Abstract

Properties of the short wave infrared (SWIR) imaging spectrograph and the front lens along with the misalignment of optical elements contribute to positionally variant displacements and blur that can significantly degrade the overall quality of the acquired images. In this work, we devise a complete routine for simultaneous displacement correction and resolution enhancement of SWIR spectral images along the two spatial and the spectral direction. The proposed restoration routine requires images of widely available and inexpensive calibration targets from which the response function of the imaging spectrometer is extracted. Extensive validation reveals that the displacement error observed in the restored images is reduced to the manufacturing accuracy of the calibration targets. Furthermore, the restored images exhibit up to a two-fold improvement in the spectral and spatial resolution.

© 2016 Optical Society of America

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References

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2016 (1)

2015 (7)

J. Núñez, A. Núñez, F. J. Montojo, and M. Condominas, “Improving space debris detection in GEO ring using image deconvolution,” Adv. Space Res. 56, 218–228 (2015).
[Crossref]

K. Lenhard, A. Baumgartner, and T. Schwarzmaier, “Independent laboratory characterization of NEO HySpex imaging spectrometers VNIR-1600 and SWIR-320m-e,” IEEE T. Geosci. Remote 53, 1828–1841 (2015).
[Crossref]

X. Liu, Z. Yuan, Z. Guo, and D. Xu, “A localized Richardson–Lucy algorithm for fiber orientation estimation in high angular resolution diffusion imaging,” Med. Phys. 42, 2524–2539 (2015).
[Crossref]

J. Dumont, T. Hirvonen, V. Heikkinen, M. Mistretta, L. Granlund, K. Himanen, L. Fauch, I. Porali, J. Hiltunen, S. Keski-Saari, M. Nygren, E. Oksanen, M. Hauta-Kasari, and M. Keinänen, “Thermal and hyperspectral imaging for Norway spruce (Picea abies) seeds screening,” Comput. Electron. Agr. 116, 118–124 (2015).
[Crossref]

C. Gomez, R. Oltra-Carrió, S. Bacha, P. Lagacherie, and X. Briottet, “Evaluating the sensitivity of clay content prediction to atmospheric effects and degradation of image spatial resolution using hyperspectral VNIR/SWIR imagery,” Remote Sens. Environ. 164, 1–15 (2015).
[Crossref]

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[Crossref]

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[Crossref]

2014 (7)

N. Mncwangi, I. Vermaak, and A. M. Viljoen, “Mid-infrared spectroscopy and short wave infrared hyperspectral imaging–A novel approach in the qualitative assessment of Harpagophytum procumbens and H. zeyheri (Devil’s Claw),” Phytochem. Lett. 7, 143–149 (2014).
[Crossref]

P. Mouroulis, B. Van Gorp, R. O. Green, H. Dierssen, D. W. Wilson, M. Eastwood, J. Boardman, B.-C. Gao, D. Cohen, B. Franklin, F. Loya, S. Lundeen, A. Mazer, I. McCubbin, D. Randall, B. Richardson, J. I. Rodriguez, C. Sarture, E. Urquiza, R. Vargas, V. White, and K. Yee, “Portable remote imaging spectrometer coastal ocean sensor: Design, characteristics, and first flight results,” Appl. Optics 53, 1363–1380 (2014).
[Crossref]

G. Notesco, V. Kopačková, P. Rojík, G. Schwartz, I. Livne, and E. B. Dor, “Mineral classification of land surface using multispectral LWIR and hyperspectral SWIR remote-sensing data. a case study over the Sokolov lignite open-pit mines, the Czech Republic,” Remote Sens. 6, 7005–7025 (2014).
[Crossref]

M. A. Ferrer, A. Morales, and A. Díaz, “An approach to SWIR hyperspectral hand biometrics,” Inform. Sciences 268, 3–19 (2014).
[Crossref]

N. Zaini, F. van der Meer, and H. van der Werff, “Determination of carbonate rock chemistry using laboratory-based hyperspectral imagery,” Remote Sens. 6, 4149–4172 (2014).
[Crossref]

G. Lu and B. Fei, “Medical hyperspectral imaging: a review,” J. Biomed. Opt. 19, 010901 (2014).
[Crossref]

J. Jemec, F. Pernuš, B. Likar, and M. Bürmen, “Push-broom hyperspectral image calibration and enhancement by 2D deconvolution with a variant response function estimate,” Opt. Express 22, 27655–27668 (2014).
[Crossref]

2013 (4)

S. Eichstädt, F. Schmähling, G. Wübbeler, K. Anhalt, L. Bünger, U. Krüger, and C. Elster, “Comparison of the Richardson–Lucy method and a classical approach for spectrometer bandpass correction,” Metrologia 50, 107 (2013).
[Crossref]

P. Baranowski, W. Mazurek, and J. Pastuszka-Woźniak, “Supervised classification of bruised apples with respect to the time after bruising on the basis of hyperspectral imaging data,” Postharvest Biol. Technol. 86, 249–258 (2013).
[Crossref]

M. Dalponte, H. O. Orka, T. Gobakken, D. Gianelle, and E. Næsset, “Tree species classification in boreal forests with hyperspectral data,” IEEE T. Geosci. Remote 51, 2632–2645 (2013).
[Crossref]

I. Vermaak, A. Viljoen, and S. W. Lindström, “Hyperspectral imaging in the quality control of herbal medicines–the case of neurotoxic Japanese star anise,” J. Pharmaceut. Biomed. 75, 207–213 (2013).
[Crossref]

2012 (2)

S. Veraverbeke, S. Hook, and G. Hulley, “An alternative spectral index for rapid fire severity assessments,” Remote Sens. Environ. 123, 72–80 (2012).
[Crossref]

T. Skauli, “An upper-bound metric for characterizing spectral and spatial coregistration errors in spectral imaging,” Opt. Express 20, 918–933 (2012).
[Crossref]

2011 (3)

Y.-W. Tai, P. Tan, and M. S. Brown, “Richardson-Lucy deblurring for scenes under a projective motion path,” IEEE T. Pattern Anal. 33, 1603–1618 (2011).
[Crossref]

L. Zhang, C. Huang, T. Wu, F. Zhang, and Q. Tong, “Laboratory calibration of a field imaging spectrometer system,” Sensors 11, 2408–2425 (2011).
[Crossref]

