Abstract

Measuring the shape (coordinates x, y, z ) and spectral characteristics (wavelength-dependent reflectance R (λi)) of macroscopic objects as a function of time (t) is of great interest in areas such as medical imaging, precision agriculture, or optical sorting. Here, we present an approach that allows to determine all these quantities with high resolution and accuracy, enabling measurement in five dimensions. We call this approach 5D hyperspectral imaging. We describe the design and implementation of a 5D sensor operating in the visible to near-infrared spectral range, which provides excellent spatial and spectral resolution, great depth accuracy, and high frame rates. The results of various experiments strongly indicate the great benefit of the new technology.

© 2018 Optical Society of America under the terms of the OSA Open Access Publishing Agreement

Full Article  |  PDF Article
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References

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2018 (1)

S. Heist, P. Dietrich, M. Landmann, P. Kühmstedt, and G. Notni, “High-speed 3D shape measurement by GOBO projection of aperiodic sinusoidal fringes: a performance analysis,” Proc. SPIE 10667, 106670A (2018).

2017 (3)

2016 (8)

P. Agrawal, K. Tack, B. Geelen, B. Masschelein, P. M. A. Moran, A. Lambrechts, and M. Jayapala, “Characterization of VNIR hyperspectral sensors with monolithically integrated optical filters,” Proc. IS&T 2016, 1–7 (2016).

J. Behmann, A.-K. Mahlein, S. Paulus, J. Dupuis, H. Kuhlmann, E.-C. Oerke, and L. Plümer, “Generation and application of hyperspectral 3D plant models: methods and challenges,” Mach. Vis. Appl. 27, 611–624 (2016).
[Crossref]

R. Bridgelall, J. B. Rafert, D. Atwood, and D. D. Tolliver, “Hyperspectral range imaging for transportation systems,” Proc. SPIE 9803, 98032Y (2016).
[Crossref]

J. Wu, B. Xiong, X. Lin, J. He, J. Suo, and Q. Dai, “Snapshot hyperspectral volumetric microscopy,” Sci. Rep. 6, 24624 (2016).
[Crossref] [PubMed]

C. Zhang, M. Rosenberger, A. Breitbarth, and G. Notni, “A novel 3D multispectral vision system based on filter wheel cameras,” IEEE Transactions on Imaging Syst. Tech. 4, 267–272 (2016).

S Zhang, P. Liu, J. Huang, and R. Xu, “Multiview hyperspectral topography of tissue structural and functional characteristics,” J. Biomed. Opt. 21, 016012 (2016).
[Crossref]

E. Honkavaara, M. A. Eskelinen, I. Pölönen, H. Saari, H. Ojanen, R. Mannila, C. Holmlund, T. Hakala, P. Litkey, T. Rosnell, N. Viljanen, and M. Pulkkanen, “Remote sensing of 3-D geometry and surface moisture of a peat production area using hyperspectral frame cameras in visible to short-wave infrared spectral ranges onboard a small unmanned airborne vehicle (UAV),” IEEE Transactions on Geosci. Remote. Sens. 54, 5440–5454 (2016).
[Crossref]

S. Heist, P. Lutzke, I. Schmidt, P. Dietrich, P. Kühmstedt, A. Tünnermann, and G. Notni, “High-speed three-dimensional shape measurement using GOBO projection,” Opt. Lasers Eng. 87, 90–96 (2016).
[Crossref]

2015 (1)

P. Lutzke, S. Heist, P. Kühmstedt, R. Kowarschik, and G. Notni, “Monte carlo simulation of three-dimensional measurements of translucent objects,” Opt. Eng. 54, 084111 (2015).
[Crossref]

2014 (7)

B. Geelen, N. Tack, and A. Lambrechts, “A compact snapshot multispectral imager with a monolithically integrated per-pixel filter mosaic,” Proc. SPIE 8974, 89740L (2014).
[Crossref]

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

H. Liang, A. Lucian, R. Lange, C. S. Cheung, and B. Su, “Remote spectral imaging with simultaneous extraction of 3D topography for historical wall paintings,” ISPRS J. Photogramm. Remote. Sens. 95, 13–22 (2014).
[Crossref]

R. M. Willett, M. F. Duarte, M. A. Davenport, and R. G. Baraniuk, “Sparsity and structure in hyperspectral imaging : Sensing, reconstruction, and target detection,” IEEE Signal Process. Mag. 31, 116–126 (2014).
[Crossref]

S. Heist, A. Mann, P. Kühmstedt, P. Schreiber, and G. Notni, “Array projection of aperiodic sinusoidal fringes for high-speed three-dimensional shape measurement,” Opt. Eng. 53, 112208 (2014).
[Crossref]

A. Shahzad, M. N. Saad, N. Walter, A. S. Malik, and F. Meriaudeau, “Hyperspectral venous image quality assessment for optimum illumination range selection based on skin tone characteristics,” Biomed. Eng. Online 13, 109 (2014).
[Crossref] [PubMed]

G. Lu and B. Fei, “Medical hyperspectral imaging: a review,” J. Biomed. Opt. 19, 19–24 (2014).
[Crossref]

2013 (1)

N. Hagen and M. W. Kudenov, “Review of snapshot spectral imaging technologies,” Opt. Eng. 52, 090901 (2013).
[Crossref]

2012 (6)

M. H. Kim, T. A. Harvey, D. S. Kittle, H. Rushmeier, J. Dorsey, R. O. Prum, and D. J. Brady, “3D imaging spectroscopy for measuring hyperspectral patterns on solid objects,” ACM Trans. Graph. 31, 38 (2012).
[Crossref]

A.-K. Mahlein, U. Steiner, C. Hillnhütter, H.-W. Dehne, and E.-C. Oerke, “Hyperspectral imaging for small-scale analysis of symptoms caused by different sugar beet diseases,” Plant Methods 8, 3 (2012).
[Crossref] [PubMed]

H. Liang, “Advances in multispectral and hyperspectral imaging for archaeology and art conservation,” Appl. Phys. A 106, 309–323 (2012).
[Crossref]

Q. Zhang, Q. Li, and G. Zhang, “Rapid determination of leaf water content using VIS/NIR spectroscopy analysis with wavelength selection,” Spectrosc. Int. J. 27, 93–105 (2012).
[Crossref]

N. Tack, A. Lambrechts, P. Soussan, and L. Haspeslagh, “A compact, high-speed, and low-cost hyperspectral imager,” Proc. SPIE 8266, 82660Q (2012).
[Crossref]

P. Lutzke, P. Kühmstedt, and G. Notni, “Fast error simulation of optical 3D measurements at translucent objects,” Proc. SPIE 8493, 84930U (2012).
[Crossref]

2011 (2)

P. Lutzke, P. Kühmstedt, and G. Notni, “Measuring error compensation on three-dimensional scans of translucent objects,” Opt. Eng. 50, 063601 (2011).
[Crossref]

J. Geng, “Structured-light 3D surface imaging: a tutorial,” Adv. Opt. Photon. 3, 128–160 (2011).
[Crossref]

2010 (1)

J. Salvi, S. Fernandez, T. Pribanic, and X. Llado, “A state of the art in structured light patterns for surface profilometry,” Pattern Recogn. 43, 2666–2680 (2010).
[Crossref]

2007 (2)

B. M. Nicolaï, K. Beullens, E. Bobelyn, A. Peirs, W. Saeys, K. I. Theron, and J. Lammertyn, “Nondestructive measurement of fruit and vegetable quality by means of NIR spectroscopy: A review,” Postharvest Biol. Technol. 46, 99–118 (2007).
[Crossref]

A. A. Gowen, C. P. O’Donnell, P. J. Cullen, G. Downey, and J. M. Frias, “Hyperspectral imaging – an emerging process analytical tool for food quality and safety control,” Trends Food Sci. Technol. 18, 590–598 (2007).
[Crossref]

2006 (1)

C. Fischer and I. Kakoulli, “Multispectral and hyperspectral imaging technologies in conservation: current research and potential applications,” Stud. Conserv. 51, 3–16 (2006).
[Crossref]

2005 (3)

J. Burger and P. Geladi, “Hyperspectral NIR image regression part I: calibration and correction,” J. Chemom. 19, 355–363 (2005).
[Crossref]

