Abstract

A microelectromechanical systems (MEMS) based self-referencing cascaded line-scan camera using single-pixel detectors is proposed and verified. Single-pixel detectors make it an attractive low-cost alternative of a traditional line-scan camera that can operate at any wavelength. The proposed system is composed of several identical cascaded line imager units driven by a common actuator. Each unit is an integration of an imaging slit, a MEMS encoding mask, a light concentrator and a single-pixel detector. The spatial resolution of the proposed line-scan camera can thus be N-fold immediately by cascading N units to achieve high spatial resolution. For prototype demonstration, a cascaded line-scan camera composed of two imager units are prepared, with each unit having a single-pixel detector and being capable of resolving 71 spatial pixels along the slit. Hadamard transform multiplexing detection is applied to enhance the camera’s signal-to-noise ratio (SNR). The MEMS encoding mask is resonantly driven at 250 Hz indicating an ideal frame-rate of 500 fps of the line-scan camera prototype. Further increase of frame-rate can be achieved through optimization of the MEMS actuator. Additionally, the MEMS encoding mask incorporates a self-referencing design which simplifies data acquisition process, thus enabling the camera system to work in a simple but efficient open-loop condition.

© 2019 Optical Society of America under the terms of the OSA Open Access Publishing Agreement

Full Article  |  PDF Article
OSA Recommended Articles
Fast time-lens-based line-scan single-pixel camera with multi-wavelength source

Qiang Guo, Hongwei Chen, Zhiliang Weng, Minghua Chen, Sigang Yang, and Shizhong Xie
Biomed. Opt. Express 6(9) 3610-3617 (2015)

Real-time imaging of methane gas leaks using a single-pixel camera

Graham M. Gibson, Baoqing Sun, Matthew P. Edgar, David B. Phillips, Nils Hempler, Gareth T. Maker, Graeme P. A. Malcolm, and Miles J. Padgett
Opt. Express 25(4) 2998-3005 (2017)

Design and characterization of a 256x64-pixel single-photon imager in CMOS for a MEMS-based laser scanning time-of-flight sensor

Cristiano Niclass, Kota Ito, Mineki Soga, Hiroyuki Matsubara, Isao Aoyagi, Satoru Kato, and Manabu Kagami
Opt. Express 20(11) 11863-11881 (2012)

References

  • View by:
  • |
  • |
  • |

  1. A. Kho and V. J. Srinivasan, “Compensating spatially dependent dispersion in visible light OCT,” Opt. Lett. 44(4), 775–778 (2019).
    [Crossref]
  2. G. Polder, P. M. Blok, H. A. C. De Villiers, J. M. Van Der Wolf, and J. Kamp, “Potato Virus Y Detection in Seed Potatoes Using Deep Learning on Hyperspectral Images,” Front. Plant Sci. 10, 209 (2019).
    [Crossref]
  3. J. Jiang, X. Feng, F. Liu, Y. Xu, and H. Huang, “Multi-Spectral RGB-NIR Image Classification Using Double-Channel CNN,” IEEE Access 7, 20607–20613 (2019).
    [Crossref]
  4. J. Qin, M. S. Kim, K. Chao, L. Bellato, W. F. Schmidt, B.-K. Cho, and M. Huang, “Inspection of maleic anhydride in starch powder using line-scan hyperspectral Raman chemical imaging technique,” Int. J. Agric. Biol. Eng. 11(6), 120–125 (2018).
    [Crossref]
  5. J. Qin, M. S. Kim, K. Chao, M. Gonzalez, and B.-K. Cho, “Quantitative detection of benzoyl peroxide in wheat flour using line-scan macroscale Raman chemical imaging,” Appl. Spectrosc. 71(11), 2469–2476 (2017).
    [Crossref]
  6. J. Qin, M. S. Kim, K. Chao, S. Dhakal, H. Lee, B.-K. Cho, and C. Mo, “Detection and quantification of adulterants in milk powder using a high-throughput Raman chemical imaging technique,” Food Addit. Contam., Part A 34(2), 152–161 (2017).
    [Crossref]
  7. B. Sun, J. Zhu, L. Yang, Y. Guo, and J. Lin, “Stereo line-scan sensor calibration for 3D shape measurement,” Appl. Opt. 56(28), 7905–7914 (2017).
    [Crossref]
  8. E. Lilienblum and A. Al-Hamadi, “A structured light approach for 3-D surface reconstruction with a stereo line-scan system,” IEEE Trans. Instrum. Meas. 64(5), 1258–1266 (2015).
    [Crossref]
  9. Z. Liu, S. Wu, Q. Wu, C. Quan, and Y. Ren, “A novel stereo vision measurement system using both line scan camera and frame camera,” IEEE Trans. Instrum. Meas. (to be published) (2018).
  10. A. Davis, O. Levecq, H. Azimani, D. Siret, and A. Dubois, “Simultaneous dual-band line-field confocal optical coherence tomography: application to skin imaging,” Biomed. Opt. Express 10(2), 694–706 (2019).
    [Crossref]
  11. A. Dubois, O. Levecq, H. Azimani, A. Davis, J. Ogien, D. Siret, and A. Barut, “Line-field confocal time-domain optical coherence tomography with dynamic focusing,” Opt. Express 26(26), 33534–33542 (2018).
    [Crossref]
  12. A. Dubois, O. Levecq, H. Azimani, D. Siret, A. Barut, M. Suppa, V. del Marmol, J. Malvehy, E. Cinotti, P. Rubegni, and J. Perrot, “Line-field confocal optical coherence tomography for high-resolution noninvasive imaging of skin tumors,” J. Biomed. Opt. 23(10), 1 (2018).
    [Crossref]
  13. N. Radwell, K. J. Mitchell, G. M. Gibson, M. P. Edgar, R. Bowman, and M. J. Padgett, “Single-pixel infrared and visible microscope,” Optica 1(5), 285–289 (2014).
    [Crossref]
  14. M. P. Edgar, G. M. Gibson, R. W. Bowman, B. Sun, N. Radwell, K. J. Mitchell, S. S. Welsh, and J. Padgett, “Simultaneous real-time visible and infrared video with single-pixel detectors,” Sci. Rep. 5(1), 10669 (2015).
    [Crossref]
  15. Z. Xu, W. Chen, J. Penuelas, M. Padgett, and M. Sun, “1000 fps computational ghost imaging using LED-based structured illumination,” Opt. Express 26(3), 2427–2434 (2018).
    [Crossref]
  16. M. Sun and J. Zhang, “Single-pixel imaging and its application in three-dimensional reconstruction: a brief review,” Sensors 19(3), 732 (2019).
    [Crossref]
  17. M. Sun, W. Chen, T. Liu, and L. Li, “Image retrieval in spatial and temporal domains with a quadrant detector,” IEEE Photonics J. 9(5), 1–6 (2017).
    [Crossref]
  18. E. Aguénounon, F. Dadouche, W. Uhring, N. Ducros, and S. Gioux, “Single snapshot imaging of optical properties using a single-pixel camera: a simulation study,” J. Biomed. Opt. 24(7), 071612 (2019).
    [Crossref]
  19. S. Jiao, M. Sun, Y. Gao, T. Lei, Z. Xie, and X. Yuan, “Motion estimation and quality enhancement for a single image in dynamic single-pixel imaging,” Opt. Express 27(9), 12841–12854 (2019).
    [Crossref]
  20. D. Shi, J. Huang, W. Meng, K. Yin, B. Sun, Y. Wang, K. Yuan, C. Xie, D. Liu, and W. Zhu, “Radon single-pixel imaging with projective sampling,” Opt. Express 27(10), 14594–14609 (2019).
    [Crossref]
  21. L. Liao, K. Li, C. Yang, and J. Liu, “Low-cost image compressive sensing with multiple measurement rates for object detection,” Sensors 19(9), 2079 (2019).
    [Crossref]
  22. M. F. Duarte, M. A. Davenport, D. Takhar, J. N. Laska, T. Sun, K. F. Kelly, and R. G. Baraniuk, “Single-pixel imaging via compressive sampling,” IEEE Signal Process. Mag. 25(2), 83–91 (2008).
    [Crossref]
  23. R. J. Bell, Introductory Fourier Transform Spectroscopy (Academic, 1972).
  24. M. Harwit, Hadamard Transform Optics (Elsevier, The Netherlands, 1979).
  25. Z. Zhang, X. Wang, G. Zheng, and J. Zhong, “Hadamard single-pixel imaging versus Fourier single-pixel imaging,” Opt. Express 25(16), 19619–19639 (2017).
    [Crossref]
  26. L. J. Hornbeck, “Digital Light ProcessingTM for high-brightness, high-resolution applications,” Proc. SPIE 3013, 27–40 (1997).
    [Crossref]
  27. A. M. Elshurafa, K. Khirallah, H. H. Tawfik, A. Emira, A. K. S. A. Aziz, and S. M. Sedky, “Nonlinear dynamics of spring softening and hardening in folded-MEMS comb drive resonators,” J. Microelectromech. Syst. 20(4), 943–958 (2011).
    [Crossref]
  28. W. T. Welford and R. Winston, High Collection Nonimaging Optics (Academic, 1989).
  29. R. Levi-Setti, D. A. Park, and R. Winston, “The corneal cones of Limulus as optimised light concentrators,” Nature 253(5487), 115–116 (1975).
    [Crossref]
  30. R. Winston and J. M. Enoch, “Retinal cone receptor as an ideal light collectort,” J. Opt. Soc. Am. 61(8), 1120–1121 (1971).
    [Crossref]
  31. L. Li, B. Wang, J. Pottas, and W. Lipiński, “Design of a compound parabolic concentrator for a multi-source high-flux solar simulator,” Sol. Energy 183, 805–811 (2019).
    [Crossref]
  32. P. Mouroulis, R. O. Green, and T. G. Chrien, “Design of pushbroom imaging spectrometers for optimum recovery of spectroscopic and spatial information,” Appl. Opt. 39(13), 2210–2220 (2000).
    [Crossref]