R. L. Lucke, M. Corson, N. R. McGlothlin, S. D. Butcher, D. L. Wood, D. R. Korwan, R. R. Li, W. A. Snyder, C. O. Davis, and D. T. Chen, “Hyperspectral Imager for the Coastal Ocean: instrument description and first images,” Appl. Optics 50, 1501–1516 (2011).
[Crossref]

2010 (1)

2009 (1)

P. Gege, J. Fries, P. Haschberger, P. Schötz, H. Schwarzer, P. Strobl, B. Suhr, G. Ulbrich, and W. J. Vreeling, “Calibration facility for airborne imaging spectrometers,” ISPRS J. Photogramm. 64, 387–397 (2009).
[Crossref]

2007 (1)

N. Oppelt and W. Mauser, “The airborne visible/infrared imaging spectrometer AVIS: Design, characterization and calibration,” Sensors 7, 1934–1953 (2007).
[Crossref]

2006 (1)

E. Ammannito, G. Filacchione, A. Coradini, F. Capaccioni, G. Piccioni, M. De Sanctis, M. Dami, and A. Barbis, “On-ground characterization of Rosetta/VIRTIS-M. I. Spectral and geometrical calibrations,” Rev. Sci. Instrum. 77, 093109 (2006).
[Crossref]

2005 (1)

2002 (2)

2000 (1)

Z. Zhang, “A flexible new technique for camera calibration,” IEEE T. Pattern Anal. 22, 1330–1334 (2000).
[Crossref]

1974 (1)

L. B. Lucy, “An iterative technique for the rectification of observed distributions,” Astron. J. 79, 745 (1974).
[Crossref]

1972 (1)

Ammannito, E.

E. Ammannito, G. Filacchione, A. Coradini, F. Capaccioni, G. Piccioni, M. De Sanctis, M. Dami, and A. Barbis, “On-ground characterization of Rosetta/VIRTIS-M. I. Spectral and geometrical calibrations,” Rev. Sci. Instrum. 77, 093109 (2006).
[Crossref]

Anhalt, K.

S. Eichstädt, F. Schmähling, G. Wübbeler, K. Anhalt, L. Bünger, U. Krüger, and C. Elster, “Comparison of the Richardson–Lucy method and a classical approach for spectrometer bandpass correction,” Metrologia 50, 107 (2013).
[Crossref]

Bacha, S.

C. Gomez, R. Oltra-Carrió, S. Bacha, P. Lagacherie, and X. Briottet, “Evaluating the sensitivity of clay content prediction to atmospheric effects and degradation of image spatial resolution using hyperspectral VNIR/SWIR imagery,” Remote Sens. Environ. 164, 1–15 (2015).
[Crossref]

Bae, H.

L. M. Kandpal, S. Lee, M. S. Kim, H. Bae, and B.-K. Cho, “Short wave infrared (SWIR) hyperspectral imaging technique for examination of aflatoxin B 1 (AFB 1) on corn kernels,” Food Control 51, 171–176 (2015).
[Crossref]

Baranowski, P.

P. Baranowski, W. Mazurek, and J. Pastuszka-Woźniak, “Supervised classification of bruised apples with respect to the time after bruising on the basis of hyperspectral imaging data,” Postharvest Biol. Technol. 86, 249–258 (2013).
[Crossref]

Barbis, A.

E. Ammannito, G. Filacchione, A. Coradini, F. Capaccioni, G. Piccioni, M. De Sanctis, M. Dami, and A. Barbis, “On-ground characterization of Rosetta/VIRTIS-M. I. Spectral and geometrical calibrations,” Rev. Sci. Instrum. 77, 093109 (2006).
[Crossref]

Baumgartner, A.

K. Lenhard, A. Baumgartner, and T. Schwarzmaier, “Independent laboratory characterization of NEO HySpex imaging spectrometers VNIR-1600 and SWIR-320m-e,” IEEE T. Geosci. Remote 53, 1828–1841 (2015).
[Crossref]

Bertero, M.

M. Bertero and P. Boccacci, Introduction to Inverse Problems in Imaging (CRC Press, 1998).
[Crossref]

Bissett, W. P.

Boardman, J.

P. Mouroulis, B. Van Gorp, R. O. Green, H. Dierssen, D. W. Wilson, M. Eastwood, J. Boardman, B.-C. Gao, D. Cohen, B. Franklin, F. Loya, S. Lundeen, A. Mazer, I. McCubbin, D. Randall, B. Richardson, J. I. Rodriguez, C. Sarture, E. Urquiza, R. Vargas, V. White, and K. Yee, “Portable remote imaging spectrometer coastal ocean sensor: Design, characteristics, and first flight results,” Appl. Optics 53, 1363–1380 (2014).
[Crossref]

Boccacci, P.

M. Bertero and P. Boccacci, Introduction to Inverse Problems in Imaging (CRC Press, 1998).
[Crossref]

Bowles, J.

Briottet, X.

C. Gomez, R. Oltra-Carrió, S. Bacha, P. Lagacherie, and X. Briottet, “Evaluating the sensitivity of clay content prediction to atmospheric effects and degradation of image spatial resolution using hyperspectral VNIR/SWIR imagery,” Remote Sens. Environ. 164, 1–15 (2015).
[Crossref]

Brown, M. S.

Y.-W. Tai, P. Tan, and M. S. Brown, “Richardson-Lucy deblurring for scenes under a projective motion path,” IEEE T. Pattern Anal. 33, 1603–1618 (2011).
[Crossref]

Bünger, L.

S. Eichstädt, F. Schmähling, G. Wübbeler, K. Anhalt, L. Bünger, U. Krüger, and C. Elster, “Comparison of the Richardson–Lucy method and a classical approach for spectrometer bandpass correction,” Metrologia 50, 107 (2013).
[Crossref]

Bürmen, M.

Butcher, S. D.

R. L. Lucke, M. Corson, N. R. McGlothlin, S. D. Butcher, D. L. Wood, D. R. Korwan, R. R. Li, W. A. Snyder, C. O. Davis, and D. T. Chen, “Hyperspectral Imager for the Coastal Ocean: instrument description and first images,” Appl. Optics 50, 1501–1516 (2011).
[Crossref]

Capaccioni, F.

E. Ammannito, G. Filacchione, A. Coradini, F. Capaccioni, G. Piccioni, M. De Sanctis, M. Dami, and A. Barbis, “On-ground characterization of Rosetta/VIRTIS-M. I. Spectral and geometrical calibrations,” Rev. Sci. Instrum. 77, 093109 (2006).
[Crossref]

Chakrova, N.

