Abstract

Hyperspectral imaging collects knowledge about the spectral content enclosed in a given target. For such investigations, fundamental requirements include the ability to extend the spectral range, improve the spectral resolution, and achieve a large field of view together with compactness and robustness. Here we introduce a new method of polarized hyperspectral imaging that makes use of two cascaded liquid crystal cells that we demonstrate to act as a Fourier spectrometer when appropriately driven with a dynamic voltage step. One thick cell (200 μm), electrically addressed, provides a tunable path delay between two polarization directions while a thin static cell is used as a temporal offset. Prior to the imaging, an accurate calibration of the system is performed by broadband spectral interferometry with femtosecond pulses. The calibration procedure allows determining the path delay between the extraordinary and ordinary waves with subfemtosecond accuracy. Thanks to this implementation, 130  cm1 (6 nm) spectral resolution is demonstrated over a 400–1000 nm spectral range. Furthermore, the device has no moving parts, is compact, integrable, and low cost compared to traditional imaging systems relying on Fourier spectrometry. Scalability in size and spectral range can also be considered. Examples of hyperspectral imaging are demonstrated with three representative samples permitting the evaluation of the potential of the technique in terms of its spectral performances, compactness, and robustness.

© 2017 Optical Society of America

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References

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M. Huang, C. He, Q. Zhu, and J. Qin, “Maize seed variety classification using the integration of spectral and image features combined with feature transformation based on hyperspectral imaging,” Appl. Sci. 6, 183 (2016).
[Crossref]

L. Snijders, T. Zaman, and D. Howell, “Using hyperspectral imaging to reveal a hidden precolonial Mesoamerican codex,” J. Archaeol. Sci. 9, 143–149 (2016).
[Crossref]

H.-T. Lim and V. M. Muruskeshan, “Spatial-scanning hyperspectral imaging probe for bio-imaging applications,” Rev. Sci. Inst. 87, 033707 (2016).
[Crossref]

I. August, Y. Oiknine, M. AbuLeil, and A. Stern, “Miniature compressive ultra-spectral imaging system utilizing a single liquid crystal phase retarder,” Sci. Rep. 6, 23524 (2016).
[Crossref]

C. Goenka, J. Semeter, J. Noto, J. Baumgardner, J. Riccobono, M. Migliozzi, H. Dahlgren, R. Marshall, S. Kapali, M. Hirsch, D. Hampton, and H. Akbari, “Multichannel tunable imager architecture for hyperspectral imaging in relevant spectral domains,” Appl. Opt. 55, 3149–3157 (2016).
[Crossref]

M. Abuleil and I. Abdulhalim, “Narrowband multispectral liquid crystal tunable filter,” Opt. Lett. 41, 1957–1960 (2016).
[Crossref]

P. Wang and Z. Zhang, “Double-filtering method based on two acousto-optic tunable filters for hyperspectral imaging application,” Opt. Express 24, 9888–9895 (2016).
[Crossref]

A. Jullien, U. Bortolozzo, S. Grabielle, J.-P. Huignard, N. Forget, and S. Residori, “Continuously tunable femtosecond delay-line based on liquid crystal cells,” Opt. Express 24, 14483–14493 (2016).
[Crossref]

2015 (1)

2014 (1)

2011 (1)

2007 (1)

G. A. Blackburn, “Hyperspectral remote sensing of plant pigments,” J. Exp. Bot. 58, 855–867 (2007).
[Crossref]

2005 (1)

R. G. Sellar and G. D. Boreman, “Classification of imaging spectrometers for remote sensing applications,” Opt. Eng. 44, 013602 (2005).
[Crossref]

2004 (1)

2003 (1)

M. Babin, D. Stramski, G. M. Ferrari, H. Claustre, A. Bricaud, G. Obolensky, and N. Hoepffner, “Variations of the light absorption coefficients of phytoplankton, non algal particles and dissolved organic matter in coastal waters around Europe,” J. Geophys. Res. 108, 3211 (2003).
[Crossref]

2002 (2)

T. Kuki, H. Fujikake, T. Nomoto, and Y. Utsumi, “Design of a microwave variable delay line using liquid crystal, and a study of its insertion loss,” Electron. Commun. Jpn. 85, 90–96 (2002).

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]

1995 (2)

1990 (1)

1984 (1)

Abdulhalim, I.

Abuleil, M.

M. Abuleil and I. Abdulhalim, “Narrowband multispectral liquid crystal tunable filter,” Opt. Lett. 41, 1957–1960 (2016).
[Crossref]

I. August, Y. Oiknine, M. AbuLeil, and A. Stern, “Miniature compressive ultra-spectral imaging system utilizing a single liquid crystal phase retarder,” Sci. Rep. 6, 23524 (2016).
[Crossref]

Akbari, H.

