst.  108, 13 (2011). doi: http://dx.doi.org/10.1016/j.chemolab.2011.04.001

A. Gowen, F. Marini, C. Esquerre, C.P. O'Donnell, and G. Downey, and J. Burger. “Time series hyperspectral chemical imaging data: Challenges, solutions and applications”, Anal. Chim. Acta  705, 272 (2011). doi: http://dx.doi.org/10.1016/j.aca.2011.06.031

Chau, C.K.

Z. Li, and C.K. Chau. “Influence of molar ratios on properties of magnesium oxychloride cement”, Cement Concr. Res.  37, 866 (2007). doi: http://dx.doi.org/10.1016/j.cemconres.2007.03.015

Dardenne, P.

P. Dardenne. “Some considerations about NIR spectroscopy: Closing speech at NIR-2009” , https://www.impublications.com/content/some-considerations-about-nir-spectroscopy (2009).

Downey, G.

A. Gowen, J. Burger, C. Esquerre, and G. Downey, and C.P. O'Donnell. “Near infrared hyperspectral image regression: On the use of prediction maps as a tool for detecting model overfitting”, J. Near Infrared Spectrosc.  22, 261 (2014). doi: http://dx.doi.org/10.1255/jnirs.1114

C. Esquerre, A. Gowen, and C.P. O'Donnell, and G. Downey. “Suppressing sample morphology in near infrared spectral imaging of agriculture products by chemometric pre-treatments”, Chemometr. Intell. Lab. Syst.  117, 129 (2012). doi: http://dx.doi.org/10.1016/j.chemolab.2012.02.006

A. Gowen, F. Marini, C. Esquerre, C.P. O'Donnell, and G. Downey, and J. Burger. “Time series hyperspectral chemical imaging data: Challenges, solutions and applications”, Anal. Chim. Acta  705, 272 (2011). doi: http://dx.doi.org/10.1016/j.aca.2011.06.031

Elcoroaristizabal, S.

J.M. Amigo and H. Babamoradi, and S. Elcoroaristizabal. “Hyperspectral image analysis. A tutorial”, Anal. Chim. Acta  896, 34 (2015). doi: http://dx.doi.org/10.1016/j.aca.2015.09.030

Esquerre, C.

A. Gowen, J. Burger, C. Esquerre, and G. Downey, and C.P. O'Donnell. “Near infrared hyperspectral image regression: On the use of prediction maps as a tool for detecting model overfitting”, J. Near Infrared Spectrosc.  22, 261 (2014). doi: http://dx.doi.org/10.1255/jnirs.1114

C. Esquerre, A. Gowen, and C.P. O'Donnell, and G. Downey. “Suppressing sample morphology in near infrared spectral imaging of agriculture products by chemometric pre-treatments”, Chemometr. Intell. Lab. Syst.  117, 129 (2012). doi: http://dx.doi.org/10.1016/j.chemolab.2012.02.006

A. Gowen, F. Marini, C. Esquerre, C.P. O'Donnell, and G. Downey, and J. Burger. “Time series hyperspectral chemical imaging data: Challenges, solutions and applications”, Anal. Chim. Acta  705, 272 (2011). doi: http://dx.doi.org/10.1016/j.aca.2011.06.031

Fekete, A.

F. Firtha, A. Fekete, T. Kaszab, B. Gillay, M. Nogula-Nagy, and Z. Kovács, and D.B. Kantor. “Methods for improving image quality and reducing data load of NIR hyperspectral images”, Sensors  8, 3287 (2008). doi: http://dx.doi.org/10.3390/s8053287

Firtha, F.

F. Firtha, A. Fekete, T. Kaszab, B. Gillay, M. Nogula-Nagy, and Z. Kovács, and D.B. Kantor. “Methods for improving image quality and reducing data load of NIR hyperspectral images”, Sensors  8, 3287 (2008). doi: http://dx.doi.org/10.3390/s8053287

Gillay, B.

F. Firtha, A. Fekete, T. Kaszab, B. Gillay, M. Nogula-Nagy, and Z. Kovács, and D.B. Kantor. “Methods for improving image quality and reducing data load of NIR hyperspectral images”, Sensors  8, 3287 (2008). doi: http://dx.doi.org/10.3390/s8053287

Gowen, A.