Chen, D. T.

R. L. Lucke, M. Corson, N. R. McGlothlin, S. D. Butcher, D. L. Wood, D. R. Korwan, R. R. Li, W. A. Snyder, C. O. Davis, and D. T. Chen, “Hyperspectral Imager for the Coastal Ocean: instrument description and first images,” Appl. Optics 50, 1501–1516 (2011).
[Crossref]

Chen, W.

Chlingaryan, A.

R. J. Murphy, A. Chlingaryan, and A. Melkumyan, “Gaussian processes for estimating wavelength position of the ferric iron crystal field feature at 900 nm from hyperspectral imagery acquired in the short-wave infrared (1002–1355 nm),” IEEE T. Geosci. Remote 53, 1907–1920 (2015).
[Crossref]

Cho, B.-K.

L. M. Kandpal, S. Lee, M. S. Kim, H. Bae, and B.-K. Cho, “Short wave infrared (SWIR) hyperspectral imaging technique for examination of aflatoxin B 1 (AFB 1) on corn kernels,” Food Control 51, 171–176 (2015).
[Crossref]

Choquette, S. J.

Cohen, D.

P. Mouroulis, B. Van Gorp, R. O. Green, H. Dierssen, D. W. Wilson, M. Eastwood, J. Boardman, B.-C. Gao, D. Cohen, B. Franklin, F. Loya, S. Lundeen, A. Mazer, I. McCubbin, D. Randall, B. Richardson, J. I. Rodriguez, C. Sarture, E. Urquiza, R. Vargas, V. White, and K. Yee, “Portable remote imaging spectrometer coastal ocean sensor: Design, characteristics, and first flight results,” Appl. Optics 53, 1363–1380 (2014).
[Crossref]

Condominas, M.

J. Núñez, A. Núñez, F. J. Montojo, and M. Condominas, “Improving space debris detection in GEO ring using image deconvolution,” Adv. Space Res. 56, 218–228 (2015).
[Crossref]

Coradini, A.

E. Ammannito, G. Filacchione, A. Coradini, F. Capaccioni, G. Piccioni, M. De Sanctis, M. Dami, and A. Barbis, “On-ground characterization of Rosetta/VIRTIS-M. I. Spectral and geometrical calibrations,” Rev. Sci. Instrum. 77, 093109 (2006).
[Crossref]

Cornwell, T. J.

T. J. Cornwell, “Image restoration,” in Diffraction-Limited Imaging with Very Large Telescopes, D. M. Alloin and J.-M. Mariotti, eds. (Springer, 1989).
[Crossref]

Corson, M.

R. L. Lucke, M. Corson, N. R. McGlothlin, S. D. Butcher, D. L. Wood, D. R. Korwan, R. R. Li, W. A. Snyder, C. O. Davis, and D. T. Chen, “Hyperspectral Imager for the Coastal Ocean: instrument description and first images,” Appl. Optics 50, 1501–1516 (2011).
[Crossref]

Dalponte, M.

M. Dalponte, H. O. Orka, T. Gobakken, D. Gianelle, and E. Næsset, “Tree species classification in boreal forests with hyperspectral data,” IEEE T. Geosci. Remote 51, 2632–2645 (2013).
[Crossref]

Dami, M.

E. Ammannito, G. Filacchione, A. Coradini, F. Capaccioni, G. Piccioni, M. De Sanctis, M. Dami, and A. Barbis, “On-ground characterization of Rosetta/VIRTIS-M. I. Spectral and geometrical calibrations,” Rev. Sci. Instrum. 77, 093109 (2006).
[Crossref]

Davis, C. O.

R. L. Lucke, M. Corson, N. R. McGlothlin, S. D. Butcher, D. L. Wood, D. R. Korwan, R. R. Li, W. A. Snyder, C. O. Davis, and D. T. Chen, “Hyperspectral Imager for the Coastal Ocean: instrument description and first images,” Appl. Optics 50, 1501–1516 (2011).
[Crossref]

C. O. Davis, J. Bowles, R. A. Leathers, D. Korwan, T. V. Downes, W. A. Snyder, W. J. Rhea, W. Chen, J. Fisher, W. P. Bissett, and R. A. Reisse, “Ocean PHILLS hyperspectral imager: design, characterization, and calibration,” Opt. Express 10, 210–221 (2002).
[Crossref]

De Sanctis, M.

E. Ammannito, G. Filacchione, A. Coradini, F. Capaccioni, G. Piccioni, M. De Sanctis, M. Dami, and A. Barbis, “On-ground characterization of Rosetta/VIRTIS-M. I. Spectral and geometrical calibrations,” Rev. Sci. Instrum. 77, 093109 (2006).
[Crossref]

Díaz, A.