August, I.

I. August, Y. Oiknine, M. AbuLeil, and A. Stern, “Miniature compressive ultra-spectral imaging system utilizing a single liquid crystal phase retarder,” Sci. Rep. 6, 23524 (2016).
[Crossref]

Babin, M.

M. Babin, D. Stramski, G. M. Ferrari, H. Claustre, A. Bricaud, G. Obolensky, and N. Hoepffner, “Variations of the light absorption coefficients of phytoplankton, non algal particles and dissolved organic matter in coastal waters around Europe,” J. Geophys. Res. 108, 3211 (2003).
[Crossref]

Barta, C.

R. Maksimenka, N. Forget, D. Kaplan, R. Hasal, C. Barta, J. Jaeck, and R. Haidar, “High spectral resolution AOTF-based hyperspectral imaging system for thermal infrared,” in Proceedings of the 4S Symposium (ESA, 2014).

Baumgardner, J.

Ben-Dor, E.

E. Ben-Dor, T. Malthus, A. Plaza, and D. Schlapfer, Airborne Measurements for Environmental Research: Methods and Instruments (Wiley, 2013).

Bissett, W. P.

Blackburn, G. A.

G. A. Blackburn, “Hyperspectral remote sensing of plant pigments,” J. Exp. Bot. 58, 855–867 (2007).
[Crossref]

Boreman, G. D.

R. G. Sellar and G. D. Boreman, “Classification of imaging spectrometers for remote sensing applications,” Opt. Eng. 44, 013602 (2005).
[Crossref]

Bortolozzo, U.

Bowles, J.

Bricaud, A.

M. Babin, D. Stramski, G. M. Ferrari, H. Claustre, A. Bricaud, G. Obolensky, and N. Hoepffner, “Variations of the light absorption coefficients of phytoplankton, non algal particles and dissolved organic matter in coastal waters around Europe,” J. Geophys. Res. 108, 3211 (2003).
[Crossref]

Chavel, P.

Chen, P.-H.

Chen, W.

Chériaux, G.

Claustre, H.

M. Babin, D. Stramski, G. M. Ferrari, H. Claustre, A. Bricaud, G. Obolensky, and N. Hoepffner, “Variations of the light absorption coefficients of phytoplankton, non algal particles and dissolved organic matter in coastal waters around Europe,” J. Geophys. Res. 108, 3211 (2003).
[Crossref]

Coudrain, C.

Dahlgren, H.

Davis, C. O.

de Haseth, J. A.

P. R. Griffiths and J. A. de Haseth, Fourier Transform Infrared Spectrometry (Wiley, 2007).

Deschamps, J.

Downes, T. V.

Efron, U.

Ferrari, G. M.

M. Babin, D. Stramski, G. M. Ferrari, H. Claustre, A. Bricaud, G. Obolensky, and N. Hoepffner, “Variations of the light absorption coefficients of phytoplankton, non algal particles and dissolved organic matter in coastal waters around Europe,” J. Geophys. Res. 108, 3211 (2003).
[Crossref]

Ferrec, Y.

Fisher, J.

Fletcher-Holmes, D. W.

Forget, N.

A. Jullien, U. Bortolozzo, S. Grabielle, J.-P. Huignard, N. Forget, and S. Residori, “Continuously tunable femtosecond delay-line based on liquid crystal cells,” Opt. Express 24, 14483–14493 (2016).
[Crossref]

R. Maksimenka, N. Forget, D. Kaplan, R. Hasal, C. Barta, J. Jaeck, and R. Haidar, “High spectral resolution AOTF-based hyperspectral imaging system for thermal infrared,” in Proceedings of the 4S Symposium (ESA, 2014).

Fournet, P.

Fujikake, H.

T. Kuki, H. Fujikake, T. Nomoto, and Y. Utsumi, “Design of a microwave variable delay line using liquid crystal, and a study of its insertion loss,” Electron. Commun. Jpn. 85, 90–96 (2002).

Goenka, C.

Grabielle, S.

Griffiths, P. R.

P. R. Griffiths and J. A. de Haseth, Fourier Transform Infrared Spectrometry (Wiley, 2007).

Haidar, R.

R. Maksimenka, N. Forget, D. Kaplan, R. Hasal, C. Barta, J. Jaeck, and R. Haidar, “High spectral resolution AOTF-based hyperspectral imaging system for thermal infrared,” in Proceedings of the 4S Symposium (ESA, 2014).

Hampton, D.

Harvey, A. R.

Hasal, R.