M. Min and W. S. Lee, “Determination of significant wavelengths and prediction of nitrogen content for citrus,” Trans. ASAE 48, 455–461 (2005).
[Crossref]

D. Zhao, K. R. Reddy, V. G. Kakani, and V. Reddy, “Nitrogen deficiency effects on plant growth, leaf photosynthesis, and hyperspectral reflectance properties of sorghum,” Eur. J. Agron. 22, 391–403 (2005).
[Crossref]

2003 (3)

N. J. Mitra and A. Nguyen, “Estimating surface normals in noisy point cloud data,” Proc. ASCG 19, 322–328 (2003).

D. A. Sims and J. A. Gamon, “Estimation of vegetation water content and photosynthetic tissue area from spectral reflectance: a comparison of indices based on liquid water and chlorophyll absorption features,” Remote. Sens. Environ. 84, 526–537 (2003).
[Crossref]

C. Balas, V. Papadakis, N. Papadakis, A. Papadakis, E. Vazgiouraki, and G. Themelis, “A novel hyper-spectral imaging apparatus for the non-destructive analysis of objects of artistic and historic value,” J. Cult. Herit. 4(1), 330–337 (2003).
[Crossref]

2000 (1)

Z. Zhang, “A flexible new technique for camera calibration,” IEEE Transactions on Pattern Analysis Mach. Intell. 22, 1330–1334 (2000).
[Crossref]

1997 (1)

J. Peñuelas, J. Piñol, R. Ogaya, and I. Filella, “Estimation of plant water concentration by the reflectance water index wi (R900/R970),” Int. J. Remote. Sens. 18, 2869–2875 (1997).
[Crossref]

1985 (1)

A. F. H. Goetz, G. Vane, J. E. Solomon, and B. N. Rock, “Imaging spectrometry for earth remote sensing,” Science 228, 1147–1153 (1985).
[Crossref] [PubMed]

1979 (1)

S. Ullman, “The interpretation of structure from motion,” Proc. R. Soc. Lond., B, Biol. Sci. 203, 405–426 (1979).
[Crossref] [PubMed]

Aasen, H.

H. Aasen, “The acquisition of hyperspectral digital surface models of crops from UAV snapshot cameras,” Ph.D. thesis, University of Cologne (2016).

Agrawal, P.

P. Agrawal, K. Tack, B. Geelen, B. Masschelein, P. M. A. Moran, A. Lambrechts, and M. Jayapala, “Characterization of VNIR hyperspectral sensors with monolithically integrated optical filters,” Proc. IS&T 2016, 1–7 (2016).

Atwood, D.

R. Bridgelall, J. B. Rafert, D. Atwood, and D. D. Tolliver, “Hyperspectral range imaging for transportation systems,” Proc. SPIE 9803, 98032Y (2016).
[Crossref]

Balas, C.

C. Balas, V. Papadakis, N. Papadakis, A. Papadakis, E. Vazgiouraki, and G. Themelis, “A novel hyper-spectral imaging apparatus for the non-destructive analysis of objects of artistic and historic value,” J. Cult. Herit. 4(1), 330–337 (2003).
[Crossref]

Baraniuk, R. G.

R. M. Willett, M. F. Duarte, M. A. Davenport, and R. G. Baraniuk, “Sparsity and structure in hyperspectral imaging : Sensing, reconstruction, and target detection,” IEEE Signal Process. Mag. 31, 116–126 (2014).
[Crossref]

Behmann, J.

J. Behmann, A.-K. Mahlein, S. Paulus, J. Dupuis, H. Kuhlmann, E.-C. Oerke, and L. Plümer, “Generation and application of hyperspectral 3D plant models: methods and challenges,” Mach. Vis. Appl. 27, 611–624 (2016).
[Crossref]

Beullens, K.

B. M. Nicolaï, K. Beullens, E. Bobelyn, A. Peirs, W. Saeys, K. I. Theron, and J. Lammertyn, “Nondestructive measurement of fruit and vegetable quality by means of NIR spectroscopy: A review,” Postharvest Biol. Technol. 46, 99–118 (2007).
[Crossref]

Bhatia, A. B.

M. Born, E. Wolf, A. B. Bhatia, P. C. Clemmow, D. Gabor, A. R. Stokes, A. M. Taylor, P. A. Wayman, and W. L. Wilcock, Principles of Optics: Electromagnetic Theory of Propagation, Interference and Diffraction of Light (Cambridge University, 1999).
[Crossref]

Bobelyn, E.

B. M. Nicolaï, K. Beullens, E. Bobelyn, A. Peirs, W. Saeys, K. I. Theron, and J. Lammertyn, “Nondestructive measurement of fruit and vegetable quality by means of NIR spectroscopy: A review,” Postharvest Biol. Technol. 46, 99–118 (2007).
[Crossref]

Böhm, J.

T. Luhmann, S. Robson, S. Kyle, and J. Böhm, Close-Range Photogrammetry and 3D Imaging (Walter de Gruyter, 2014).

Born, M.

M. Born, E. Wolf, A. B. Bhatia, P. C. Clemmow, D. Gabor, A. R. Stokes, A. M. Taylor, P. A. Wayman, and W. L. Wilcock, Principles of Optics: Electromagnetic Theory of Propagation, Interference and Diffraction of Light (Cambridge University, 1999).
[Crossref]

Brady, D. J.

M. H. Kim, T. A. Harvey, D. S. Kittle, H. Rushmeier, J. Dorsey, R. O. Prum, and D. J. Brady, “3D imaging spectroscopy for measuring hyperspectral patterns on solid objects,” ACM Trans. Graph. 31, 38 (2012).
[Crossref]

Breitbarth, A.

C. Zhang, M. Rosenberger, A. Breitbarth, and G. Notni, “Wavelength dependency of optical 3D measurements at translucent objects using fringe pattern projection,” Proc. SPIE 10220, 1022007 (2017).
[Crossref]

C. Zhang, M. Rosenberger, A. Breitbarth, and G. Notni, “A novel 3D multispectral vision system based on filter wheel cameras,” IEEE Transactions on Imaging Syst. Tech. 4, 267–272 (2016).

Bridgelall, R.

R. Bridgelall, J. B. Rafert, D. Atwood, and D. D. Tolliver, “Hyperspectral range imaging for transportation systems,” Proc. SPIE 9803, 98032Y (2016).
[Crossref]

Burger, J.

J. Burger and P. Geladi, “Hyperspectral NIR image regression part I: calibration and correction,” J. Chemom. 19, 355–363 (2005).
[Crossref]

Cheung, C. S.

H. Liang, A. Lucian, R. Lange, C. S. Cheung, and B. Su, “Remote spectral imaging with simultaneous extraction of 3D topography for historical wall paintings,” ISPRS J. Photogramm. Remote. Sens. 95, 13–22 (2014).
[Crossref]

Clemmow, P. C.

M. Born, E. Wolf, A. B. Bhatia, P. C. Clemmow, D. Gabor, A. R. Stokes, A. M. Taylor, P. A. Wayman, and W. L. Wilcock, Principles of Optics: Electromagnetic Theory of Propagation, Interference and Diffraction of Light (Cambridge University, 1999).
[Crossref]

Cullen, P. J.

A. A. Gowen, C. P. O’Donnell, P. J. Cullen, G. Downey, and J. M. Frias, “Hyperspectral imaging – an emerging process analytical tool for food quality and safety control,” Trends Food Sci. Technol. 18, 590–598 (2007).
[Crossref]

Dai, Q.

J. Wu, B. Xiong, X. Lin, J. He, J. Suo, and Q. Dai, “Snapshot hyperspectral volumetric microscopy,” Sci. Rep. 6, 24624 (2016).
[Crossref] [PubMed]

Davenport, M. A.