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L. M. Kandpal, S. Lee, M. S. Kim, H. Bae, and B.-K. Cho, “Short wave infrared (SWIR) hyperspectral imaging technique for examination of aflatoxin B 1 (AFB 1) on corn kernels,” Food Control 51, 171–176 (2015).
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L. M. Kandpal, S. Lee, M. S. Kim, H. Bae, and B.-K. Cho, “Short wave infrared (SWIR) hyperspectral imaging technique for examination of aflatoxin B 1 (AFB 1) on corn kernels,” Food Control 51, 171–176 (2015).
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P. Mouroulis, B. Van Gorp, R. O. Green, H. Dierssen, D. W. Wilson, M. Eastwood, J. Boardman, B.-C. Gao, D. Cohen, B. Franklin, F. Loya, S. Lundeen, A. Mazer, I. McCubbin, D. Randall, B. Richardson, J. I. Rodriguez, C. Sarture, E. Urquiza, R. Vargas, V. White, and K. Yee, “Portable remote imaging spectrometer coastal ocean sensor: Design, characteristics, and first flight results,” Appl. Optics 53, 1363–1380 (2014).
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M. A. Ferrer, A. Morales, and A. Díaz, “An approach to SWIR hyperspectral hand biometrics,” Inform. Sciences 268, 3–19 (2014).
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P. Mouroulis, B. Van Gorp, R. O. Green, H. Dierssen, D. W. Wilson, M. Eastwood, J. Boardman, B.-C. Gao, D. Cohen, B. Franklin, F. Loya, S. Lundeen, A. Mazer, I. McCubbin, D. Randall, B. Richardson, J. I. Rodriguez, C. Sarture, E. Urquiza, R. Vargas, V. White, and K. Yee, “Portable remote imaging spectrometer coastal ocean sensor: Design, characteristics, and first flight results,” Appl. Optics 53, 1363–1380 (2014).
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M. Dalponte, H. O. Orka, T. Gobakken, D. Gianelle, and E. Næsset, “Tree species classification in boreal forests with hyperspectral data,” IEEE T. Geosci. Remote 51, 2632–2645 (2013).
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G. Notesco, V. Kopačková, P. Rojík, G. Schwartz, I. Livne, and E. B. Dor, “Mineral classification of land surface using multispectral LWIR and hyperspectral SWIR remote-sensing data. a case study over the Sokolov lignite open-pit mines, the Czech Republic,” Remote Sens. 6, 7005–7025 (2014).
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J. Núñez, A. Núñez, F. J. Montojo, and M. Condominas, “Improving space debris detection in GEO ring using image deconvolution,” Adv. Space Res. 56, 218–228 (2015).
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J. Dumont, T. Hirvonen, V. Heikkinen, M. Mistretta, L. Granlund, K. Himanen, L. Fauch, I. Porali, J. Hiltunen, S. Keski-Saari, M. Nygren, E. Oksanen, M. Hauta-Kasari, and M. Keinänen, “Thermal and hyperspectral imaging for Norway spruce (Picea abies) seeds screening,” Comput. Electron. Agr. 116, 118–124 (2015).
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J. Dumont, T. Hirvonen, V. Heikkinen, M. Mistretta, L. Granlund, K. Himanen, L. Fauch, I. Porali, J. Hiltunen, S. Keski-Saari, M. Nygren, E. Oksanen, M. Hauta-Kasari, and M. Keinänen, “Thermal and hyperspectral imaging for Norway spruce (Picea abies) seeds screening,” Comput. Electron. Agr. 116, 118–124 (2015).
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C. Gomez, R. Oltra-Carrió, S. Bacha, P. Lagacherie, and X. Briottet, “Evaluating the sensitivity of clay content prediction to atmospheric effects and degradation of image spatial resolution using hyperspectral VNIR/SWIR imagery,” Remote Sens. Environ. 164, 1–15 (2015).
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N. Oppelt and W. Mauser, “The airborne visible/infrared imaging spectrometer AVIS: Design, characterization and calibration,” Sensors 7, 1934–1953 (2007).
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M. Dalponte, H. O. Orka, T. Gobakken, D. Gianelle, and E. Næsset, “Tree species classification in boreal forests with hyperspectral data,” IEEE T. Geosci. Remote 51, 2632–2645 (2013).
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J. Dumont, T. Hirvonen, V. Heikkinen, M. Mistretta, L. Granlund, K. Himanen, L. Fauch, I. Porali, J. Hiltunen, S. Keski-Saari, M. Nygren, E. Oksanen, M. Hauta-Kasari, and M. Keinänen, “Thermal and hyperspectral imaging for Norway spruce (Picea abies) seeds screening,” Comput. Electron. Agr. 116, 118–124 (2015).
[Crossref]

Randall, D.

P. Mouroulis, B. Van Gorp, R. O. Green, H. Dierssen, D. W. Wilson, M. Eastwood, J. Boardman, B.-C. Gao, D. Cohen, B. Franklin, F. Loya, S. Lundeen, A. Mazer, I. McCubbin, D. Randall, B. Richardson, J. I. Rodriguez, C. Sarture, E. Urquiza, R. Vargas, V. White, and K. Yee, “Portable remote imaging spectrometer coastal ocean sensor: Design, characteristics, and first flight results,” Appl. Optics 53, 1363–1380 (2014).
[Crossref]

Reisse, R. A.

Rhea, W. J.

Richardson, B.

P. Mouroulis, B. Van Gorp, R. O. Green, H. Dierssen, D. W. Wilson, M. Eastwood, J. Boardman, B.-C. Gao, D. Cohen, B. Franklin, F. Loya, S. Lundeen, A. Mazer, I. McCubbin, D. Randall, B. Richardson, J. I. Rodriguez, C. Sarture, E. Urquiza, R. Vargas, V. White, and K. Yee, “Portable remote imaging spectrometer coastal ocean sensor: Design, characteristics, and first flight results,” Appl. Optics 53, 1363–1380 (2014).
[Crossref]

Richardson, W. H.

Rieger, B.

Rodriguez, J. I.

P. Mouroulis, B. Van Gorp, R. O. Green, H. Dierssen, D. W. Wilson, M. Eastwood, J. Boardman, B.-C. Gao, D. Cohen, B. Franklin, F. Loya, S. Lundeen, A. Mazer, I. McCubbin, D. Randall, B. Richardson, J. I. Rodriguez, C. Sarture, E. Urquiza, R. Vargas, V. White, and K. Yee, “Portable remote imaging spectrometer coastal ocean sensor: Design, characteristics, and first flight results,” Appl. Optics 53, 1363–1380 (2014).
[Crossref]

Rojík, P.

G. Notesco, V. Kopačková, P. Rojík, G. Schwartz, I. Livne, and E. B. Dor, “Mineral classification of land surface using multispectral LWIR and hyperspectral SWIR remote-sensing data. a case study over the Sokolov lignite open-pit mines, the Czech Republic,” Remote Sens. 6, 7005–7025 (2014).
[Crossref]

Sarture, C.

P. Mouroulis, B. Van Gorp, R. O. Green, H. Dierssen, D. W. Wilson, M. Eastwood, J. Boardman, B.-C. Gao, D. Cohen, B. Franklin, F. Loya, S. Lundeen, A. Mazer, I. McCubbin, D. Randall, B. Richardson, J. I. Rodriguez, C. Sarture, E. Urquiza, R. Vargas, V. White, and K. Yee, “Portable remote imaging spectrometer coastal ocean sensor: Design, characteristics, and first flight results,” Appl. Optics 53, 1363–1380 (2014).
[Crossref]

Schmähling, F.

S. Eichstädt, F. Schmähling, G. Wübbeler, K. Anhalt, L. Bünger, U. Krüger, and C. Elster, “Comparison of the Richardson–Lucy method and a classical approach for spectrometer bandpass correction,” Metrologia 50, 107 (2013).
[Crossref]

Schötz, P.