R. Maksimenka, N. Forget, D. Kaplan, R. Hasal, C. Barta, J. Jaeck, and R. Haidar, “High spectral resolution AOTF-based hyperspectral imaging system for thermal infrared,” in Proceedings of the 4S Symposium (ESA, 2014).

He, C.

M. Huang, C. He, Q. Zhu, and J. Qin, “Maize seed variety classification using the integration of spectral and image features combined with feature transformation based on hyperspectral imaging,” Appl. Sci. 6, 183 (2016).
[Crossref]

Hegyi, A.

Hess, L. D.

Hirsch, M.

Hoepffner, N.

M. Babin, D. Stramski, G. M. Ferrari, H. Claustre, A. Bricaud, G. Obolensky, and N. Hoepffner, “Variations of the light absorption coefficients of phytoplankton, non algal particles and dissolved organic matter in coastal waters around Europe,” J. Geophys. Res. 108, 3211 (2003).
[Crossref]

Howell, D.

L. Snijders, T. Zaman, and D. Howell, “Using hyperspectral imaging to reveal a hidden precolonial Mesoamerican codex,” J. Archaeol. Sci. 9, 143–149 (2016).
[Crossref]

Huang, M.

M. Huang, C. He, Q. Zhu, and J. Qin, “Maize seed variety classification using the integration of spectral and image features combined with feature transformation based on hyperspectral imaging,” Appl. Sci. 6, 183 (2016).
[Crossref]

Huignard, J.-P.

Ichioka, Y.

Inoue, T.

Itoh, K.

Jaeck, J.

R. Maksimenka, N. Forget, D. Kaplan, R. Hasal, C. Barta, J. Jaeck, and R. Haidar, “High spectral resolution AOTF-based hyperspectral imaging system for thermal infrared,” in Proceedings of the 4S Symposium (ESA, 2014).

Joffre, M.

Jullien, A.

Kapali, S.

Kaplan, D.

R. Maksimenka, N. Forget, D. Kaplan, R. Hasal, C. Barta, J. Jaeck, and R. Haidar, “High spectral resolution AOTF-based hyperspectral imaging system for thermal infrared,” in Proceedings of the 4S Symposium (ESA, 2014).

Khoo, I.-C.

I.-C. Khoo, Liquid Crystals, Physical Properties and Nonlinear Optical Phenomena (Wiley, 1995).

Korwan, D.

Kuki, T.

T. Kuki, H. Fujikake, T. Nomoto, and Y. Utsumi, “Design of a microwave variable delay line using liquid crystal, and a study of its insertion loss,” Electron. Commun. Jpn. 85, 90–96 (2002).

Leathers, R. A.

Lepetit, L.

Lim, H.-T.

H.-T. Lim and V. M. Muruskeshan, “Spatial-scanning hyperspectral imaging probe for bio-imaging applications,” Rev. Sci. Inst. 87, 033707 (2016).
[Crossref]

Maksimenka, R.

R. Maksimenka, N. Forget, D. Kaplan, R. Hasal, C. Barta, J. Jaeck, and R. Haidar, “High spectral resolution AOTF-based hyperspectral imaging system for thermal infrared,” in Proceedings of the 4S Symposium (ESA, 2014).

Malthus, T.

E. Ben-Dor, T. Malthus, A. Plaza, and D. Schlapfer, Airborne Measurements for Environmental Research: Methods and Instruments (Wiley, 2013).

Marshall, R.

Martini, J.

Migliozzi, M.

Muruskeshan, V. M.

H.-T. Lim and V. M. Muruskeshan, “Spatial-scanning hyperspectral imaging probe for bio-imaging applications,” Rev. Sci. Inst. 87, 033707 (2016).
[Crossref]

Nomoto, T.

T. Kuki, H. Fujikake, T. Nomoto, and Y. Utsumi, “Design of a microwave variable delay line using liquid crystal, and a study of its insertion loss,” Electron. Commun. Jpn. 85, 90–96 (2002).

Noto, J.

Obolensky, G.

M. Babin, D. Stramski, G. M. Ferrari, H. Claustre, A. Bricaud, G. Obolensky, and N. Hoepffner, “Variations of the light absorption coefficients of phytoplankton, non algal particles and dissolved organic matter in coastal waters around Europe,” J. Geophys. Res. 108, 3211 (2003).
[Crossref]

Ohta, T.

Oiknine, Y.

I. August, Y. Oiknine, M. AbuLeil, and A. Stern, “Miniature compressive ultra-spectral imaging system utilizing a single liquid crystal phase retarder,” Sci. Rep. 6, 23524 (2016).
[Crossref]

Pan, C.-L.