2019 (10)

G. Polder, P. M. Blok, H. A. C. De Villiers, J. M. Van Der Wolf, and J. Kamp, “Potato Virus Y Detection in Seed Potatoes Using Deep Learning on Hyperspectral Images,” Front. Plant Sci. 10, 209 (2019).
[Crossref]

J. Jiang, X. Feng, F. Liu, Y. Xu, and H. Huang, “Multi-Spectral RGB-NIR Image Classification Using Double-Channel CNN,” IEEE Access 7, 20607–20613 (2019).
[Crossref]

M. Sun and J. Zhang, “Single-pixel imaging and its application in three-dimensional reconstruction: a brief review,” Sensors 19(3), 732 (2019).
[Crossref]

E. Aguénounon, F. Dadouche, W. Uhring, N. Ducros, and S. Gioux, “Single snapshot imaging of optical properties using a single-pixel camera: a simulation study,” J. Biomed. Opt. 24(7), 071612 (2019).
[Crossref]

L. Liao, K. Li, C. Yang, and J. Liu, “Low-cost image compressive sensing with multiple measurement rates for object detection,” Sensors 19(9), 2079 (2019).
[Crossref]

L. Li, B. Wang, J. Pottas, and W. Lipiński, “Design of a compound parabolic concentrator for a multi-source high-flux solar simulator,” Sol. Energy 183, 805–811 (2019).
[Crossref]

A. Davis, O. Levecq, H. Azimani, D. Siret, and A. Dubois, “Simultaneous dual-band line-field confocal optical coherence tomography: application to skin imaging,” Biomed. Opt. Express 10(2), 694–706 (2019).
[Crossref]

A. Kho and V. J. Srinivasan, “Compensating spatially dependent dispersion in visible light OCT,” Opt. Lett. 44(4), 775–778 (2019).
[Crossref]

S. Jiao, M. Sun, Y. Gao, T. Lei, Z. Xie, and X. Yuan, “Motion estimation and quality enhancement for a single image in dynamic single-pixel imaging,” Opt. Express 27(9), 12841–12854 (2019).
[Crossref]

D. Shi, J. Huang, W. Meng, K. Yin, B. Sun, Y. Wang, K. Yuan, C. Xie, D. Liu, and W. Zhu, “Radon single-pixel imaging with projective sampling,” Opt. Express 27(10), 14594–14609 (2019).
[Crossref]

2018 (4)

Z. Xu, W. Chen, J. Penuelas, M. Padgett, and M. Sun, “1000 fps computational ghost imaging using LED-based structured illumination,” Opt. Express 26(3), 2427–2434 (2018).
[Crossref]

A. Dubois, O. Levecq, H. Azimani, A. Davis, J. Ogien, D. Siret, and A. Barut, “Line-field confocal time-domain optical coherence tomography with dynamic focusing,” Opt. Express 26(26), 33534–33542 (2018).
[Crossref]