P. Gege, J. Fries, P. Haschberger, P. Schötz, H. Schwarzer, P. Strobl, B. Suhr, G. Ulbrich, and W. J. Vreeling, “Calibration facility for airborne imaging spectrometers,” ISPRS J. Photogramm. 64, 387–397 (2009).
[Crossref]

Schwartz, G.

G. Notesco, V. Kopačková, P. Rojík, G. Schwartz, I. Livne, and E. B. Dor, “Mineral classification of land surface using multispectral LWIR and hyperspectral SWIR remote-sensing data. a case study over the Sokolov lignite open-pit mines, the Czech Republic,” Remote Sens. 6, 7005–7025 (2014).
[Crossref]

Schwarzer, H.

P. Gege, J. Fries, P. Haschberger, P. Schötz, H. Schwarzer, P. Strobl, B. Suhr, G. Ulbrich, and W. J. Vreeling, “Calibration facility for airborne imaging spectrometers,” ISPRS J. Photogramm. 64, 387–397 (2009).
[Crossref]

Schwarzmaier, T.

K. Lenhard, A. Baumgartner, and T. Schwarzmaier, “Independent laboratory characterization of NEO HySpex imaging spectrometers VNIR-1600 and SWIR-320m-e,” IEEE T. Geosci. Remote 53, 1828–1841 (2015).
[Crossref]

Skauli, T.

Snyder, W. A.

R. L. Lucke, M. Corson, N. R. McGlothlin, S. D. Butcher, D. L. Wood, D. R. Korwan, R. R. Li, W. A. Snyder, C. O. Davis, and D. T. Chen, “Hyperspectral Imager for the Coastal Ocean: instrument description and first images,” Appl. Optics 50, 1501–1516 (2011).
[Crossref]

C. O. Davis, J. Bowles, R. A. Leathers, D. Korwan, T. V. Downes, W. A. Snyder, W. J. Rhea, W. Chen, J. Fisher, W. P. Bissett, and R. A. Reisse, “Ocean PHILLS hyperspectral imager: design, characterization, and calibration,” Opt. Express 10, 210–221 (2002).
[Crossref]

Stallinga, S.

Starck, J.

J. Starck, E. Pantin, and F. Murtagh, “Deconvolution in astronomy: A review,” Publ. Astron. Soc. Pac. 114, 1051 (2002).
[Crossref]

Strobl, P.

P. Gege, J. Fries, P. Haschberger, P. Schötz, H. Schwarzer, P. Strobl, B. Suhr, G. Ulbrich, and W. J. Vreeling, “Calibration facility for airborne imaging spectrometers,” ISPRS J. Photogramm. 64, 387–397 (2009).
[Crossref]

Suhr, B.

P. Gege, J. Fries, P. Haschberger, P. Schötz, H. Schwarzer, P. Strobl, B. Suhr, G. Ulbrich, and W. J. Vreeling, “Calibration facility for airborne imaging spectrometers,” ISPRS J. Photogramm. 64, 387–397 (2009).
[Crossref]

Tai, Y.-W.

Y.-W. Tai, P. Tan, and M. S. Brown, “Richardson-Lucy deblurring for scenes under a projective motion path,” IEEE T. Pattern Anal. 33, 1603–1618 (2011).
[Crossref]

Tan, P.

Y.-W. Tai, P. Tan, and M. S. Brown, “Richardson-Lucy deblurring for scenes under a projective motion path,” IEEE T. Pattern Anal. 33, 1603–1618 (2011).
[Crossref]

Thiébaut, E.

E. Thiébaut, “Introduction to Image Reconstruction and Inverse Problems,” in Optics in Astrophysics, R. Foy and F. C. Foy, eds. (Springer, 2005).

Tong, Q.

L. Zhang, C. Huang, T. Wu, F. Zhang, and Q. Tong, “Laboratory calibration of a field imaging spectrometer system,” Sensors 11, 2408–2425 (2011).
[Crossref]

Ulbrich, G.

P. Gege, J. Fries, P. Haschberger, P. Schötz, H. Schwarzer, P. Strobl, B. Suhr, G. Ulbrich, and W. J. Vreeling, “Calibration facility for airborne imaging spectrometers,” ISPRS J. Photogramm. 64, 387–397 (2009).
[Crossref]

Urbas, A.

S. J. Choquette and A. Urbas, The National Institute of Standards and Technology (email personal communication, 2015).

Urquiza, E.

P. Mouroulis, B. Van Gorp, R. O. Green, H. Dierssen, D. W. Wilson, M. Eastwood, J. Boardman, B.-C. Gao, D. Cohen, B. Franklin, F. Loya, S. Lundeen, A. Mazer, I. McCubbin, D. Randall, B. Richardson, J. I. Rodriguez, C. Sarture, E. Urquiza, R. Vargas, V. White, and K. Yee, “Portable remote imaging spectrometer coastal ocean sensor: Design, characteristics, and first flight results,” Appl. Optics 53, 1363–1380 (2014).
[Crossref]

van der Meer, F.

N. Zaini, F. van der Meer, and H. van der Werff, “Determination of carbonate rock chemistry using laboratory-based hyperspectral imagery,” Remote Sens. 6, 4149–4172 (2014).
[Crossref]

van der Werff, H.

N. Zaini, F. van der Meer, and H. van der Werff, “Determination of carbonate rock chemistry using laboratory-based hyperspectral imagery,” Remote Sens. 6, 4149–4172 (2014).
[Crossref]

Van Gorp, B.

P. Mouroulis, B. Van Gorp, R. O. Green, H. Dierssen, D. W. Wilson, M. Eastwood, J. Boardman, B.-C. Gao, D. Cohen, B. Franklin, F. Loya, S. Lundeen, A. Mazer, I. McCubbin, D. Randall, B. Richardson, J. I. Rodriguez, C. Sarture, E. Urquiza, R. Vargas, V. White, and K. Yee, “Portable remote imaging spectrometer coastal ocean sensor: Design, characteristics, and first flight results,” Appl. Optics 53, 1363–1380 (2014).
[Crossref]

Vargas, R.