R. M. Willett, M. F. Duarte, M. A. Davenport, and R. G. Baraniuk, “Sparsity and structure in hyperspectral imaging : Sensing, reconstruction, and target detection,” IEEE Signal Process. Mag. 31, 116–126 (2014).
[Crossref]

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S. Heist, P. Lutzke, I. Schmidt, P. Dietrich, P. Kühmstedt, A. Tünnermann, and G. Notni, “High-speed three-dimensional shape measurement using GOBO projection,” Opt. Lasers Eng. 87, 90–96 (2016).
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P. Agrawal, K. Tack, B. Geelen, B. Masschelein, P. M. A. Moran, A. Lambrechts, and M. Jayapala, “Characterization of VNIR hyperspectral sensors with monolithically integrated optical filters,” Proc. IS&T 2016, 1–7 (2016).

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S. Heist, P. Kühmstedt, A. Tünnermann, and G. Notni, “BRDF-dependent accuracy of array projection-based 3D sensors,” Appl. Opt. 56, 2162–2170 (2017).
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E. Honkavaara, M. A. Eskelinen, I. Pölönen, H. Saari, H. Ojanen, R. Mannila, C. Holmlund, T. Hakala, P. Litkey, T. Rosnell, N. Viljanen, and M. Pulkkanen, “Remote sensing of 3-D geometry and surface moisture of a peat production area using hyperspectral frame cameras in visible to short-wave infrared spectral ranges onboard a small unmanned airborne vehicle (UAV),” IEEE Transactions on Geosci. Remote. Sens. 54, 5440–5454 (2016).
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M. H. Kim, T. A. Harvey, D. S. Kittle, H. Rushmeier, J. Dorsey, R. O. Prum, and D. J. Brady, “3D imaging spectroscopy for measuring hyperspectral patterns on solid objects,” ACM Trans. Graph. 31, 38 (2012).
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M. H. Kim, T. A. Harvey, D. S. Kittle, H. Rushmeier, J. Dorsey, R. O. Prum, and D. J. Brady, “3D imaging spectroscopy for measuring hyperspectral patterns on solid objects,” ACM Trans. Graph. 31, 38 (2012).
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P. Lutzke, S. Heist, P. Kühmstedt, R. Kowarschik, and G. Notni, “Monte carlo simulation of three-dimensional measurements of translucent objects,” Opt. Eng. 54, 084111 (2015).
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N. Hagen and M. W. Kudenov, “Review of snapshot spectral imaging technologies,” Opt. Eng. 52, 090901 (2013).
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S. Heist, P. Dietrich, M. Landmann, P. Kühmstedt, and G. Notni, “High-speed 3D shape measurement by GOBO projection of aperiodic sinusoidal fringes: a performance analysis,” Proc. SPIE 10667, 106670A (2018).

S. Heist, P. Kühmstedt, A. Tünnermann, and G. Notni, “BRDF-dependent accuracy of array projection-based 3D sensors,” Appl. Opt. 56, 2162–2170 (2017).
[Crossref] [PubMed]

S. Heist, P. Lutzke, I. Schmidt, P. Dietrich, P. Kühmstedt, A. Tünnermann, and G. Notni, “High-speed three-dimensional shape measurement using GOBO projection,” Opt. Lasers Eng. 87, 90–96 (2016).
[Crossref]

P. Lutzke, S. Heist, P. Kühmstedt, R. Kowarschik, and G. Notni, “Monte carlo simulation of three-dimensional measurements of translucent objects,” Opt. Eng. 54, 084111 (2015).
[Crossref]

S. Heist, A. Mann, P. Kühmstedt, P. Schreiber, and G. Notni, “Array projection of aperiodic sinusoidal fringes for high-speed three-dimensional shape measurement,” Opt. Eng. 53, 112208 (2014).
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P. Lutzke, P. Kühmstedt, and G. Notni, “Fast error simulation of optical 3D measurements at translucent objects,” Proc. SPIE 8493, 84930U (2012).
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P. Lutzke, P. Kühmstedt, and G. Notni, “Measuring error compensation on three-dimensional scans of translucent objects,” Opt. Eng. 50, 063601 (2011).
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B. Geelen, N. Tack, and A. Lambrechts, “A compact snapshot multispectral imager with a monolithically integrated per-pixel filter mosaic,” Proc. SPIE 8974, 89740L (2014).
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N. Tack, A. Lambrechts, P. Soussan, and L. Haspeslagh, “A compact, high-speed, and low-cost hyperspectral imager,” Proc. SPIE 8266, 82660Q (2012).
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B. M. Nicolaï, K. Beullens, E. Bobelyn, A. Peirs, W. Saeys, K. I. Theron, and J. Lammertyn, “Nondestructive measurement of fruit and vegetable quality by means of NIR spectroscopy: A review,” Postharvest Biol. Technol. 46, 99–118 (2007).
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S. Heist, P. Dietrich, M. Landmann, P. Kühmstedt, and G. Notni, “High-speed 3D shape measurement by GOBO projection of aperiodic sinusoidal fringes: a performance analysis,” Proc. SPIE 10667, 106670A (2018).

Lange, R.

H. Liang, A. Lucian, R. Lange, C. S. Cheung, and B. Su, “Remote spectral imaging with simultaneous extraction of 3D topography for historical wall paintings,” ISPRS J. Photogramm. Remote. Sens. 95, 13–22 (2014).
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M. Min and W. S. Lee, “Determination of significant wavelengths and prediction of nitrogen content for citrus,” Trans. ASAE 48, 455–461 (2005).
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H. Liang, A. Lucian, R. Lange, C. S. Cheung, and B. Su, “Remote spectral imaging with simultaneous extraction of 3D topography for historical wall paintings,” ISPRS J. Photogramm. Remote. Sens. 95, 13–22 (2014).
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Lin, X.

J. Wu, B. Xiong, X. Lin, J. He, J. Suo, and Q. Dai, “Snapshot hyperspectral volumetric microscopy,” Sci. Rep. 6, 24624 (2016).
[Crossref] [PubMed]

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E. Honkavaara, M. A. Eskelinen, I. Pölönen, H. Saari, H. Ojanen, R. Mannila, C. Holmlund, T. Hakala, P. Litkey, T. Rosnell, N. Viljanen, and M. Pulkkanen, “Remote sensing of 3-D geometry and surface moisture of a peat production area using hyperspectral frame cameras in visible to short-wave infrared spectral ranges onboard a small unmanned airborne vehicle (UAV),” IEEE Transactions on Geosci. Remote. Sens. 54, 5440–5454 (2016).
[Crossref]

Liu, P.

S Zhang, P. Liu, J. Huang, and R. Xu, “Multiview hyperspectral topography of tissue structural and functional characteristics,” J. Biomed. Opt. 21, 016012 (2016).
[Crossref]

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J. Salvi, S. Fernandez, T. Pribanic, and X. Llado, “A state of the art in structured light patterns for surface profilometry,” Pattern Recogn. 43, 2666–2680 (2010).
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G. Lu and B. Fei, “Medical hyperspectral imaging: a review,” J. Biomed. Opt. 19, 010901 (2014).
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G. Lu and B. Fei, “Medical hyperspectral imaging: a review,” J. Biomed. Opt. 19, 19–24 (2014).
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H. Liang, A. Lucian, R. Lange, C. S. Cheung, and B. Su, “Remote spectral imaging with simultaneous extraction of 3D topography for historical wall paintings,” ISPRS J. Photogramm. Remote. Sens. 95, 13–22 (2014).
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T. Luhmann, S. Robson, S. Kyle, and J. Böhm, Close-Range Photogrammetry and 3D Imaging (Walter de Gruyter, 2014).