A. Dubois, O. Levecq, H. Azimani, D. Siret, A. Barut, M. Suppa, V. del Marmol, J. Malvehy, E. Cinotti, P. Rubegni, and J. Perrot, “Line-field confocal optical coherence tomography for high-resolution noninvasive imaging of skin tumors,” J. Biomed. Opt. 23(10), 1 (2018).
[Crossref]

J. Qin, M. S. Kim, K. Chao, L. Bellato, W. F. Schmidt, B.-K. Cho, and M. Huang, “Inspection of maleic anhydride in starch powder using line-scan hyperspectral Raman chemical imaging technique,” Int. J. Agric. Biol. Eng. 11(6), 120–125 (2018).
[Crossref]

2017 (5)

J. Qin, M. S. Kim, K. Chao, S. Dhakal, H. Lee, B.-K. Cho, and C. Mo, “Detection and quantification of adulterants in milk powder using a high-throughput Raman chemical imaging technique,” Food Addit. Contam., Part A 34(2), 152–161 (2017).
[Crossref]

M. Sun, W. Chen, T. Liu, and L. Li, “Image retrieval in spatial and temporal domains with a quadrant detector,” IEEE Photonics J. 9(5), 1–6 (2017).
[Crossref]

Z. Zhang, X. Wang, G. Zheng, and J. Zhong, “Hadamard single-pixel imaging versus Fourier single-pixel imaging,” Opt. Express 25(16), 19619–19639 (2017).
[Crossref]

B. Sun, J. Zhu, L. Yang, Y. Guo, and J. Lin, “Stereo line-scan sensor calibration for 3D shape measurement,” Appl. Opt. 56(28), 7905–7914 (2017).
[Crossref]

J. Qin, M. S. Kim, K. Chao, M. Gonzalez, and B.-K. Cho, “Quantitative detection of benzoyl peroxide in wheat flour using line-scan macroscale Raman chemical imaging,” Appl. Spectrosc. 71(11), 2469–2476 (2017).
[Crossref]

2015 (2)

M. P. Edgar, G. M. Gibson, R. W. Bowman, B. Sun, N. Radwell, K. J. Mitchell, S. S. Welsh, and J. Padgett, “Simultaneous real-time visible and infrared video with single-pixel detectors,” Sci. Rep. 5(1), 10669 (2015).
[Crossref]

E. Lilienblum and A. Al-Hamadi, “A structured light approach for 3-D surface reconstruction with a stereo line-scan system,” IEEE Trans. Instrum. Meas. 64(5), 1258–1266 (2015).
[Crossref]

2014 (1)

2011 (1)

A. M. Elshurafa, K. Khirallah, H. H. Tawfik, A. Emira, A. K. S. A. Aziz, and S. M. Sedky, “Nonlinear dynamics of spring softening and hardening in folded-MEMS comb drive resonators,” J. Microelectromech. Syst. 20(4), 943–958 (2011).
[Crossref]

2008 (1)

M. F. Duarte, M. A. Davenport, D. Takhar, J. N. Laska, T. Sun, K. F. Kelly, and R. G. Baraniuk, “Single-pixel imaging via compressive sampling,” IEEE Signal Process. Mag. 25(2), 83–91 (2008).
[Crossref]

2000 (1)

1997 (1)

L. J. Hornbeck, “Digital Light ProcessingTM for high-brightness, high-resolution applications,” Proc. SPIE 3013, 27–40 (1997).
[Crossref]

1975 (1)

R. Levi-Setti, D. A. Park, and R. Winston, “The corneal cones of Limulus as optimised light concentrators,” Nature 253(5487), 115–116 (1975).
[Crossref]

1971 (1)

Aguénounon, E.

E. Aguénounon, F. Dadouche, W. Uhring, N. Ducros, and S. Gioux, “Single snapshot imaging of optical properties using a single-pixel camera: a simulation study,” J. Biomed. Opt. 24(7), 071612 (2019).
[Crossref]

Al-Hamadi, A.

E. Lilienblum and A. Al-Hamadi, “A structured light approach for 3-D surface reconstruction with a stereo line-scan system,” IEEE Trans. Instrum. Meas. 64(5), 1258–1266 (2015).
[Crossref]

Azimani, H.

Aziz, A. K. S. A.

A. M. Elshurafa, K. Khirallah, H. H. Tawfik, A. Emira, A. K. S. A. Aziz, and S. M. Sedky, “Nonlinear dynamics of spring softening and hardening in folded-MEMS comb drive resonators,” J. Microelectromech. Syst. 20(4), 943–958 (2011).
[Crossref]

Baraniuk, R. G.

M. F. Duarte, M. A. Davenport, D. Takhar, J. N. Laska, T. Sun, K. F. Kelly, and R. G. Baraniuk, “Single-pixel imaging via compressive sampling,” IEEE Signal Process. Mag. 25(2), 83–91 (2008).
[Crossref]

Barut, A.

A. Dubois, O. Levecq, H. Azimani, D. Siret, A. Barut, M. Suppa, V. del Marmol, J. Malvehy, E. Cinotti, P. Rubegni, and J. Perrot, “Line-field confocal optical coherence tomography for high-resolution noninvasive imaging of skin tumors,” J. Biomed. Opt. 23(10), 1 (2018).
[Crossref]

A. Dubois, O. Levecq, H. Azimani, A. Davis, J. Ogien, D. Siret, and A. Barut, “Line-field confocal time-domain optical coherence tomography with dynamic focusing,” Opt. Express 26(26), 33534–33542 (2018).
[Crossref]

Bell, R. J.

R. J. Bell, Introductory Fourier Transform Spectroscopy (Academic, 1972).

Bellato, L.

J. Qin, M. S. Kim, K. Chao, L. Bellato, W. F. Schmidt, B.-K. Cho, and M. Huang, “Inspection of maleic anhydride in starch powder using line-scan hyperspectral Raman chemical imaging technique,” Int. J. Agric. Biol. Eng. 11(6), 120–125 (2018).
[Crossref]

Blok, P. M.

G. Polder, P. M. Blok, H. A. C. De Villiers, J. M. Van Der Wolf, and J. Kamp, “Potato Virus Y Detection in Seed Potatoes Using Deep Learning on Hyperspectral Images,” Front. Plant Sci. 10, 209 (2019).
[Crossref]

Bowman, R.