P. Mouroulis, B. Van Gorp, R. O. Green, H. Dierssen, D. W. Wilson, M. Eastwood, J. Boardman, B.-C. Gao, D. Cohen, B. Franklin, F. Loya, S. Lundeen, A. Mazer, I. McCubbin, D. Randall, B. Richardson, J. I. Rodriguez, C. Sarture, E. Urquiza, R. Vargas, V. White, and K. Yee, “Portable remote imaging spectrometer coastal ocean sensor: Design, characteristics, and first flight results,” Appl. Optics 53, 1363–1380 (2014).
[Crossref]

Veraverbeke, S.

S. Veraverbeke, S. Hook, and G. Hulley, “An alternative spectral index for rapid fire severity assessments,” Remote Sens. Environ. 123, 72–80 (2012).
[Crossref]

Vermaak, I.

N. Mncwangi, I. Vermaak, and A. M. Viljoen, “Mid-infrared spectroscopy and short wave infrared hyperspectral imaging–A novel approach in the qualitative assessment of Harpagophytum procumbens and H. zeyheri (Devil’s Claw),” Phytochem. Lett. 7, 143–149 (2014).
[Crossref]

I. Vermaak, A. Viljoen, and S. W. Lindström, “Hyperspectral imaging in the quality control of herbal medicines–the case of neurotoxic Japanese star anise,” J. Pharmaceut. Biomed. 75, 207–213 (2013).
[Crossref]

Viljoen, A.

I. Vermaak, A. Viljoen, and S. W. Lindström, “Hyperspectral imaging in the quality control of herbal medicines–the case of neurotoxic Japanese star anise,” J. Pharmaceut. Biomed. 75, 207–213 (2013).
[Crossref]

Viljoen, A. M.

N. Mncwangi, I. Vermaak, and A. M. Viljoen, “Mid-infrared spectroscopy and short wave infrared hyperspectral imaging–A novel approach in the qualitative assessment of Harpagophytum procumbens and H. zeyheri (Devil’s Claw),” Phytochem. Lett. 7, 143–149 (2014).
[Crossref]

Vreeling, W. J.

P. Gege, J. Fries, P. Haschberger, P. Schötz, H. Schwarzer, P. Strobl, B. Suhr, G. Ulbrich, and W. J. Vreeling, “Calibration facility for airborne imaging spectrometers,” ISPRS J. Photogramm. 64, 387–397 (2009).
[Crossref]

White, V.

P. Mouroulis, B. Van Gorp, R. O. Green, H. Dierssen, D. W. Wilson, M. Eastwood, J. Boardman, B.-C. Gao, D. Cohen, B. Franklin, F. Loya, S. Lundeen, A. Mazer, I. McCubbin, D. Randall, B. Richardson, J. I. Rodriguez, C. Sarture, E. Urquiza, R. Vargas, V. White, and K. Yee, “Portable remote imaging spectrometer coastal ocean sensor: Design, characteristics, and first flight results,” Appl. Optics 53, 1363–1380 (2014).
[Crossref]

Wilson, D. W.

P. Mouroulis, B. Van Gorp, R. O. Green, H. Dierssen, D. W. Wilson, M. Eastwood, J. Boardman, B.-C. Gao, D. Cohen, B. Franklin, F. Loya, S. Lundeen, A. Mazer, I. McCubbin, D. Randall, B. Richardson, J. I. Rodriguez, C. Sarture, E. Urquiza, R. Vargas, V. White, and K. Yee, “Portable remote imaging spectrometer coastal ocean sensor: Design, characteristics, and first flight results,” Appl. Optics 53, 1363–1380 (2014).
[Crossref]

Wood, D. L.

R. L. Lucke, M. Corson, N. R. McGlothlin, S. D. Butcher, D. L. Wood, D. R. Korwan, R. R. Li, W. A. Snyder, C. O. Davis, and D. T. Chen, “Hyperspectral Imager for the Coastal Ocean: instrument description and first images,” Appl. Optics 50, 1501–1516 (2011).
[Crossref]

Wu, T.

L. Zhang, C. Huang, T. Wu, F. Zhang, and Q. Tong, “Laboratory calibration of a field imaging spectrometer system,” Sensors 11, 2408–2425 (2011).
[Crossref]

Wübbeler, G.

S. Eichstädt, F. Schmähling, G. Wübbeler, K. Anhalt, L. Bünger, U. Krüger, and C. Elster, “Comparison of the Richardson–Lucy method and a classical approach for spectrometer bandpass correction,” Metrologia 50, 107 (2013).
[Crossref]

Xu, D.

X. Liu, Z. Yuan, Z. Guo, and D. Xu, “A localized Richardson–Lucy algorithm for fiber orientation estimation in high angular resolution diffusion imaging,” Med. Phys. 42, 2524–2539 (2015).
[Crossref]

Yee, K.

P. Mouroulis, B. Van Gorp, R. O. Green, H. Dierssen, D. W. Wilson, M. Eastwood, J. Boardman, B.-C. Gao, D. Cohen, B. Franklin, F. Loya, S. Lundeen, A. Mazer, I. McCubbin, D. Randall, B. Richardson, J. I. Rodriguez, C. Sarture, E. Urquiza, R. Vargas, V. White, and K. Yee, “Portable remote imaging spectrometer coastal ocean sensor: Design, characteristics, and first flight results,” Appl. Optics 53, 1363–1380 (2014).
[Crossref]

Yuan, Z.

X. Liu, Z. Yuan, Z. Guo, and D. Xu, “A localized Richardson–Lucy algorithm for fiber orientation estimation in high angular resolution diffusion imaging,” Med. Phys. 42, 2524–2539 (2015).
[Crossref]

Zaini, N.

N. Zaini, F. van der Meer, and H. van der Werff, “Determination of carbonate rock chemistry using laboratory-based hyperspectral imagery,” Remote Sens. 6, 4149–4172 (2014).
[Crossref]

Zhang, F.

L. Zhang, C. Huang, T. Wu, F. Zhang, and Q. Tong, “Laboratory calibration of a field imaging spectrometer system,” Sensors 11, 2408–2425 (2011).
[Crossref]

Zhang, L.

L. Zhang, C. Huang, T. Wu, F. Zhang, and Q. Tong, “Laboratory calibration of a field imaging spectrometer system,” Sensors 11, 2408–2425 (2011).
[Crossref]

Zhang, Z.