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S. Heist, P. Lutzke, I. Schmidt, P. Dietrich, P. Kühmstedt, A. Tünnermann, and G. Notni, “High-speed three-dimensional shape measurement using GOBO projection,” Opt. Lasers Eng. 87, 90–96 (2016).
[Crossref]

P. Lutzke, S. Heist, P. Kühmstedt, R. Kowarschik, and G. Notni, “Monte carlo simulation of three-dimensional measurements of translucent objects,” Opt. Eng. 54, 084111 (2015).
[Crossref]

P. Lutzke, P. Kühmstedt, and G. Notni, “Fast error simulation of optical 3D measurements at translucent objects,” Proc. SPIE 8493, 84930U (2012).
[Crossref]

P. Lutzke, P. Kühmstedt, and G. Notni, “Measuring error compensation on three-dimensional scans of translucent objects,” Opt. Eng. 50, 063601 (2011).
[Crossref]

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J. Behmann, A.-K. Mahlein, S. Paulus, J. Dupuis, H. Kuhlmann, E.-C. Oerke, and L. Plümer, “Generation and application of hyperspectral 3D plant models: methods and challenges,” Mach. Vis. Appl. 27, 611–624 (2016).
[Crossref]

A.-K. Mahlein, U. Steiner, C. Hillnhütter, H.-W. Dehne, and E.-C. Oerke, “Hyperspectral imaging for small-scale analysis of symptoms caused by different sugar beet diseases,” Plant Methods 8, 3 (2012).
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A. Shahzad, M. N. Saad, N. Walter, A. S. Malik, and F. Meriaudeau, “Hyperspectral venous image quality assessment for optimum illumination range selection based on skin tone characteristics,” Biomed. Eng. Online 13, 109 (2014).
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S. Heist, A. Mann, P. Kühmstedt, P. Schreiber, and G. Notni, “Array projection of aperiodic sinusoidal fringes for high-speed three-dimensional shape measurement,” Opt. Eng. 53, 112208 (2014).
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Mannila, R.

E. Honkavaara, M. A. Eskelinen, I. Pölönen, H. Saari, H. Ojanen, R. Mannila, C. Holmlund, T. Hakala, P. Litkey, T. Rosnell, N. Viljanen, and M. Pulkkanen, “Remote sensing of 3-D geometry and surface moisture of a peat production area using hyperspectral frame cameras in visible to short-wave infrared spectral ranges onboard a small unmanned airborne vehicle (UAV),” IEEE Transactions on Geosci. Remote. Sens. 54, 5440–5454 (2016).
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P. Agrawal, K. Tack, B. Geelen, B. Masschelein, P. M. A. Moran, A. Lambrechts, and M. Jayapala, “Characterization of VNIR hyperspectral sensors with monolithically integrated optical filters,” Proc. IS&T 2016, 1–7 (2016).

Meriaudeau, F.

A. Shahzad, M. N. Saad, N. Walter, A. S. Malik, and F. Meriaudeau, “Hyperspectral venous image quality assessment for optimum illumination range selection based on skin tone characteristics,” Biomed. Eng. Online 13, 109 (2014).
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M. Min and W. S. Lee, “Determination of significant wavelengths and prediction of nitrogen content for citrus,” Trans. ASAE 48, 455–461 (2005).
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P. Agrawal, K. Tack, B. Geelen, B. Masschelein, P. M. A. Moran, A. Lambrechts, and M. Jayapala, “Characterization of VNIR hyperspectral sensors with monolithically integrated optical filters,” Proc. IS&T 2016, 1–7 (2016).

Nguyen, A.

N. J. Mitra and A. Nguyen, “Estimating surface normals in noisy point cloud data,” Proc. ASCG 19, 322–328 (2003).

Nicolaï, B. M.

B. M. Nicolaï, K. Beullens, E. Bobelyn, A. Peirs, W. Saeys, K. I. Theron, and J. Lammertyn, “Nondestructive measurement of fruit and vegetable quality by means of NIR spectroscopy: A review,” Postharvest Biol. Technol. 46, 99–118 (2007).
[Crossref]

Notni, G.

S. Heist, P. Dietrich, M. Landmann, P. Kühmstedt, and G. Notni, “High-speed 3D shape measurement by GOBO projection of aperiodic sinusoidal fringes: a performance analysis,” Proc. SPIE 10667, 106670A (2018).

C. Zhang, M. Rosenberger, A. Breitbarth, and G. Notni, “Wavelength dependency of optical 3D measurements at translucent objects using fringe pattern projection,” Proc. SPIE 10220, 1022007 (2017).
[Crossref]

S. Heist, P. Kühmstedt, A. Tünnermann, and G. Notni, “BRDF-dependent accuracy of array projection-based 3D sensors,” Appl. Opt. 56, 2162–2170 (2017).
[Crossref] [PubMed]

S. Heist, P. Lutzke, I. Schmidt, P. Dietrich, P. Kühmstedt, A. Tünnermann, and G. Notni, “High-speed three-dimensional shape measurement using GOBO projection,” Opt. Lasers Eng. 87, 90–96 (2016).
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C. Zhang, M. Rosenberger, A. Breitbarth, and G. Notni, “A novel 3D multispectral vision system based on filter wheel cameras,” IEEE Transactions on Imaging Syst. Tech. 4, 267–272 (2016).

P. Lutzke, S. Heist, P. Kühmstedt, R. Kowarschik, and G. Notni, “Monte carlo simulation of three-dimensional measurements of translucent objects,” Opt. Eng. 54, 084111 (2015).
[Crossref]

S. Heist, A. Mann, P. Kühmstedt, P. Schreiber, and G. Notni, “Array projection of aperiodic sinusoidal fringes for high-speed three-dimensional shape measurement,” Opt. Eng. 53, 112208 (2014).
[Crossref]

P. Lutzke, P. Kühmstedt, and G. Notni, “Fast error simulation of optical 3D measurements at translucent objects,” Proc. SPIE 8493, 84930U (2012).
[Crossref]

P. Lutzke, P. Kühmstedt, and G. Notni, “Measuring error compensation on three-dimensional scans of translucent objects,” Opt. Eng. 50, 063601 (2011).
[Crossref]

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A. A. Gowen, C. P. O’Donnell, P. J. Cullen, G. Downey, and J. M. Frias, “Hyperspectral imaging – an emerging process analytical tool for food quality and safety control,” Trends Food Sci. Technol. 18, 590–598 (2007).
[Crossref]

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J. Behmann, A.-K. Mahlein, S. Paulus, J. Dupuis, H. Kuhlmann, E.-C. Oerke, and L. Plümer, “Generation and application of hyperspectral 3D plant models: methods and challenges,” Mach. Vis. Appl. 27, 611–624 (2016).
[Crossref]

A.-K. Mahlein, U. Steiner, C. Hillnhütter, H.-W. Dehne, and E.-C. Oerke, “Hyperspectral imaging for small-scale analysis of symptoms caused by different sugar beet diseases,” Plant Methods 8, 3 (2012).
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J. Peñuelas, J. Piñol, R. Ogaya, and I. Filella, “Estimation of plant water concentration by the reflectance water index wi (R900/R970),” Int. J. Remote. Sens. 18, 2869–2875 (1997).
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E. Honkavaara, M. A. Eskelinen, I. Pölönen, H. Saari, H. Ojanen, R. Mannila, C. Holmlund, T. Hakala, P. Litkey, T. Rosnell, N. Viljanen, and M. Pulkkanen, “Remote sensing of 3-D geometry and surface moisture of a peat production area using hyperspectral frame cameras in visible to short-wave infrared spectral ranges onboard a small unmanned airborne vehicle (UAV),” IEEE Transactions on Geosci. Remote. Sens. 54, 5440–5454 (2016).
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Ozawa, K.

Papadakis, A.

C. Balas, V. Papadakis, N. Papadakis, A. Papadakis, E. Vazgiouraki, and G. Themelis, “A novel hyper-spectral imaging apparatus for the non-destructive analysis of objects of artistic and historic value,” J. Cult. Herit. 4(1), 330–337 (2003).
[Crossref]

Papadakis, N.

C. Balas, V. Papadakis, N. Papadakis, A. Papadakis, E. Vazgiouraki, and G. Themelis, “A novel hyper-spectral imaging apparatus for the non-destructive analysis of objects of artistic and historic value,” J. Cult. Herit. 4(1), 330–337 (2003).
[Crossref]

Papadakis, V.

C. Balas, V. Papadakis, N. Papadakis, A. Papadakis, E. Vazgiouraki, and G. Themelis, “A novel hyper-spectral imaging apparatus for the non-destructive analysis of objects of artistic and historic value,” J. Cult. Herit. 4(1), 330–337 (2003).
[Crossref]

Paulus, S.

J. Behmann, A.-K. Mahlein, S. Paulus, J. Dupuis, H. Kuhlmann, E.-C. Oerke, and L. Plümer, “Generation and application of hyperspectral 3D plant models: methods and challenges,” Mach. Vis. Appl. 27, 611–624 (2016).
[Crossref]

Peirs, A.