Bowman, R. W.

M. P. Edgar, G. M. Gibson, R. W. Bowman, B. Sun, N. Radwell, K. J. Mitchell, S. S. Welsh, and J. Padgett, “Simultaneous real-time visible and infrared video with single-pixel detectors,” Sci. Rep. 5(1), 10669 (2015).
[Crossref]

Chao, K.

J. Qin, M. S. Kim, K. Chao, L. Bellato, W. F. Schmidt, B.-K. Cho, and M. Huang, “Inspection of maleic anhydride in starch powder using line-scan hyperspectral Raman chemical imaging technique,” Int. J. Agric. Biol. Eng. 11(6), 120–125 (2018).
[Crossref]

J. Qin, M. S. Kim, K. Chao, S. Dhakal, H. Lee, B.-K. Cho, and C. Mo, “Detection and quantification of adulterants in milk powder using a high-throughput Raman chemical imaging technique,” Food Addit. Contam., Part A 34(2), 152–161 (2017).
[Crossref]

J. Qin, M. S. Kim, K. Chao, M. Gonzalez, and B.-K. Cho, “Quantitative detection of benzoyl peroxide in wheat flour using line-scan macroscale Raman chemical imaging,” Appl. Spectrosc. 71(11), 2469–2476 (2017).
[Crossref]

Chen, W.

Z. Xu, W. Chen, J. Penuelas, M. Padgett, and M. Sun, “1000 fps computational ghost imaging using LED-based structured illumination,” Opt. Express 26(3), 2427–2434 (2018).
[Crossref]

M. Sun, W. Chen, T. Liu, and L. Li, “Image retrieval in spatial and temporal domains with a quadrant detector,” IEEE Photonics J. 9(5), 1–6 (2017).
[Crossref]

Cho, B.-K.

J. Qin, M. S. Kim, K. Chao, L. Bellato, W. F. Schmidt, B.-K. Cho, and M. Huang, “Inspection of maleic anhydride in starch powder using line-scan hyperspectral Raman chemical imaging technique,” Int. J. Agric. Biol. Eng. 11(6), 120–125 (2018).
[Crossref]

J. Qin, M. S. Kim, K. Chao, S. Dhakal, H. Lee, B.-K. Cho, and C. Mo, “Detection and quantification of adulterants in milk powder using a high-throughput Raman chemical imaging technique,” Food Addit. Contam., Part A 34(2), 152–161 (2017).
[Crossref]

J. Qin, M. S. Kim, K. Chao, M. Gonzalez, and B.-K. Cho, “Quantitative detection of benzoyl peroxide in wheat flour using line-scan macroscale Raman chemical imaging,” Appl. Spectrosc. 71(11), 2469–2476 (2017).
[Crossref]

Chrien, T. G.

Cinotti, E.

A. Dubois, O. Levecq, H. Azimani, D. Siret, A. Barut, M. Suppa, V. del Marmol, J. Malvehy, E. Cinotti, P. Rubegni, and J. Perrot, “Line-field confocal optical coherence tomography for high-resolution noninvasive imaging of skin tumors,” J. Biomed. Opt. 23(10), 1 (2018).
[Crossref]

Dadouche, F.

E. Aguénounon, F. Dadouche, W. Uhring, N. Ducros, and S. Gioux, “Single snapshot imaging of optical properties using a single-pixel camera: a simulation study,” J. Biomed. Opt. 24(7), 071612 (2019).
[Crossref]

Davenport, M. A.

M. F. Duarte, M. A. Davenport, D. Takhar, J. N. Laska, T. Sun, K. F. Kelly, and R. G. Baraniuk, “Single-pixel imaging via compressive sampling,” IEEE Signal Process. Mag. 25(2), 83–91 (2008).
[Crossref]

Davis, A.

De Villiers, H. A. C.

G. Polder, P. M. Blok, H. A. C. De Villiers, J. M. Van Der Wolf, and J. Kamp, “Potato Virus Y Detection in Seed Potatoes Using Deep Learning on Hyperspectral Images,” Front. Plant Sci. 10, 209 (2019).
[Crossref]

del Marmol, V.

A. Dubois, O. Levecq, H. Azimani, D. Siret, A. Barut, M. Suppa, V. del Marmol, J. Malvehy, E. Cinotti, P. Rubegni, and J. Perrot, “Line-field confocal optical coherence tomography for high-resolution noninvasive imaging of skin tumors,” J. Biomed. Opt. 23(10), 1 (2018).
[Crossref]

Dhakal, S.

J. Qin, M. S. Kim, K. Chao, S. Dhakal, H. Lee, B.-K. Cho, and C. Mo, “Detection and quantification of adulterants in milk powder using a high-throughput Raman chemical imaging technique,” Food Addit. Contam., Part A 34(2), 152–161 (2017).
[Crossref]

Duarte, M. F.

M. F. Duarte, M. A. Davenport, D. Takhar, J. N. Laska, T. Sun, K. F. Kelly, and R. G. Baraniuk, “Single-pixel imaging via compressive sampling,” IEEE Signal Process. Mag. 25(2), 83–91 (2008).
[Crossref]

Dubois, A.

Ducros, N.

E. Aguénounon, F. Dadouche, W. Uhring, N. Ducros, and S. Gioux, “Single snapshot imaging of optical properties using a single-pixel camera: a simulation study,” J. Biomed. Opt. 24(7), 071612 (2019).
[Crossref]

Edgar, M. P.

M. P. Edgar, G. M. Gibson, R. W. Bowman, B. Sun, N. Radwell, K. J. Mitchell, S. S. Welsh, and J. Padgett, “Simultaneous real-time visible and infrared video with single-pixel detectors,” Sci. Rep. 5(1), 10669 (2015).
[Crossref]

N. Radwell, K. J. Mitchell, G. M. Gibson, M. P. Edgar, R. Bowman, and M. J. Padgett, “Single-pixel infrared and visible microscope,” Optica 1(5), 285–289 (2014).
[Crossref]

Elshurafa, A. M.

A. M. Elshurafa, K. Khirallah, H. H. Tawfik, A. Emira, A. K. S. A. Aziz, and S. M. Sedky, “Nonlinear dynamics of spring softening and hardening in folded-MEMS comb drive resonators,” J. Microelectromech. Syst. 20(4), 943–958 (2011).
[Crossref]

Emira, A.