Z. Zhang, “A flexible new technique for camera calibration,” IEEE T. Pattern Anal. 22, 1330–1334 (2000).
[Crossref]

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J. Núñez, A. Núñez, F. J. Montojo, and M. Condominas, “Improving space debris detection in GEO ring using image deconvolution,” Adv. Space Res. 56, 218–228 (2015).
[Crossref]

Appl. Optics (2)

R. L. Lucke, M. Corson, N. R. McGlothlin, S. D. Butcher, D. L. Wood, D. R. Korwan, R. R. Li, W. A. Snyder, C. O. Davis, and D. T. Chen, “Hyperspectral Imager for the Coastal Ocean: instrument description and first images,” Appl. Optics 50, 1501–1516 (2011).
[Crossref]

P. Mouroulis, B. Van Gorp, R. O. Green, H. Dierssen, D. W. Wilson, M. Eastwood, J. Boardman, B.-C. Gao, D. Cohen, B. Franklin, F. Loya, S. Lundeen, A. Mazer, I. McCubbin, D. Randall, B. Richardson, J. I. Rodriguez, C. Sarture, E. Urquiza, R. Vargas, V. White, and K. Yee, “Portable remote imaging spectrometer coastal ocean sensor: Design, characteristics, and first flight results,” Appl. Optics 53, 1363–1380 (2014).
[Crossref]

Appl. Spectrosc. (2)

Astron. J. (1)

L. B. Lucy, “An iterative technique for the rectification of observed distributions,” Astron. J. 79, 745 (1974).
[Crossref]

Comput. Electron. Agr. (1)

J. Dumont, T. Hirvonen, V. Heikkinen, M. Mistretta, L. Granlund, K. Himanen, L. Fauch, I. Porali, J. Hiltunen, S. Keski-Saari, M. Nygren, E. Oksanen, M. Hauta-Kasari, and M. Keinänen, “Thermal and hyperspectral imaging for Norway spruce (Picea abies) seeds screening,” Comput. Electron. Agr. 116, 118–124 (2015).
[Crossref]

Food Control (1)

L. M. Kandpal, S. Lee, M. S. Kim, H. Bae, and B.-K. Cho, “Short wave infrared (SWIR) hyperspectral imaging technique for examination of aflatoxin B 1 (AFB 1) on corn kernels,” Food Control 51, 171–176 (2015).
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IEEE T. Geosci. Remote (3)

M. Dalponte, H. O. Orka, T. Gobakken, D. Gianelle, and E. Næsset, “Tree species classification in boreal forests with hyperspectral data,” IEEE T. Geosci. Remote 51, 2632–2645 (2013).
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R. J. Murphy, A. Chlingaryan, and A. Melkumyan, “Gaussian processes for estimating wavelength position of the ferric iron crystal field feature at 900 nm from hyperspectral imagery acquired in the short-wave infrared (1002–1355 nm),” IEEE T. Geosci. Remote 53, 1907–1920 (2015).
[Crossref]

K. Lenhard, A. Baumgartner, and T. Schwarzmaier, “Independent laboratory characterization of NEO HySpex imaging spectrometers VNIR-1600 and SWIR-320m-e,” IEEE T. Geosci. Remote 53, 1828–1841 (2015).
[Crossref]

IEEE T. Pattern Anal. (2)

Y.-W. Tai, P. Tan, and M. S. Brown, “Richardson-Lucy deblurring for scenes under a projective motion path,” IEEE T. Pattern Anal. 33, 1603–1618 (2011).
[Crossref]

Z. Zhang, “A flexible new technique for camera calibration,” IEEE T. Pattern Anal. 22, 1330–1334 (2000).
[Crossref]

Inform. Sciences (1)

M. A. Ferrer, A. Morales, and A. Díaz, “An approach to SWIR hyperspectral hand biometrics,” Inform. Sciences 268, 3–19 (2014).
[Crossref]

ISPRS J. Photogramm. (1)

P. Gege, J. Fries, P. Haschberger, P. Schötz, H. Schwarzer, P. Strobl, B. Suhr, G. Ulbrich, and W. J. Vreeling, “Calibration facility for airborne imaging spectrometers,” ISPRS J. Photogramm. 64, 387–397 (2009).
[Crossref]

J. Biomed. Opt. (1)

G. Lu and B. Fei, “Medical hyperspectral imaging: a review,” J. Biomed. Opt. 19, 010901 (2014).
[Crossref]

J. Opt. Soc. Am. (1)

J. Opt. Soc. Am. A (1)

J. Pharmaceut. Biomed. (1)

I. Vermaak, A. Viljoen, and S. W. Lindström, “Hyperspectral imaging in the quality control of herbal medicines–the case of neurotoxic Japanese star anise,” J. Pharmaceut. Biomed. 75, 207–213 (2013).
[Crossref]

Med. Phys. (1)

X. Liu, Z. Yuan, Z. Guo, and D. Xu, “A localized Richardson–Lucy algorithm for fiber orientation estimation in high angular resolution diffusion imaging,” Med. Phys. 42, 2524–2539 (2015).
[Crossref]

Metrologia (1)

S. Eichstädt, F. Schmähling, G. Wübbeler, K. Anhalt, L. Bünger, U. Krüger, and C. Elster, “Comparison of the Richardson–Lucy method and a classical approach for spectrometer bandpass correction,” Metrologia 50, 107 (2013).
[Crossref]

Opt. Express (3)

Phytochem. Lett. (1)

N. Mncwangi, I. Vermaak, and A. M. Viljoen, “Mid-infrared spectroscopy and short wave infrared hyperspectral imaging–A novel approach in the qualitative assessment of Harpagophytum procumbens and H. zeyheri (Devil’s Claw),” Phytochem. Lett. 7, 143–149 (2014).
[Crossref]

Postharvest Biol. Technol. (1)

P. Baranowski, W. Mazurek, and J. Pastuszka-Woźniak, “Supervised classification of bruised apples with respect to the time after bruising on the basis of hyperspectral imaging data,” Postharvest Biol. Technol. 86, 249–258 (2013).
[Crossref]

Publ. Astron. Soc. Pac. (1)

J. Starck, E. Pantin, and F. Murtagh, “Deconvolution in astronomy: A review,” Publ. Astron. Soc. Pac. 114, 1051 (2002).
[Crossref]

Remote Sens. (2)

N. Zaini, F. van der Meer, and H. van der Werff, “Determination of carbonate rock chemistry using laboratory-based hyperspectral imagery,” Remote Sens. 6, 4149–4172 (2014).
[Crossref]