B. M. Nicolaï, K. Beullens, E. Bobelyn, A. Peirs, W. Saeys, K. I. Theron, and J. Lammertyn, “Nondestructive measurement of fruit and vegetable quality by means of NIR spectroscopy: A review,” Postharvest Biol. Technol. 46, 99–118 (2007).
[Crossref]

Peñuelas, J.

J. Peñuelas, J. Piñol, R. Ogaya, and I. Filella, “Estimation of plant water concentration by the reflectance water index wi (R900/R970),” Int. J. Remote. Sens. 18, 2869–2875 (1997).
[Crossref]

Piñol, J.

J. Peñuelas, J. Piñol, R. Ogaya, and I. Filella, “Estimation of plant water concentration by the reflectance water index wi (R900/R970),” Int. J. Remote. Sens. 18, 2869–2875 (1997).
[Crossref]

Plümer, L.

J. Behmann, A.-K. Mahlein, S. Paulus, J. Dupuis, H. Kuhlmann, E.-C. Oerke, and L. Plümer, “Generation and application of hyperspectral 3D plant models: methods and challenges,” Mach. Vis. Appl. 27, 611–624 (2016).
[Crossref]

Pölönen, I.

E. Honkavaara, M. A. Eskelinen, I. Pölönen, H. Saari, H. Ojanen, R. Mannila, C. Holmlund, T. Hakala, P. Litkey, T. Rosnell, N. Viljanen, and M. Pulkkanen, “Remote sensing of 3-D geometry and surface moisture of a peat production area using hyperspectral frame cameras in visible to short-wave infrared spectral ranges onboard a small unmanned airborne vehicle (UAV),” IEEE Transactions on Geosci. Remote. Sens. 54, 5440–5454 (2016).
[Crossref]

Pribanic, T.

J. Salvi, S. Fernandez, T. Pribanic, and X. Llado, “A state of the art in structured light patterns for surface profilometry,” Pattern Recogn. 43, 2666–2680 (2010).
[Crossref]

Prum, R. O.

M. H. Kim, T. A. Harvey, D. S. Kittle, H. Rushmeier, J. Dorsey, R. O. Prum, and D. J. Brady, “3D imaging spectroscopy for measuring hyperspectral patterns on solid objects,” ACM Trans. Graph. 31, 38 (2012).
[Crossref]

Pulkkanen, M.

E. Honkavaara, M. A. Eskelinen, I. Pölönen, H. Saari, H. Ojanen, R. Mannila, C. Holmlund, T. Hakala, P. Litkey, T. Rosnell, N. Viljanen, and M. Pulkkanen, “Remote sensing of 3-D geometry and surface moisture of a peat production area using hyperspectral frame cameras in visible to short-wave infrared spectral ranges onboard a small unmanned airborne vehicle (UAV),” IEEE Transactions on Geosci. Remote. Sens. 54, 5440–5454 (2016).
[Crossref]

Rafert, J. B.

R. Bridgelall, J. B. Rafert, D. Atwood, and D. D. Tolliver, “Hyperspectral range imaging for transportation systems,” Proc. SPIE 9803, 98032Y (2016).
[Crossref]

Reddy, K. R.

D. Zhao, K. R. Reddy, V. G. Kakani, and V. Reddy, “Nitrogen deficiency effects on plant growth, leaf photosynthesis, and hyperspectral reflectance properties of sorghum,” Eur. J. Agron. 22, 391–403 (2005).
[Crossref]

Reddy, V.

D. Zhao, K. R. Reddy, V. G. Kakani, and V. Reddy, “Nitrogen deficiency effects on plant growth, leaf photosynthesis, and hyperspectral reflectance properties of sorghum,” Eur. J. Agron. 22, 391–403 (2005).
[Crossref]

Robson, S.

T. Luhmann, S. Robson, S. Kyle, and J. Böhm, Close-Range Photogrammetry and 3D Imaging (Walter de Gruyter, 2014).

Rock, B. N.

A. F. H. Goetz, G. Vane, J. E. Solomon, and B. N. Rock, “Imaging spectrometry for earth remote sensing,” Science 228, 1147–1153 (1985).
[Crossref] [PubMed]

Rosenberger, M.

C. Zhang, M. Rosenberger, A. Breitbarth, and G. Notni, “Wavelength dependency of optical 3D measurements at translucent objects using fringe pattern projection,” Proc. SPIE 10220, 1022007 (2017).
[Crossref]

C. Zhang, M. Rosenberger, A. Breitbarth, and G. Notni, “A novel 3D multispectral vision system based on filter wheel cameras,” IEEE Transactions on Imaging Syst. Tech. 4, 267–272 (2016).

Rosnell, T.

E. Honkavaara, M. A. Eskelinen, I. Pölönen, H. Saari, H. Ojanen, R. Mannila, C. Holmlund, T. Hakala, P. Litkey, T. Rosnell, N. Viljanen, and M. Pulkkanen, “Remote sensing of 3-D geometry and surface moisture of a peat production area using hyperspectral frame cameras in visible to short-wave infrared spectral ranges onboard a small unmanned airborne vehicle (UAV),” IEEE Transactions on Geosci. Remote. Sens. 54, 5440–5454 (2016).
[Crossref]

Rushmeier, H.

M. H. Kim, T. A. Harvey, D. S. Kittle, H. Rushmeier, J. Dorsey, R. O. Prum, and D. J. Brady, “3D imaging spectroscopy for measuring hyperspectral patterns on solid objects,” ACM Trans. Graph. 31, 38 (2012).
[Crossref]

Saad, M. N.

A. Shahzad, M. N. Saad, N. Walter, A. S. Malik, and F. Meriaudeau, “Hyperspectral venous image quality assessment for optimum illumination range selection based on skin tone characteristics,” Biomed. Eng. Online 13, 109 (2014).
[Crossref] [PubMed]

Saari, H.

E. Honkavaara, M. A. Eskelinen, I. Pölönen, H. Saari, H. Ojanen, R. Mannila, C. Holmlund, T. Hakala, P. Litkey, T. Rosnell, N. Viljanen, and M. Pulkkanen, “Remote sensing of 3-D geometry and surface moisture of a peat production area using hyperspectral frame cameras in visible to short-wave infrared spectral ranges onboard a small unmanned airborne vehicle (UAV),” IEEE Transactions on Geosci. Remote. Sens. 54, 5440–5454 (2016).
[Crossref]

Saeys, W.

B. M. Nicolaï, K. Beullens, E. Bobelyn, A. Peirs, W. Saeys, K. I. Theron, and J. Lammertyn, “Nondestructive measurement of fruit and vegetable quality by means of NIR spectroscopy: A review,” Postharvest Biol. Technol. 46, 99–118 (2007).
[Crossref]

Salvi, J.

J. Salvi, S. Fernandez, T. Pribanic, and X. Llado, “A state of the art in structured light patterns for surface profilometry,” Pattern Recogn. 43, 2666–2680 (2010).
[Crossref]

Sato, I.

Schmidt, I.

S. Heist, P. Lutzke, I. Schmidt, P. Dietrich, P. Kühmstedt, A. Tünnermann, and G. Notni, “High-speed three-dimensional shape measurement using GOBO projection,” Opt. Lasers Eng. 87, 90–96 (2016).
[Crossref]

Schreiber, P.

S. Heist, A. Mann, P. Kühmstedt, P. Schreiber, and G. Notni, “Array projection of aperiodic sinusoidal fringes for high-speed three-dimensional shape measurement,” Opt. Eng. 53, 112208 (2014).
[Crossref]

Shahzad, A.

A. Shahzad, M. N. Saad, N. Walter, A. S. Malik, and F. Meriaudeau, “Hyperspectral venous image quality assessment for optimum illumination range selection based on skin tone characteristics,” Biomed. Eng. Online 13, 109 (2014).
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Sims, D. A.