A. M. Elshurafa, K. Khirallah, H. H. Tawfik, A. Emira, A. K. S. A. Aziz, and S. M. Sedky, “Nonlinear dynamics of spring softening and hardening in folded-MEMS comb drive resonators,” J. Microelectromech. Syst. 20(4), 943–958 (2011).
[Crossref]

Enoch, J. M.

Feng, X.

J. Jiang, X. Feng, F. Liu, Y. Xu, and H. Huang, “Multi-Spectral RGB-NIR Image Classification Using Double-Channel CNN,” IEEE Access 7, 20607–20613 (2019).
[Crossref]

Gao, Y.

Gibson, G. M.

M. P. Edgar, G. M. Gibson, R. W. Bowman, B. Sun, N. Radwell, K. J. Mitchell, S. S. Welsh, and J. Padgett, “Simultaneous real-time visible and infrared video with single-pixel detectors,” Sci. Rep. 5(1), 10669 (2015).
[Crossref]

N. Radwell, K. J. Mitchell, G. M. Gibson, M. P. Edgar, R. Bowman, and M. J. Padgett, “Single-pixel infrared and visible microscope,” Optica 1(5), 285–289 (2014).
[Crossref]

Gioux, S.

E. Aguénounon, F. Dadouche, W. Uhring, N. Ducros, and S. Gioux, “Single snapshot imaging of optical properties using a single-pixel camera: a simulation study,” J. Biomed. Opt. 24(7), 071612 (2019).
[Crossref]

Gonzalez, M.

Green, R. O.

Guo, Y.

Harwit, M.

M. Harwit, Hadamard Transform Optics (Elsevier, The Netherlands, 1979).

Hornbeck, L. J.

L. J. Hornbeck, “Digital Light ProcessingTM for high-brightness, high-resolution applications,” Proc. SPIE 3013, 27–40 (1997).
[Crossref]

Huang, H.

J. Jiang, X. Feng, F. Liu, Y. Xu, and H. Huang, “Multi-Spectral RGB-NIR Image Classification Using Double-Channel CNN,” IEEE Access 7, 20607–20613 (2019).
[Crossref]

Huang, J.

Huang, M.

J. Qin, M. S. Kim, K. Chao, L. Bellato, W. F. Schmidt, B.-K. Cho, and M. Huang, “Inspection of maleic anhydride in starch powder using line-scan hyperspectral Raman chemical imaging technique,” Int. J. Agric. Biol. Eng. 11(6), 120–125 (2018).
[Crossref]

Jiang, J.

J. Jiang, X. Feng, F. Liu, Y. Xu, and H. Huang, “Multi-Spectral RGB-NIR Image Classification Using Double-Channel CNN,” IEEE Access 7, 20607–20613 (2019).
[Crossref]

Jiao, S.

Kamp, J.

G. Polder, P. M. Blok, H. A. C. De Villiers, J. M. Van Der Wolf, and J. Kamp, “Potato Virus Y Detection in Seed Potatoes Using Deep Learning on Hyperspectral Images,” Front. Plant Sci. 10, 209 (2019).
[Crossref]

Kelly, K. F.

M. F. Duarte, M. A. Davenport, D. Takhar, J. N. Laska, T. Sun, K. F. Kelly, and R. G. Baraniuk, “Single-pixel imaging via compressive sampling,” IEEE Signal Process. Mag. 25(2), 83–91 (2008).
[Crossref]

Khirallah, K.

A. M. Elshurafa, K. Khirallah, H. H. Tawfik, A. Emira, A. K. S. A. Aziz, and S. M. Sedky, “Nonlinear dynamics of spring softening and hardening in folded-MEMS comb drive resonators,” J. Microelectromech. Syst. 20(4), 943–958 (2011).
[Crossref]

Kho, A.

Kim, M. S.

J. Qin, M. S. Kim, K. Chao, L. Bellato, W. F. Schmidt, B.-K. Cho, and M. Huang, “Inspection of maleic anhydride in starch powder using line-scan hyperspectral Raman chemical imaging technique,” Int. J. Agric. Biol. Eng. 11(6), 120–125 (2018).
[Crossref]

J. Qin, M. S. Kim, K. Chao, S. Dhakal, H. Lee, B.-K. Cho, and C. Mo, “Detection and quantification of adulterants in milk powder using a high-throughput Raman chemical imaging technique,” Food Addit. Contam., Part A 34(2), 152–161 (2017).
[Crossref]

J. Qin, M. S. Kim, K. Chao, M. Gonzalez, and B.-K. Cho, “Quantitative detection of benzoyl peroxide in wheat flour using line-scan macroscale Raman chemical imaging,” Appl. Spectrosc. 71(11), 2469–2476 (2017).
[Crossref]

Laska, J. N.

M. F. Duarte, M. A. Davenport, D. Takhar, J. N. Laska, T. Sun, K. F. Kelly, and R. G. Baraniuk, “Single-pixel imaging via compressive sampling,” IEEE Signal Process. Mag. 25(2), 83–91 (2008).
[Crossref]

Lee, H.

J. Qin, M. S. Kim, K. Chao, S. Dhakal, H. Lee, B.-K. Cho, and C. Mo, “Detection and quantification of adulterants in milk powder using a high-throughput Raman chemical imaging technique,” Food Addit. Contam., Part A 34(2), 152–161 (2017).
[Crossref]

Lei, T.

Levecq, O.

Levi-Setti, R.

R. Levi-Setti, D. A. Park, and R. Winston, “The corneal cones of Limulus as optimised light concentrators,” Nature 253(5487), 115–116 (1975).
[Crossref]

Li, K.

L. Liao, K. Li, C. Yang, and J. Liu, “Low-cost image compressive sensing with multiple measurement rates for object detection,” Sensors 19(9), 2079 (2019).
[Crossref]

Li, L.

L. Li, B. Wang, J. Pottas, and W. Lipiński, “Design of a compound parabolic concentrator for a multi-source high-flux solar simulator,” Sol. Energy 183, 805–811 (2019).
[Crossref]

M. Sun, W. Chen, T. Liu, and L. Li, “Image retrieval in spatial and temporal domains with a quadrant detector,” IEEE Photonics J. 9(5), 1–6 (2017).
[Crossref]

Liao, L.

L. Liao, K. Li, C. Yang, and J. Liu, “Low-cost image compressive sensing with multiple measurement rates for object detection,” Sensors 19(9), 2079 (2019).
[Crossref]

Lilienblum, E.