A. Gowen, J. Burger, C. Esquerre, and G. Downey, and C.P. O'Donnell. “Near infrared hyperspectral image regression: On the use of prediction maps as a tool for detecting model overfitting”, J. Near Infrared Spectrosc.  22, 261 (2014). doi: http://dx.doi.org/10.1255/jnirs.1114

C. Esquerre, A. Gowen, and C.P. O'Donnell, and G. Downey. “Suppressing sample morphology in near infrared spectral imaging of agriculture products by chemometric pre-treatments”, Chemometr. Intell. Lab. Syst.  117, 129 (2012). doi: http://dx.doi.org/10.1016/j.chemolab.2012.02.006

J. Burger, and A. Gowen. “Data handling in hyperspectral image analysis”, Chemometr. Intell. Lab. Syst.  108, 13 (2011). doi: http://dx.doi.org/10.1016/j.chemolab.2011.04.001

A. Gowen, F. Marini, C. Esquerre, C.P. O'Donnell, and G. Downey, and J. Burger. “Time series hyperspectral chemical imaging data: Challenges, solutions and applications”, Anal. Chim. Acta  705, 272 (2011). doi: http://dx.doi.org/10.1016/j.aca.2011.06.031

Grover, L.M.

Y. Tan, Y. Liu, Z. Zhao, and J.Z. Paxton, and L.M. Grover. “Synthesis and in vitro degradation of a novel magnesium oxychloride cement”, J. Biomed. Mater. Res. A  103, 194 (2014). doi: http://dx.doi.org/10.1002/jbm.a.35166

Henson, M.J.

Huang, H.

H. Huang and L. Liu, and M.O. Ngadi. “Recent developments in hyperspectral imaging for assessment of food quality and safety”, Sensors  14, 7248 (2014). doi: http://dx.doi.org/10.3390/s140407248

Kantor, D.B.

F. Firtha, A. Fekete, T. Kaszab, B. Gillay, M. Nogula-Nagy, and Z. Kovács, and D.B. Kantor. “Methods for improving image quality and reducing data load of NIR hyperspectral images”, Sensors  8, 3287 (2008). doi: http://dx.doi.org/10.3390/s8053287

Kaszab, T.

F. Firtha, A. Fekete, T. Kaszab, B. Gillay, M. Nogula-Nagy, and Z. Kovács, and D.B. Kantor. “Methods for improving image quality and reducing data load of NIR hyperspectral images”, Sensors  8, 3287 (2008). doi: http://dx.doi.org/10.3390/s8053287

Kovács, Z.

F. Firtha, A. Fekete, T. Kaszab, B. Gillay, M. Nogula-Nagy, and Z. Kovács, and D.B. Kantor. “Methods for improving image quality and reducing data load of NIR hyperspectral images”, Sensors  8, 3287 (2008). doi: http://dx.doi.org/10.3390/s8053287

Li, Z.

Z. Li, and C.K. Chau. “Influence of molar ratios on properties of magnesium oxychloride cement”, Cement Concr. Res.  37, 866 (2007). doi: http://dx.doi.org/10.1016/j.cemconres.2007.03.015

Liu, L.

H. Huang and L. Liu, and M.O. Ngadi. “Recent developments in hyperspectral imaging for assessment of food quality and safety”, Sensors  14, 7248 (2014). doi: http://dx.doi.org/10.3390/s140407248

Liu, Y.

Y. Tan, Y. Liu, Z. Zhao, and J.Z. Paxton, and L.M. Grover. “Synthesis and in vitro degradation of a novel magnesium oxychloride cement”, J. Biomed. Mater. Res. A  103, 194 (2014). doi: http://dx.doi.org/10.1002/jbm.a.35166

Marini, F.

A. Gowen, F. Marini, C. Esquerre, C.P. O'Donnell, and G. Downey, and J. Burger. “Time series hyperspectral chemical imaging data: Challenges, solutions and applications”, Anal. Chim. Acta  705, 272 (2011). doi: http://dx.doi.org/10.1016/j.aca.2011.06.031

Ngadi, M.O.

H. Huang and L. Liu, and M.O. Ngadi. “Recent developments in hyperspectral imaging for assessment of food quality and safety”, Sensors  14, 7248 (2014). doi: http://dx.doi.org/10.3390/s140407248

Nogula-Nagy, M.

F. Firtha, A. Fekete, T. Kaszab, B. Gillay, M. Nogula-Nagy, and Z. Kovács, and D.B. Kantor. “Methods for improving image quality and reducing data load of NIR hyperspectral images”, Sensors  8, 3287 (2008). doi: http://dx.doi.org/10.3390/s8053287

O'Donnell, C.P.