D. A. Sims and J. A. Gamon, “Estimation of vegetation water content and photosynthetic tissue area from spectral reflectance: a comparison of indices based on liquid water and chlorophyll absorption features,” Remote. Sens. Environ. 84, 526–537 (2003).
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A. F. H. Goetz, G. Vane, J. E. Solomon, and B. N. Rock, “Imaging spectrometry for earth remote sensing,” Science 228, 1147–1153 (1985).
[Crossref] [PubMed]

Soussan, P.

N. Tack, A. Lambrechts, P. Soussan, and L. Haspeslagh, “A compact, high-speed, and low-cost hyperspectral imager,” Proc. SPIE 8266, 82660Q (2012).
[Crossref]

Steiner, U.

A.-K. Mahlein, U. Steiner, C. Hillnhütter, H.-W. Dehne, and E.-C. Oerke, “Hyperspectral imaging for small-scale analysis of symptoms caused by different sugar beet diseases,” Plant Methods 8, 3 (2012).
[Crossref] [PubMed]

Stokes, A. R.

M. Born, E. Wolf, A. B. Bhatia, P. C. Clemmow, D. Gabor, A. R. Stokes, A. M. Taylor, P. A. Wayman, and W. L. Wilcock, Principles of Optics: Electromagnetic Theory of Propagation, Interference and Diffraction of Light (Cambridge University, 1999).
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Su, B.

H. Liang, A. Lucian, R. Lange, C. S. Cheung, and B. Su, “Remote spectral imaging with simultaneous extraction of 3D topography for historical wall paintings,” ISPRS J. Photogramm. Remote. Sens. 95, 13–22 (2014).
[Crossref]

Sun, D.-W.

G. ElMasry and D.-W. Sun, “Principles of hyperspectral imaging technology,” in “Hyperspectral Imaging for Food Quality Analysis and Control,” D.-W. Sun, ed. (Academic, San Diego, 2010), pp. 3–43.
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Suo, J.

J. Wu, B. Xiong, X. Lin, J. He, J. Suo, and Q. Dai, “Snapshot hyperspectral volumetric microscopy,” Sci. Rep. 6, 24624 (2016).
[Crossref] [PubMed]

Tack, K.

P. Agrawal, K. Tack, B. Geelen, B. Masschelein, P. M. A. Moran, A. Lambrechts, and M. Jayapala, “Characterization of VNIR hyperspectral sensors with monolithically integrated optical filters,” Proc. IS&T 2016, 1–7 (2016).

Tack, N.

B. Geelen, N. Tack, and A. Lambrechts, “A compact snapshot multispectral imager with a monolithically integrated per-pixel filter mosaic,” Proc. SPIE 8974, 89740L (2014).
[Crossref]

N. Tack, A. Lambrechts, P. Soussan, and L. Haspeslagh, “A compact, high-speed, and low-cost hyperspectral imager,” Proc. SPIE 8266, 82660Q (2012).
[Crossref]

Taylor, A. M.

M. Born, E. Wolf, A. B. Bhatia, P. C. Clemmow, D. Gabor, A. R. Stokes, A. M. Taylor, P. A. Wayman, and W. L. Wilcock, Principles of Optics: Electromagnetic Theory of Propagation, Interference and Diffraction of Light (Cambridge University, 1999).
[Crossref]

Themelis, G.

C. Balas, V. Papadakis, N. Papadakis, A. Papadakis, E. Vazgiouraki, and G. Themelis, “A novel hyper-spectral imaging apparatus for the non-destructive analysis of objects of artistic and historic value,” J. Cult. Herit. 4(1), 330–337 (2003).
[Crossref]

Theron, K. I.

B. M. Nicolaï, K. Beullens, E. Bobelyn, A. Peirs, W. Saeys, K. I. Theron, and J. Lammertyn, “Nondestructive measurement of fruit and vegetable quality by means of NIR spectroscopy: A review,” Postharvest Biol. Technol. 46, 99–118 (2007).
[Crossref]

Tolliver, D. D.

R. Bridgelall, J. B. Rafert, D. Atwood, and D. D. Tolliver, “Hyperspectral range imaging for transportation systems,” Proc. SPIE 9803, 98032Y (2016).
[Crossref]

Tünnermann, A.

S. Heist, P. Kühmstedt, A. Tünnermann, and G. Notni, “BRDF-dependent accuracy of array projection-based 3D sensors,” Appl. Opt. 56, 2162–2170 (2017).
[Crossref] [PubMed]

S. Heist, P. Lutzke, I. Schmidt, P. Dietrich, P. Kühmstedt, A. Tünnermann, and G. Notni, “High-speed three-dimensional shape measurement using GOBO projection,” Opt. Lasers Eng. 87, 90–96 (2016).
[Crossref]

Ullman, S.

S. Ullman, “The interpretation of structure from motion,” Proc. R. Soc. Lond., B, Biol. Sci. 203, 405–426 (1979).
[Crossref] [PubMed]

Vane, G.

A. F. H. Goetz, G. Vane, J. E. Solomon, and B. N. Rock, “Imaging spectrometry for earth remote sensing,” Science 228, 1147–1153 (1985).
[Crossref] [PubMed]

Vazgiouraki, E.

C. Balas, V. Papadakis, N. Papadakis, A. Papadakis, E. Vazgiouraki, and G. Themelis, “A novel hyper-spectral imaging apparatus for the non-destructive analysis of objects of artistic and historic value,” J. Cult. Herit. 4(1), 330–337 (2003).
[Crossref]

Viljanen, N.

E. Honkavaara, M. A. Eskelinen, I. Pölönen, H. Saari, H. Ojanen, R. Mannila, C. Holmlund, T. Hakala, P. Litkey, T. Rosnell, N. Viljanen, and M. Pulkkanen, “Remote sensing of 3-D geometry and surface moisture of a peat production area using hyperspectral frame cameras in visible to short-wave infrared spectral ranges onboard a small unmanned airborne vehicle (UAV),” IEEE Transactions on Geosci. Remote. Sens. 54, 5440–5454 (2016).
[Crossref]

Walter, N.

A. Shahzad, M. N. Saad, N. Walter, A. S. Malik, and F. Meriaudeau, “Hyperspectral venous image quality assessment for optimum illumination range selection based on skin tone characteristics,” Biomed. Eng. Online 13, 109 (2014).
[Crossref] [PubMed]

Wayman, P. A.

M. Born, E. Wolf, A. B. Bhatia, P. C. Clemmow, D. Gabor, A. R. Stokes, A. M. Taylor, P. A. Wayman, and W. L. Wilcock, Principles of Optics: Electromagnetic Theory of Propagation, Interference and Diffraction of Light (Cambridge University, 1999).
[Crossref]

Wilcock, W. L.

M. Born, E. Wolf, A. B. Bhatia, P. C. Clemmow, D. Gabor, A. R. Stokes, A. M. Taylor, P. A. Wayman, and W. L. Wilcock, Principles of Optics: Electromagnetic Theory of Propagation, Interference and Diffraction of Light (Cambridge University, 1999).
[Crossref]

Willett, R. M.

R. M. Willett, M. F. Duarte, M. A. Davenport, and R. G. Baraniuk, “Sparsity and structure in hyperspectral imaging : Sensing, reconstruction, and target detection,” IEEE Signal Process. Mag. 31, 116–126 (2014).
[Crossref]

Wolf, E.

M. Born, E. Wolf, A. B. Bhatia, P. C. Clemmow, D. Gabor, A. R. Stokes, A. M. Taylor, P. A. Wayman, and W. L. Wilcock, Principles of Optics: Electromagnetic Theory of Propagation, Interference and Diffraction of Light (Cambridge University, 1999).
[Crossref]

Wu, J.

J. Wu, B. Xiong, X. Lin, J. He, J. Suo, and Q. Dai, “Snapshot hyperspectral volumetric microscopy,” Sci. Rep. 6, 24624 (2016).
[Crossref] [PubMed]

Xiong, B.

J. Wu, B. Xiong, X. Lin, J. He, J. Suo, and Q. Dai, “Snapshot hyperspectral volumetric microscopy,” Sci. Rep. 6, 24624 (2016).
[Crossref] [PubMed]

Xu, R.

S Zhang, P. Liu, J. Huang, and R. Xu, “Multiview hyperspectral topography of tissue structural and functional characteristics,” J. Biomed. Opt. 21, 016012 (2016).
[Crossref]

Yamaguchi, M.