Pan, R.-P.

Persky, M. J.

M. J. Persky, “A review of spaceborne infrared Fourier transform spectrometers for remote sensing,” Rev. Sci. Inst. 66, 4763–4797 (1995).
[Crossref]

Plaza, A.

E. Ben-Dor, T. Malthus, A. Plaza, and D. Schlapfer, Airborne Measurements for Environmental Research: Methods and Instruments (Wiley, 2013).

Primot, J.

Qin, J.

M. Huang, C. He, Q. Zhu, and J. Qin, “Maize seed variety classification using the integration of spectral and image features combined with feature transformation based on hyperspectral imaging,” Appl. Sci. 6, 183 (2016).
[Crossref]

Reisse, R. A.

Residori, S.

Rhea, W. J.

Riccobono, J.

Sauer, H.

Schlapfer, D.

E. Ben-Dor, T. Malthus, A. Plaza, and D. Schlapfer, Airborne Measurements for Environmental Research: Methods and Instruments (Wiley, 2013).

Sellar, R. G.

R. G. Sellar and G. D. Boreman, “Classification of imaging spectrometers for remote sensing applications,” Opt. Eng. 44, 013602 (2005).
[Crossref]

Semeter, J.

Snijders, L.

L. Snijders, T. Zaman, and D. Howell, “Using hyperspectral imaging to reveal a hidden precolonial Mesoamerican codex,” J. Archaeol. Sci. 9, 143–149 (2016).
[Crossref]

Snyder, W. A.

Stern, A.

I. August, Y. Oiknine, M. AbuLeil, and A. Stern, “Miniature compressive ultra-spectral imaging system utilizing a single liquid crystal phase retarder,” Sci. Rep. 6, 23524 (2016).
[Crossref]

Stramski, D.

M. Babin, D. Stramski, G. M. Ferrari, H. Claustre, A. Bricaud, G. Obolensky, and N. Hoepffner, “Variations of the light absorption coefficients of phytoplankton, non algal particles and dissolved organic matter in coastal waters around Europe,” J. Geophys. Res. 108, 3211 (2003).
[Crossref]

Taboury, J.

Tang, T.-T.

Utsumi, Y.

T. Kuki, H. Fujikake, T. Nomoto, and Y. Utsumi, “Design of a microwave variable delay line using liquid crystal, and a study of its insertion loss,” Electron. Commun. Jpn. 85, 90–96 (2002).

Wang, P.

Wu, S.-T.

Yang, C.-S.

Yang, D.-K.

D.-K. Yang and S.-T. Wu, Fundamentals of Liquid Crystal Devices (Wiley, 2012).

Yu, P.

Zaman, T.

L. Snijders, T. Zaman, and D. Howell, “Using hyperspectral imaging to reveal a hidden precolonial Mesoamerican codex,” J. Archaeol. Sci. 9, 143–149 (2016).
[Crossref]

Zhang, Z.

Zhu, Q.

M. Huang, C. He, Q. Zhu, and J. Qin, “Maize seed variety classification using the integration of spectral and image features combined with feature transformation based on hyperspectral imaging,” Appl. Sci. 6, 183 (2016).
[Crossref]

Appl. Opt. (3)

Appl. Sci. (1)

M. Huang, C. He, Q. Zhu, and J. Qin, “Maize seed variety classification using the integration of spectral and image features combined with feature transformation based on hyperspectral imaging,” Appl. Sci. 6, 183 (2016).
[Crossref]

Electron. Commun. Jpn. (1)

T. Kuki, H. Fujikake, T. Nomoto, and Y. Utsumi, “Design of a microwave variable delay line using liquid crystal, and a study of its insertion loss,” Electron. Commun. Jpn. 85, 90–96 (2002).

J. Archaeol. Sci. (1)

L. Snijders, T. Zaman, and D. Howell, “Using hyperspectral imaging to reveal a hidden precolonial Mesoamerican codex,” J. Archaeol. Sci. 9, 143–149 (2016).
[Crossref]

J. Exp. Bot. (1)

G. A. Blackburn, “Hyperspectral remote sensing of plant pigments,” J. Exp. Bot. 58, 855–867 (2007).
[Crossref]

J. Geophys. Res. (1)

M. Babin, D. Stramski, G. M. Ferrari, H. Claustre, A. Bricaud, G. Obolensky, and N. Hoepffner, “Variations of the light absorption coefficients of phytoplankton, non algal particles and dissolved organic matter in coastal waters around Europe,” J. Geophys. Res. 108, 3211 (2003).
[Crossref]

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

Opt. Eng. (1)