A. Gowen, J. Burger, C. Esquerre, and G. Downey, and C.P. O'Donnell. “Near infrared hyperspectral image regression: On the use of prediction maps as a tool for detecting model overfitting”, J. Near Infrared Spectrosc.  22, 261 (2014). doi: http://dx.doi.org/10.1255/jnirs.1114

C. Esquerre, A. Gowen, and C.P. O'Donnell, and G. Downey. “Suppressing sample morphology in near infrared spectral imaging of agriculture products by chemometric pre-treatments”, Chemometr. Intell. Lab. Syst.  117, 129 (2012). doi: http://dx.doi.org/10.1016/j.chemolab.2012.02.006

A. Gowen, F. Marini, C. Esquerre, C.P. O'Donnell, and G. Downey, and J. Burger. “Time series hyperspectral chemical imaging data: Challenges, solutions and applications”, Anal. Chim. Acta  705, 272 (2011). doi: http://dx.doi.org/10.1016/j.aca.2011.06.031

Paxton, J.Z.

Y. Tan, Y. Liu, Z. Zhao, and J.Z. Paxton, and L.M. Grover. “Synthesis and in vitro degradation of a novel magnesium oxychloride cement”, J. Biomed. Mater. Res. A  103, 194 (2014). doi: http://dx.doi.org/10.1002/jbm.a.35166

Tan, Y.

Y. Tan, Y. Liu, Z. Zhao, and J.Z. Paxton, and L.M. Grover. “Synthesis and in vitro degradation of a novel magnesium oxychloride cement”, J. Biomed. Mater. Res. A  103, 194 (2014). doi: http://dx.doi.org/10.1002/jbm.a.35166

Zhang, L.

Zhao, Z.

Y. Tan, Y. Liu, Z. Zhao, and J.Z. Paxton, and L.M. Grover. “Synthesis and in vitro degradation of a novel magnesium oxychloride cement”, J. Biomed. Mater. Res. A  103, 194 (2014). doi: http://dx.doi.org/10.1002/jbm.a.35166

Anal. Chim. Acta (2)

J.M. Amigo and H. Babamoradi, and S. Elcoroaristizabal. “Hyperspectral image analysis. A tutorial”, Anal. Chim. Acta  896, 34 (2015). doi: http://dx.doi.org/10.1016/j.aca.2015.09.030

A. Gowen, F. Marini, C. Esquerre, C.P. O'Donnell, and G. Downey, and J. Burger. “Time series hyperspectral chemical imaging data: Challenges, solutions and applications”, Anal. Chim. Acta  705, 272 (2011). doi: http://dx.doi.org/10.1016/j.aca.2011.06.031

Appl. Spectrosc. (1)

Cement Concr. Res. (1)

Z. Li, and C.K. Chau. “Influence of molar ratios on properties of magnesium oxychloride cement”, Cement Concr. Res.  37, 866 (2007). doi: http://dx.doi.org/10.1016/j.cemconres.2007.03.015

Chemometr. Intell. Lab. Syst. (2)

C. Esquerre, A. Gowen, and C.P. O'Donnell, and G. Downey. “Suppressing sample morphology in near infrared spectral imaging of agriculture products by chemometric pre-treatments”, Chemometr. Intell. Lab. Syst.  117, 129 (2012). doi: http://dx.doi.org/10.1016/j.chemolab.2012.02.006

J. Burger, and A. Gowen. “Data handling in hyperspectral image analysis”, Chemometr. Intell. Lab. Syst.  108, 13 (2011). doi: http://dx.doi.org/10.1016/j.chemolab.2011.04.001

J. Biomed. Mater. Res. A (1)

Y. Tan, Y. Liu, Z. Zhao, and J.Z. Paxton, and L.M. Grover. “Synthesis and in vitro degradation of a novel magnesium oxychloride cement”, J. Biomed. Mater. Res. A  103, 194 (2014). doi: http://dx.doi.org/10.1002/jbm.a.35166

J. Near Infrared Spectrosc. (1)

Sensors (2)

F. Firtha, A. Fekete, T. Kaszab, B. Gillay, M. Nogula-Nagy, and Z. Kovács, and D.B. Kantor. “Methods for improving image quality and reducing data load of NIR hyperspectral images”, Sensors  8, 3287 (2008). doi: http://dx.doi.org/10.3390/s8053287

H. Huang and L. Liu, and M.O. Ngadi. “Recent developments in hyperspectral imaging for assessment of food quality and safety”, Sensors  14, 7248 (2014). doi: http://dx.doi.org/10.3390/s140407248

Other (1)

P. Dardenne. “Some considerations about NIR spectroscopy: Closing speech at NIR-2009” , https://www.impublications.com/content/some-considerations-about-nir-spectroscopy (2009).

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