E. Lilienblum and A. Al-Hamadi, “A structured light approach for 3-D surface reconstruction with a stereo line-scan system,” IEEE Trans. Instrum. Meas. 64(5), 1258–1266 (2015).
[Crossref]

Lin, J.

Lipinski, W.

L. Li, B. Wang, J. Pottas, and W. Lipiński, “Design of a compound parabolic concentrator for a multi-source high-flux solar simulator,” Sol. Energy 183, 805–811 (2019).
[Crossref]

Liu, D.

Liu, F.

J. Jiang, X. Feng, F. Liu, Y. Xu, and H. Huang, “Multi-Spectral RGB-NIR Image Classification Using Double-Channel CNN,” IEEE Access 7, 20607–20613 (2019).
[Crossref]

Liu, J.

L. Liao, K. Li, C. Yang, and J. Liu, “Low-cost image compressive sensing with multiple measurement rates for object detection,” Sensors 19(9), 2079 (2019).
[Crossref]

Liu, T.

M. Sun, W. Chen, T. Liu, and L. Li, “Image retrieval in spatial and temporal domains with a quadrant detector,” IEEE Photonics J. 9(5), 1–6 (2017).
[Crossref]

Liu, Z.

Z. Liu, S. Wu, Q. Wu, C. Quan, and Y. Ren, “A novel stereo vision measurement system using both line scan camera and frame camera,” IEEE Trans. Instrum. Meas. (to be published) (2018).

Malvehy, J.

A. Dubois, O. Levecq, H. Azimani, D. Siret, A. Barut, M. Suppa, V. del Marmol, J. Malvehy, E. Cinotti, P. Rubegni, and J. Perrot, “Line-field confocal optical coherence tomography for high-resolution noninvasive imaging of skin tumors,” J. Biomed. Opt. 23(10), 1 (2018).
[Crossref]

Meng, W.

Mitchell, K. J.

M. P. Edgar, G. M. Gibson, R. W. Bowman, B. Sun, N. Radwell, K. J. Mitchell, S. S. Welsh, and J. Padgett, “Simultaneous real-time visible and infrared video with single-pixel detectors,” Sci. Rep. 5(1), 10669 (2015).
[Crossref]

N. Radwell, K. J. Mitchell, G. M. Gibson, M. P. Edgar, R. Bowman, and M. J. Padgett, “Single-pixel infrared and visible microscope,” Optica 1(5), 285–289 (2014).
[Crossref]

Mo, C.

J. Qin, M. S. Kim, K. Chao, S. Dhakal, H. Lee, B.-K. Cho, and C. Mo, “Detection and quantification of adulterants in milk powder using a high-throughput Raman chemical imaging technique,” Food Addit. Contam., Part A 34(2), 152–161 (2017).
[Crossref]

Mouroulis, P.

Ogien, J.

Padgett, J.

M. P. Edgar, G. M. Gibson, R. W. Bowman, B. Sun, N. Radwell, K. J. Mitchell, S. S. Welsh, and J. Padgett, “Simultaneous real-time visible and infrared video with single-pixel detectors,” Sci. Rep. 5(1), 10669 (2015).
[Crossref]

Padgett, M.

Padgett, M. J.

Park, D. A.

R. Levi-Setti, D. A. Park, and R. Winston, “The corneal cones of Limulus as optimised light concentrators,” Nature 253(5487), 115–116 (1975).
[Crossref]

Penuelas, J.

Perrot, J.

A. Dubois, O. Levecq, H. Azimani, D. Siret, A. Barut, M. Suppa, V. del Marmol, J. Malvehy, E. Cinotti, P. Rubegni, and J. Perrot, “Line-field confocal optical coherence tomography for high-resolution noninvasive imaging of skin tumors,” J. Biomed. Opt. 23(10), 1 (2018).
[Crossref]

Polder, G.

G. Polder, P. M. Blok, H. A. C. De Villiers, J. M. Van Der Wolf, and J. Kamp, “Potato Virus Y Detection in Seed Potatoes Using Deep Learning on Hyperspectral Images,” Front. Plant Sci. 10, 209 (2019).
[Crossref]

Pottas, J.

L. Li, B. Wang, J. Pottas, and W. Lipiński, “Design of a compound parabolic concentrator for a multi-source high-flux solar simulator,” Sol. Energy 183, 805–811 (2019).
[Crossref]

Qin, J.

J. Qin, M. S. Kim, K. Chao, L. Bellato, W. F. Schmidt, B.-K. Cho, and M. Huang, “Inspection of maleic anhydride in starch powder using line-scan hyperspectral Raman chemical imaging technique,” Int. J. Agric. Biol. Eng. 11(6), 120–125 (2018).
[Crossref]

J. Qin, M. S. Kim, K. Chao, S. Dhakal, H. Lee, B.-K. Cho, and C. Mo, “Detection and quantification of adulterants in milk powder using a high-throughput Raman chemical imaging technique,” Food Addit. Contam., Part A 34(2), 152–161 (2017).
[Crossref]

J. Qin, M. S. Kim, K. Chao, M. Gonzalez, and B.-K. Cho, “Quantitative detection of benzoyl peroxide in wheat flour using line-scan macroscale Raman chemical imaging,” Appl. Spectrosc. 71(11), 2469–2476 (2017).
[Crossref]

Quan, C.

Z. Liu, S. Wu, Q. Wu, C. Quan, and Y. Ren, “A novel stereo vision measurement system using both line scan camera and frame camera,” IEEE Trans. Instrum. Meas. (to be published) (2018).

Radwell, N.

M. P. Edgar, G. M. Gibson, R. W. Bowman, B. Sun, N. Radwell, K. J. Mitchell, S. S. Welsh, and J. Padgett, “Simultaneous real-time visible and infrared video with single-pixel detectors,” Sci. Rep. 5(1), 10669 (2015).
[Crossref]

N. Radwell, K. J. Mitchell, G. M. Gibson, M. P. Edgar, R. Bowman, and M. J. Padgett, “Single-pixel infrared and visible microscope,” Optica 1(5), 285–289 (2014).
[Crossref]

Ren, Y.

Z. Liu, S. Wu, Q. Wu, C. Quan, and Y. Ren, “A novel stereo vision measurement system using both line scan camera and frame camera,” IEEE Trans. Instrum. Meas. (to be published) (2018).

Rubegni, P.