Zhang, C.

C. Zhang, M. Rosenberger, A. Breitbarth, and G. Notni, “Wavelength dependency of optical 3D measurements at translucent objects using fringe pattern projection,” Proc. SPIE 10220, 1022007 (2017).
[Crossref]

C. Zhang, M. Rosenberger, A. Breitbarth, and G. Notni, “A novel 3D multispectral vision system based on filter wheel cameras,” IEEE Transactions on Imaging Syst. Tech. 4, 267–272 (2016).

Zhang, G.

Q. Zhang, Q. Li, and G. Zhang, “Rapid determination of leaf water content using VIS/NIR spectroscopy analysis with wavelength selection,” Spectrosc. Int. J. 27, 93–105 (2012).
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Zhang, Q.

Q. Zhang, Q. Li, and G. Zhang, “Rapid determination of leaf water content using VIS/NIR spectroscopy analysis with wavelength selection,” Spectrosc. Int. J. 27, 93–105 (2012).
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Zhang, S

S Zhang, P. Liu, J. Huang, and R. Xu, “Multiview hyperspectral topography of tissue structural and functional characteristics,” J. Biomed. Opt. 21, 016012 (2016).
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Zhang, S.

S. Zhang, Handbook of 3D Machine Vision: Optical Metrology and Imaging (CRC, 2013).
[Crossref]

Zhang, Z.

Z. Zhang, “A flexible new technique for camera calibration,” IEEE Transactions on Pattern Analysis Mach. Intell. 22, 1330–1334 (2000).
[Crossref]

Zhao, D.

D. Zhao, K. R. Reddy, V. G. Kakani, and V. Reddy, “Nitrogen deficiency effects on plant growth, leaf photosynthesis, and hyperspectral reflectance properties of sorghum,” Eur. J. Agron. 22, 391–403 (2005).
[Crossref]

Zhou, J.

A. Zia, J. Liang, J. Zhou, and Y. Gao, “3D reconstruction from hyperspectral images,” in Proceedings of the Winter Conference on Applications of Computer Vision (WACV) pp. 318–325 (2015).

Zia, A.

A. Zia, J. Liang, J. Zhou, and Y. Gao, “3D reconstruction from hyperspectral images,” in Proceedings of the Winter Conference on Applications of Computer Vision (WACV) pp. 318–325 (2015).

Zisserman, A.

R. Hartley and A. Zisserman, Multiple View Geometry in Computer Vision (Cambridge University, 2004).
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ACM Trans. Graph. (1)

M. H. Kim, T. A. Harvey, D. S. Kittle, H. Rushmeier, J. Dorsey, R. O. Prum, and D. J. Brady, “3D imaging spectroscopy for measuring hyperspectral patterns on solid objects,” ACM Trans. Graph. 31, 38 (2012).
[Crossref]

Adv. Opt. Photon. (1)

Appl. Opt. (1)

Appl. Phys. A (1)

H. Liang, “Advances in multispectral and hyperspectral imaging for archaeology and art conservation,” Appl. Phys. A 106, 309–323 (2012).
[Crossref]

Biomed. Eng. Online (1)

A. Shahzad, M. N. Saad, N. Walter, A. S. Malik, and F. Meriaudeau, “Hyperspectral venous image quality assessment for optimum illumination range selection based on skin tone characteristics,” Biomed. Eng. Online 13, 109 (2014).
[Crossref] [PubMed]

Eur. J. Agron. (1)

D. Zhao, K. R. Reddy, V. G. Kakani, and V. Reddy, “Nitrogen deficiency effects on plant growth, leaf photosynthesis, and hyperspectral reflectance properties of sorghum,” Eur. J. Agron. 22, 391–403 (2005).
[Crossref]

IEEE Signal Process. Mag. (1)

R. M. Willett, M. F. Duarte, M. A. Davenport, and R. G. Baraniuk, “Sparsity and structure in hyperspectral imaging : Sensing, reconstruction, and target detection,” IEEE Signal Process. Mag. 31, 116–126 (2014).
[Crossref]

IEEE Transactions on Geosci. Remote. Sens. (1)

E. Honkavaara, M. A. Eskelinen, I. Pölönen, H. Saari, H. Ojanen, R. Mannila, C. Holmlund, T. Hakala, P. Litkey, T. Rosnell, N. Viljanen, and M. Pulkkanen, “Remote sensing of 3-D geometry and surface moisture of a peat production area using hyperspectral frame cameras in visible to short-wave infrared spectral ranges onboard a small unmanned airborne vehicle (UAV),” IEEE Transactions on Geosci. Remote. Sens. 54, 5440–5454 (2016).
[Crossref]

IEEE Transactions on Imaging Syst. Tech. (1)

C. Zhang, M. Rosenberger, A. Breitbarth, and G. Notni, “A novel 3D multispectral vision system based on filter wheel cameras,” IEEE Transactions on Imaging Syst. Tech. 4, 267–272 (2016).

IEEE Transactions on Pattern Analysis Mach. Intell. (1)

Z. Zhang, “A flexible new technique for camera calibration,” IEEE Transactions on Pattern Analysis Mach. Intell. 22, 1330–1334 (2000).
[Crossref]

Int. J. Remote. Sens. (1)

J. Peñuelas, J. Piñol, R. Ogaya, and I. Filella, “Estimation of plant water concentration by the reflectance water index wi (R900/R970),” Int. J. Remote. Sens. 18, 2869–2875 (1997).
[Crossref]

ISPRS J. Photogramm. Remote. Sens. (1)

H. Liang, A. Lucian, R. Lange, C. S. Cheung, and B. Su, “Remote spectral imaging with simultaneous extraction of 3D topography for historical wall paintings,” ISPRS J. Photogramm. Remote. Sens. 95, 13–22 (2014).
[Crossref]

J. Biomed. Opt. (3)

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

S Zhang, P. Liu, J. Huang, and R. Xu, “Multiview hyperspectral topography of tissue structural and functional characteristics,” J. Biomed. Opt. 21, 016012 (2016).
[Crossref]

G. Lu and B. Fei, “Medical hyperspectral imaging: a review,” J. Biomed. Opt. 19, 19–24 (2014).
[Crossref]

J. Chemom. (1)

J. Burger and P. Geladi, “Hyperspectral NIR image regression part I: calibration and correction,” J. Chemom. 19, 355–363 (2005).
[Crossref]

J. Cult. Herit. (1)

C. Balas, V. Papadakis, N. Papadakis, A. Papadakis, E. Vazgiouraki, and G. Themelis, “A novel hyper-spectral imaging apparatus for the non-destructive analysis of objects of artistic and historic value,” J. Cult. Herit. 4(1), 330–337 (2003).
[Crossref]

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

Mach. Vis. Appl. (1)

J. Behmann, A.-K. Mahlein, S. Paulus, J. Dupuis, H. Kuhlmann, E.-C. Oerke, and L. Plümer, “Generation and application of hyperspectral 3D plant models: methods and challenges,” Mach. Vis. Appl. 27, 611–624 (2016).
[Crossref]

Opt. Eng. (4)

S. Heist, A. Mann, P. Kühmstedt, P. Schreiber, and G. Notni, “Array projection of aperiodic sinusoidal fringes for high-speed three-dimensional shape measurement,” Opt. Eng. 53, 112208 (2014).
[Crossref]

N. Hagen and M. W. Kudenov, “Review of snapshot spectral imaging technologies,” Opt. Eng. 52, 090901 (2013).
[Crossref]

P. Lutzke, P. Kühmstedt, and G. Notni, “Measuring error compensation on three-dimensional scans of translucent objects,” Opt. Eng. 50, 063601 (2011).
[Crossref]

P. Lutzke, S. Heist, P. Kühmstedt, R. Kowarschik, and G. Notni, “Monte carlo simulation of three-dimensional measurements of translucent objects,” Opt. Eng. 54, 084111 (2015).
[Crossref]

Opt. Lasers Eng. (1)

S. Heist, P. Lutzke, I. Schmidt, P. Dietrich, P. Kühmstedt, A. Tünnermann, and G. Notni, “High-speed three-dimensional shape measurement using GOBO projection,” Opt. Lasers Eng. 87, 90–96 (2016).
[Crossref]