R. G. Sellar and G. D. Boreman, “Classification of imaging spectrometers for remote sensing applications,” Opt. Eng. 44, 013602 (2005).
[Crossref]

Opt. Express (5)

Opt. Lett. (3)

Rev. Sci. Inst. (2)

M. J. Persky, “A review of spaceborne infrared Fourier transform spectrometers for remote sensing,” Rev. Sci. Inst. 66, 4763–4797 (1995).
[Crossref]

H.-T. Lim and V. M. Muruskeshan, “Spatial-scanning hyperspectral imaging probe for bio-imaging applications,” Rev. Sci. Inst. 87, 033707 (2016).
[Crossref]

Sci. Rep. (1)

I. August, Y. Oiknine, M. AbuLeil, and A. Stern, “Miniature compressive ultra-spectral imaging system utilizing a single liquid crystal phase retarder,” Sci. Rep. 6, 23524 (2016).
[Crossref]

Other (5)

R. Maksimenka, N. Forget, D. Kaplan, R. Hasal, C. Barta, J. Jaeck, and R. Haidar, “High spectral resolution AOTF-based hyperspectral imaging system for thermal infrared,” in Proceedings of the 4S Symposium (ESA, 2014).

E. Ben-Dor, T. Malthus, A. Plaza, and D. Schlapfer, Airborne Measurements for Environmental Research: Methods and Instruments (Wiley, 2013).

P. R. Griffiths and J. A. de Haseth, Fourier Transform Infrared Spectrometry (Wiley, 2007).

D.-K. Yang and S.-T. Wu, Fundamentals of Liquid Crystal Devices (Wiley, 2012).

I.-C. Khoo, Liquid Crystals, Physical Properties and Nonlinear Optical Phenomena (Wiley, 1995).

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Figures (8)

Fig. 1.
Fig. 1. Basic principle of the proposed LC-based Fourier spectrometer.
Fig. 2.
Fig. 2. Experimental setup: (a) the FTHSI measurement configuration and (b) the calibration procedure. In the inset are shown the bias voltage step Vb(t) applied to the thick cell together with the corresponding change of the LC average director tilt θ (solid line) and average extraordinary refractive index ne (dashed line). ne(t) depends on θ(t) according to Eq. [1] and θ(t) is related to Vbmax. In the experiment, Vbmax=10  V. In (b) a flip mirror is used to seed a femtosecond laser pulse train in the beam path instead of the white lamp.
Fig. 3.
Fig. 3. Calibration of the FTHSI delay line. The bias voltage of 10 V is shut down at t=0. (a) The interference spectrum recorded regularly (every 8 ms) as a function of time. (b) The retrieved group delay between the two polarization states as a function of acquisition time.
Fig. 4.
Fig. 4. Interferogram measurement and analysis. The bias voltage of 10 V is shut down at t=0. (a) The one-sided interferogram measured for one pixel of the camera as a function of time over the full acquisition span. The inset is a zoom of the ten first seconds of acquisition. (b) The reconstructed interferogram as a function of the retardation time between the two polarization components of the incident light. The baseline is indicated (dashed).
Fig. 5.
Fig. 5. (a) Retrieved spectral resolution as a function of the wavelength. (b) The retrieved spectrum of the calibration lamp without (higher blue curve) and with (lower red curve) a bandpass filter. The hatched area indicates the detected spectral bandwidth. The spectral cutoff λmin is also indicated.
Fig. 6.
Fig. 6. FTHSI of a beam splitter pellicle BP145B1 from Thorlabs. (a) The hyperspectral data cube. (b) Bottom: the reconstructed spectrum. Top: the background spectrum is subtracted and the retrieved spectral transmittance of the pellicle [red, from the ZOI indicated in (a)] is compared to the data provided by the furnisher (green).
Fig. 7.
Fig. 7. FTHSI of a giant chromosome. (a) The hyperspectral data cube. (b) The spectral transmission extracted from chosen parts of the picture. The spectra are normalized with respect to the reference and the color of the lines refers to the color of the ZOI in (a). (c) From the data cube, monochromatic views of the sample can be reconstructed.
Fig. 8.
Fig. 8. FTHSI of a mixture of olive oil and water. (a) An image of the sample. The white line limits the analyzed area. (b) The transmitted spectra. The color line refers to the color of the ZOI in (c). (c) A monochromatic image (650 nm) of the selected area.

Equations (3)

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ne(θ)=nonecos2θno2+sin2θne2,
I(ω,τ)=|E0(ω)(1+exp(iωτ))|2=[I0(ω)(1+cos(Δϕ(ω)+ωτ)],
I(τ)=12[E(t)2dt+E(t)E(tτ)dt].

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