A. Dubois, O. Levecq, H. Azimani, D. Siret, A. Barut, M. Suppa, V. del Marmol, J. Malvehy, E. Cinotti, P. Rubegni, and J. Perrot, “Line-field confocal optical coherence tomography for high-resolution noninvasive imaging of skin tumors,” J. Biomed. Opt. 23(10), 1 (2018).
[Crossref]

Schmidt, W. F.

J. Qin, M. S. Kim, K. Chao, L. Bellato, W. F. Schmidt, B.-K. Cho, and M. Huang, “Inspection of maleic anhydride in starch powder using line-scan hyperspectral Raman chemical imaging technique,” Int. J. Agric. Biol. Eng. 11(6), 120–125 (2018).
[Crossref]

Sedky, S. M.

A. M. Elshurafa, K. Khirallah, H. H. Tawfik, A. Emira, A. K. S. A. Aziz, and S. M. Sedky, “Nonlinear dynamics of spring softening and hardening in folded-MEMS comb drive resonators,” J. Microelectromech. Syst. 20(4), 943–958 (2011).
[Crossref]

Shi, D.

Siret, D.

Srinivasan, V. J.

Sun, B.

Sun, M.

M. Sun and J. Zhang, “Single-pixel imaging and its application in three-dimensional reconstruction: a brief review,” Sensors 19(3), 732 (2019).
[Crossref]

S. Jiao, M. Sun, Y. Gao, T. Lei, Z. Xie, and X. Yuan, “Motion estimation and quality enhancement for a single image in dynamic single-pixel imaging,” Opt. Express 27(9), 12841–12854 (2019).
[Crossref]

Z. Xu, W. Chen, J. Penuelas, M. Padgett, and M. Sun, “1000 fps computational ghost imaging using LED-based structured illumination,” Opt. Express 26(3), 2427–2434 (2018).
[Crossref]

M. Sun, W. Chen, T. Liu, and L. Li, “Image retrieval in spatial and temporal domains with a quadrant detector,” IEEE Photonics J. 9(5), 1–6 (2017).
[Crossref]

Sun, T.

M. F. Duarte, M. A. Davenport, D. Takhar, J. N. Laska, T. Sun, K. F. Kelly, and R. G. Baraniuk, “Single-pixel imaging via compressive sampling,” IEEE Signal Process. Mag. 25(2), 83–91 (2008).
[Crossref]

Suppa, M.

A. Dubois, O. Levecq, H. Azimani, D. Siret, A. Barut, M. Suppa, V. del Marmol, J. Malvehy, E. Cinotti, P. Rubegni, and J. Perrot, “Line-field confocal optical coherence tomography for high-resolution noninvasive imaging of skin tumors,” J. Biomed. Opt. 23(10), 1 (2018).
[Crossref]

Takhar, D.

M. F. Duarte, M. A. Davenport, D. Takhar, J. N. Laska, T. Sun, K. F. Kelly, and R. G. Baraniuk, “Single-pixel imaging via compressive sampling,” IEEE Signal Process. Mag. 25(2), 83–91 (2008).
[Crossref]

Tawfik, H. H.

A. M. Elshurafa, K. Khirallah, H. H. Tawfik, A. Emira, A. K. S. A. Aziz, and S. M. Sedky, “Nonlinear dynamics of spring softening and hardening in folded-MEMS comb drive resonators,” J. Microelectromech. Syst. 20(4), 943–958 (2011).
[Crossref]

Uhring, W.

E. Aguénounon, F. Dadouche, W. Uhring, N. Ducros, and S. Gioux, “Single snapshot imaging of optical properties using a single-pixel camera: a simulation study,” J. Biomed. Opt. 24(7), 071612 (2019).
[Crossref]

Van Der Wolf, J. M.

G. Polder, P. M. Blok, H. A. C. De Villiers, J. M. Van Der Wolf, and J. Kamp, “Potato Virus Y Detection in Seed Potatoes Using Deep Learning on Hyperspectral Images,” Front. Plant Sci. 10, 209 (2019).
[Crossref]

Wang, B.

L. Li, B. Wang, J. Pottas, and W. Lipiński, “Design of a compound parabolic concentrator for a multi-source high-flux solar simulator,” Sol. Energy 183, 805–811 (2019).
[Crossref]

Wang, X.

Wang, Y.

Welford, W. T.

W. T. Welford and R. Winston, High Collection Nonimaging Optics (Academic, 1989).

Welsh, S. S.

M. P. Edgar, G. M. Gibson, R. W. Bowman, B. Sun, N. Radwell, K. J. Mitchell, S. S. Welsh, and J. Padgett, “Simultaneous real-time visible and infrared video with single-pixel detectors,” Sci. Rep. 5(1), 10669 (2015).
[Crossref]

Winston, R.

R. Levi-Setti, D. A. Park, and R. Winston, “The corneal cones of Limulus as optimised light concentrators,” Nature 253(5487), 115–116 (1975).
[Crossref]

R. Winston and J. M. Enoch, “Retinal cone receptor as an ideal light collectort,” J. Opt. Soc. Am. 61(8), 1120–1121 (1971).
[Crossref]

W. T. Welford and R. Winston, High Collection Nonimaging Optics (Academic, 1989).

Wu, Q.

Z. Liu, S. Wu, Q. Wu, C. Quan, and Y. Ren, “A novel stereo vision measurement system using both line scan camera and frame camera,” IEEE Trans. Instrum. Meas. (to be published) (2018).

Wu, S.

Z. Liu, S. Wu, Q. Wu, C. Quan, and Y. Ren, “A novel stereo vision measurement system using both line scan camera and frame camera,” IEEE Trans. Instrum. Meas. (to be published) (2018).

Xie, C.

Xie, Z.

Xu, Y.

J. Jiang, X. Feng, F. Liu, Y. Xu, and H. Huang, “Multi-Spectral RGB-NIR Image Classification Using Double-Channel CNN,” IEEE Access 7, 20607–20613 (2019).
[Crossref]

Xu, Z.

Yang, C.

L. Liao, K. Li, C. Yang, and J. Liu, “Low-cost image compressive sensing with multiple measurement rates for object detection,” Sensors 19(9), 2079 (2019).
[Crossref]

Yang, L.

Yin, K.

Yuan, K.

Yuan, X.

Zhang, J.

M. Sun and J. Zhang, “Single-pixel imaging and its application in three-dimensional reconstruction: a brief review,” Sensors 19(3), 732 (2019).
[Crossref]

Zhang, Z.

Zheng, G.

Zhong, J.

Zhu, J.

Zhu, W.