Pattern Recogn. (1)

J. Salvi, S. Fernandez, T. Pribanic, and X. Llado, “A state of the art in structured light patterns for surface profilometry,” Pattern Recogn. 43, 2666–2680 (2010).
[Crossref]

Plant Methods (1)

A.-K. Mahlein, U. Steiner, C. Hillnhütter, H.-W. Dehne, and E.-C. Oerke, “Hyperspectral imaging for small-scale analysis of symptoms caused by different sugar beet diseases,” Plant Methods 8, 3 (2012).
[Crossref] [PubMed]

Postharvest Biol. Technol. (1)

B. M. Nicolaï, K. Beullens, E. Bobelyn, A. Peirs, W. Saeys, K. I. Theron, and J. Lammertyn, “Nondestructive measurement of fruit and vegetable quality by means of NIR spectroscopy: A review,” Postharvest Biol. Technol. 46, 99–118 (2007).
[Crossref]

Proc. ASCG (1)

N. J. Mitra and A. Nguyen, “Estimating surface normals in noisy point cloud data,” Proc. ASCG 19, 322–328 (2003).

Proc. IS&T (1)

P. Agrawal, K. Tack, B. Geelen, B. Masschelein, P. M. A. Moran, A. Lambrechts, and M. Jayapala, “Characterization of VNIR hyperspectral sensors with monolithically integrated optical filters,” Proc. IS&T 2016, 1–7 (2016).

Proc. R. Soc. Lond., B, Biol. Sci. (1)

S. Ullman, “The interpretation of structure from motion,” Proc. R. Soc. Lond., B, Biol. Sci. 203, 405–426 (1979).
[Crossref] [PubMed]

Proc. SPIE (6)

R. Bridgelall, J. B. Rafert, D. Atwood, and D. D. Tolliver, “Hyperspectral range imaging for transportation systems,” Proc. SPIE 9803, 98032Y (2016).
[Crossref]

B. Geelen, N. Tack, and A. Lambrechts, “A compact snapshot multispectral imager with a monolithically integrated per-pixel filter mosaic,” Proc. SPIE 8974, 89740L (2014).
[Crossref]

N. Tack, A. Lambrechts, P. Soussan, and L. Haspeslagh, “A compact, high-speed, and low-cost hyperspectral imager,” Proc. SPIE 8266, 82660Q (2012).
[Crossref]

C. Zhang, M. Rosenberger, A. Breitbarth, and G. Notni, “Wavelength dependency of optical 3D measurements at translucent objects using fringe pattern projection,” Proc. SPIE 10220, 1022007 (2017).
[Crossref]

S. Heist, P. Dietrich, M. Landmann, P. Kühmstedt, and G. Notni, “High-speed 3D shape measurement by GOBO projection of aperiodic sinusoidal fringes: a performance analysis,” Proc. SPIE 10667, 106670A (2018).

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[Crossref]

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J. Wu, B. Xiong, X. Lin, J. He, J. Suo, and Q. Dai, “Snapshot hyperspectral volumetric microscopy,” Sci. Rep. 6, 24624 (2016).
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R. Hartley and A. Zisserman, Multiple View Geometry in Computer Vision (Cambridge University, 2004).
[Crossref]

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Figures (10)

Fig. 1
Fig. 1 Operating principle of a hyperspectral snapshot camera. (a) Schematic representation of a hyperspectral, 5 × 5 tessellated snapshot sensor. (b) Optical path in the Fabry-Pérot interferometer.
Fig. 2
Fig. 2 (a) Illustration of a stereo camera system and its epipolar geometry. (b) Camera images of an aperiodic sinusoidal pattern projected onto a measurement object, making the detection of corresponding image points p 1 and p 2 possible.
Fig. 3
Fig. 3 Location of the principal point p 0 in the coordinate system of a spectral channel: for channel (0, 1) with its virtual pixels marked with orange lines, the principal point has the coordinates p 0 ( 0 , 1 ) = [ ( x 0 , y 0 ) ( 0 , 1 ) ] / 5. In general, it is p 0 ( i , j ) = [ ( x 0 , y 0 ) ( 0 , 1 ) ] / 5.
Fig. 4
Fig. 4 Measurement setup. (a) Photograph of the developed 5D sensor comprising two hyperspectral snapshot cameras, a GOBO projector illuminating the measurement object with varying aperiodic sinusoidal patterns, and a projector homogeneously illuminating the scene. (b) GOBO wheel consisting of a borosilicate glass plate with a chromium coating from which aperiodic strips have been etched.
Fig. 5
Fig. 5 Spectral properties of one of the applied hyperspectral snapshot cameras: combined quantum efficiency Qi of the 5 × 5 different channels and combined transmittance Tfilter of the band-pass/edge filter in front of the sensor in the operation mode (OM1), i.e., with a spectral response between 600 and 875 nm.
Fig. 6
Fig. 6 Operation modes of the 5D sensor. Depending on the filters mounted in front of the objective lenses of the hyperspectral cameras (HSC1 and HSC2), the projector for homogeneous illumination (HI), and the GOBO projector for aperiodic sinusoidal patterns (ASP), the sensor can be operated in four different modes.
Fig. 7
Fig. 7 Hyperspectral 3D measurement of a historical globe. (a) Photograph of the globe with marked measurement area. (b) 3D surface model with artificial blue shading. (c) 3D surface model with mapped intensities from selected spectral channels, colored according to their wavelength.
Fig. 8
Fig. 8 Hyperspectral 3D measurement of a human hand. 3D surface model without (left) and with mapped intensities from selected channels in the (a) 600-875-nm and (b) 675-975-nm camera configuration.
Fig. 9
Fig. 9 Water absorption by a citrus plant. (a) Color images of the plant after supplying water. (b) 3D surface models. (c) Reflectance spectrum.
Fig. 10
Fig. 10 Measurement of an opaque and a translucent sphere. (a) Exemplary camera images during the measurement in the 750-nm channel. (b) Illustration of the measured points’ deviation from the real surface when measuring a translucent sphere. (c) Results obtained using our hyperspectral 3D sensor. Error bars denote the standard deviation of the results of the measurement which was repeated ten times.

Equations (15)

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p k = [ x k , y k I k ( λ 1 , , λ n ) ]
p k = [ x k , y k , z k , I k ( λ 1 , , λ n ) ] .
p k 5 D = [ x k , y k , z k , t , I k ( λ 1 , , λ n ) ] .
T = ( 1 R 1 ) ( 1 R 2 ) ( 1 R 1 R 2 ) 2 + 4 R 1 R 2 sin 2 Δ φ 2
with Δ φ = 4 π n d cos ϑ λ and n sin ϑ = sin ϑ 0
λ k = 2 n d cos ϑ k with k = 1 , 2 , 3 , .
g i = K t exp = : K 0 R obj ( λ ) E e ( λ ) T lens ( λ ) T filter ( λ ) Q i ( λ ) = : F i ( λ ) d λ with i = 1 , , n
g i = K j = 1 n λ j a λ j b R obj ( λ ) F i ( λ ) d λ .
g i = K j = 1 n R obj , j λ j a λ j b F i ( λ ) d λ .
R obj = R obj R dark R spec R dark .
I k proj ( x , y ) = a k ( x ) + b k ( x ) sin [ c k ( x ) x + d k ( x ) ] with k = 1 , , N
ρ = k = 1 N [ g k ( 1 ) g ( 1 ) ¯ ] [ g k ( 2 ) g ( 2 ) ¯ ] k = 1 N [ g k ( 1 ) g ( 1 ) ¯ ] 2 k = 1 N [ g k ( 2 ) g ( 2 ) ¯ ] 2
g ( 1 ) ¯ = 1 N k = 1 N g k ( 1 ) and g ( 2 ) ¯ = 1 N k = 1 N g k ( 2 ) .
R ( i , j ) = [ R full ( i , j ) ] / 5 .
Q ( x 1 y disp 1 ) with Q = [ 1 0 0 c x 1 0 1 0 c y 1 0 0 0 κ 0 0 1 / l ( c x 1 c x 2 ) / l ] .

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