G. Notesco, V. Kopačková, P. Rojík, G. Schwartz, I. Livne, and E. B. Dor, “Mineral classification of land surface using multispectral LWIR and hyperspectral SWIR remote-sensing data. a case study over the Sokolov lignite open-pit mines, the Czech Republic,” Remote Sens. 6, 7005–7025 (2014).
[Crossref]

Remote Sens. Environ. (2)

S. Veraverbeke, S. Hook, and G. Hulley, “An alternative spectral index for rapid fire severity assessments,” Remote Sens. Environ. 123, 72–80 (2012).
[Crossref]

C. Gomez, R. Oltra-Carrió, S. Bacha, P. Lagacherie, and X. Briottet, “Evaluating the sensitivity of clay content prediction to atmospheric effects and degradation of image spatial resolution using hyperspectral VNIR/SWIR imagery,” Remote Sens. Environ. 164, 1–15 (2015).
[Crossref]

Rev. Sci. Instrum. (1)

E. Ammannito, G. Filacchione, A. Coradini, F. Capaccioni, G. Piccioni, M. De Sanctis, M. Dami, and A. Barbis, “On-ground characterization of Rosetta/VIRTIS-M. I. Spectral and geometrical calibrations,” Rev. Sci. Instrum. 77, 093109 (2006).
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Sensors (2)

N. Oppelt and W. Mauser, “The airborne visible/infrared imaging spectrometer AVIS: Design, characterization and calibration,” Sensors 7, 1934–1953 (2007).
[Crossref]

L. Zhang, C. Huang, T. Wu, F. Zhang, and Q. Tong, “Laboratory calibration of a field imaging spectrometer system,” Sensors 11, 2408–2425 (2011).
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M. Bertero and P. Boccacci, Introduction to Inverse Problems in Imaging (CRC Press, 1998).
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E. Thiébaut, “Introduction to Image Reconstruction and Inverse Problems,” in Optics in Astrophysics, R. Foy and F. C. Foy, eds. (Springer, 2005).

T. J. Cornwell, “Image restoration,” in Diffraction-Limited Imaging with Very Large Telescopes, D. M. Alloin and J.-M. Mariotti, eds. (Springer, 1989).
[Crossref]

S. J. Choquette and A. Urbas, The National Institute of Standards and Technology (email personal communication, 2015).

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Figures (11)

Fig. 1
Fig. 1 A diagram of the image restoration procedure.
Fig. 2
Fig. 2 SWIR imaging spectrometer setup.
Fig. 3
Fig. 3 (a) Response functions in the across-track direction (top row), in the spectral direction (middle row) and in the along-track direction (bottom row) observed at the 252th across-track position and at the 23rd and 168th spectral position. The corresponding acquired intensity profiles and the model fits at the (b) 23rd and (c) 168th spectral positions.
Fig. 4
Fig. 4 (a) Error bars for the positions of the dot centers in the acquired and the restored glass distortion target images at four spectral and five across-track regions. The dotted horizontal line represents the limit imposed by the manufacturing accuracy of the calibration targets. (b) RMSE distribution of the dot center positions in the spectral direction for the acquired and the restored glass distortion target images. (c) An image of the glass distortion target used for validation.
Fig. 5
Fig. 5 (a)–(e) Five SRM 2035 band locations at different across-track positions in the acquired and the restored image with the certified uncertainties. (f) SRM 2035 spectrum with the designated bands that were used for validation.
Fig. 6
Fig. 6 FWHM in the acquired and the restored image in the (a) across-track and (b) along-track direction as a function of the spectral position. FWHM of the (c) He 1083 nm and (d) Kr 2191 nm spectral lines in the acquired and the restored image as a function of the across-track position.
Fig. 7
Fig. 7 (a) Spectral and (b) spatial coregistration error maps of the acquired and restored images.
Fig. 8
Fig. 8 (a) Across-track and (b) along-track spatial coregistration error maps of the acquired and restored images.
Fig. 9
Fig. 9 Acquired and restored profiles of the (a) Kr lines at 1678.5, 1689.0, 1689.7, 1693.6 and 1709.9 nm at five different across-track positions, (b) edge in the image of the validation target for the across-track direction at five different spectral positions and (c) the glass distortion target at the 151th across-track pixel and at five different spectral positions.
Fig. 10
Fig. 10 The acquired (upper row) and the restored (bottom row) 2D slices of a 3D coffee beans and pepper image segment containing pixels [100–250, 1–235, 400–550] where the position in brackets represent the across-track, spectral and along-track directions, respectively. The displayed slices are located at the 175th across-track, 55th spectral and 475th along-track pixel.
Fig. 11
Fig. 11 The acquired (upper row) and the restored (bottom row) 2D slices of a 3D electronic circuit image segment containing pixels [90–240, 1–235, 210–360]. The displayed slices are located at the 165th across-track, 115th spectral, and 285th along-track pixel.

Tables (2)

Tables Icon

Table 1 Adopted basis function and baseline models along the spectral and the two spatial directions. Abbreviations: G stands for Gaussian, x1 × x2 s.n. stands for the number of nodes in the bivariate spline model and x1 + x2 + ··· + xn p.d. stands for the degree of an n-dimensional polynomial defined as the sum of its powers.

Tables Icon

Table 2 Average values and standard deviations of the displacements and FWHM in each direction before and after the restoration.

Equations (7)

Equations on this page are rendered with MathJax. Learn more.

o ( u , w , z ) = g ( u , w , z ) * h ( u , w , z ) + b ( u , w , z ) + ε ( u , w , z ) ,
h i , j ( u , w , z ) = f ( u , w , z , λ 0 ( i , j ) , λ 1 ( i , j ) , , λ n ( i , j ) ) ,
χ = ε ( u , w , z ) 2 ,
o ˜ k + 1 ( u , w , z ) = o ˜ k ( u , w , z ) = Ω o ( u , w , z ) d ˜ k ( u , w , z ) h ^ u , w ( u u , w w , z z ) d u d w d z Ω h u , w ( u , w , z ) d u d w d z ,
r k ( u , w , z ) = o ( u , w , z ) d ˜ k ( u , w , z ) ,
d ˜ k ( u , w , z ) = Ω o ˜ k ( u , w , z ) h u , w ( u u , w w , z z ) d u d w d z .
σ r k 1 σ r k σ r k < ξ .

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