Appl. Opt. (2)

Appl. Spectrosc. (1)

Biomed. Opt. Express (1)

Food Addit. Contam., Part A (1)

J. Qin, M. S. Kim, K. Chao, S. Dhakal, H. Lee, B.-K. Cho, and C. Mo, “Detection and quantification of adulterants in milk powder using a high-throughput Raman chemical imaging technique,” Food Addit. Contam., Part A 34(2), 152–161 (2017).
[Crossref]

Front. Plant Sci. (1)

G. Polder, P. M. Blok, H. A. C. De Villiers, J. M. Van Der Wolf, and J. Kamp, “Potato Virus Y Detection in Seed Potatoes Using Deep Learning on Hyperspectral Images,” Front. Plant Sci. 10, 209 (2019).
[Crossref]

IEEE Access (1)

J. Jiang, X. Feng, F. Liu, Y. Xu, and H. Huang, “Multi-Spectral RGB-NIR Image Classification Using Double-Channel CNN,” IEEE Access 7, 20607–20613 (2019).
[Crossref]

IEEE Photonics J. (1)

M. Sun, W. Chen, T. Liu, and L. Li, “Image retrieval in spatial and temporal domains with a quadrant detector,” IEEE Photonics J. 9(5), 1–6 (2017).
[Crossref]

IEEE Signal Process. Mag. (1)

M. F. Duarte, M. A. Davenport, D. Takhar, J. N. Laska, T. Sun, K. F. Kelly, and R. G. Baraniuk, “Single-pixel imaging via compressive sampling,” IEEE Signal Process. Mag. 25(2), 83–91 (2008).
[Crossref]

IEEE Trans. Instrum. Meas. (1)

E. Lilienblum and A. Al-Hamadi, “A structured light approach for 3-D surface reconstruction with a stereo line-scan system,” IEEE Trans. Instrum. Meas. 64(5), 1258–1266 (2015).
[Crossref]

Int. J. Agric. Biol. Eng. (1)

J. Qin, M. S. Kim, K. Chao, L. Bellato, W. F. Schmidt, B.-K. Cho, and M. Huang, “Inspection of maleic anhydride in starch powder using line-scan hyperspectral Raman chemical imaging technique,” Int. J. Agric. Biol. Eng. 11(6), 120–125 (2018).
[Crossref]

J. Biomed. Opt. (2)

E. Aguénounon, F. Dadouche, W. Uhring, N. Ducros, and S. Gioux, “Single snapshot imaging of optical properties using a single-pixel camera: a simulation study,” J. Biomed. Opt. 24(7), 071612 (2019).
[Crossref]

A. Dubois, O. Levecq, H. Azimani, D. Siret, A. Barut, M. Suppa, V. del Marmol, J. Malvehy, E. Cinotti, P. Rubegni, and J. Perrot, “Line-field confocal optical coherence tomography for high-resolution noninvasive imaging of skin tumors,” J. Biomed. Opt. 23(10), 1 (2018).
[Crossref]

J. Microelectromech. Syst. (1)

A. M. Elshurafa, K. Khirallah, H. H. Tawfik, A. Emira, A. K. S. A. Aziz, and S. M. Sedky, “Nonlinear dynamics of spring softening and hardening in folded-MEMS comb drive resonators,” J. Microelectromech. Syst. 20(4), 943–958 (2011).
[Crossref]

J. Opt. Soc. Am. (1)

Nature (1)

R. Levi-Setti, D. A. Park, and R. Winston, “The corneal cones of Limulus as optimised light concentrators,” Nature 253(5487), 115–116 (1975).
[Crossref]

Opt. Express (5)

Opt. Lett. (1)

Optica (1)

Proc. SPIE (1)

L. J. Hornbeck, “Digital Light ProcessingTM for high-brightness, high-resolution applications,” Proc. SPIE 3013, 27–40 (1997).
[Crossref]

Sci. Rep. (1)

M. P. Edgar, G. M. Gibson, R. W. Bowman, B. Sun, N. Radwell, K. J. Mitchell, S. S. Welsh, and J. Padgett, “Simultaneous real-time visible and infrared video with single-pixel detectors,” Sci. Rep. 5(1), 10669 (2015).
[Crossref]

Sensors (2)

M. Sun and J. Zhang, “Single-pixel imaging and its application in three-dimensional reconstruction: a brief review,” Sensors 19(3), 732 (2019).
[Crossref]

L. Liao, K. Li, C. Yang, and J. Liu, “Low-cost image compressive sensing with multiple measurement rates for object detection,” Sensors 19(9), 2079 (2019).
[Crossref]

Sol. Energy (1)

L. Li, B. Wang, J. Pottas, and W. Lipiński, “Design of a compound parabolic concentrator for a multi-source high-flux solar simulator,” Sol. Energy 183, 805–811 (2019).
[Crossref]

Other (4)

W. T. Welford and R. Winston, High Collection Nonimaging Optics (Academic, 1989).

R. J. Bell, Introductory Fourier Transform Spectroscopy (Academic, 1972).

M. Harwit, Hadamard Transform Optics (Elsevier, The Netherlands, 1979).

Z. Liu, S. Wu, Q. Wu, C. Quan, and Y. Ren, “A novel stereo vision measurement system using both line scan camera and frame camera,” IEEE Trans. Instrum. Meas. (to be published) (2018).

Cited By

OSA participates in Crossref's Cited-By Linking service. Citing articles from OSA journals and other participating publishers are listed here.

Alert me when this article is cited.


Figures (9)

Fig. 1.
Fig. 1. The schematic of the self-referencing cascaded line-scan camera.
Fig. 2.
Fig. 2. (a) The schematic of a slit and an encoding mask. (b) Self-referencing working mechanism. (c) Microscope picture of one encoding mask.
Fig. 3.
Fig. 3. (a) Fabrication process. (b) Microscope image of the SOI MEMS chip having two cascaded encoding masks. (c) The FEM simulated resonance mode shape.
Fig. 4.
Fig. 4. (a) FEM simulated amplification result. (b) Top view of the oscillation platform. The oscillation amplitudes of (c) left MEMS encoding mask and (d) right MEMS encoding mask, respectively as functions of the driving frequency.
Fig. 5.
Fig. 5. (a) Miniature CPC fabrication process. (b) A perspective view of a CPC. (c) Completed CPCs.
Fig. 6.
Fig. 6. (a) The PCB board with photodetectors integrated with their respective CPCs and amplification circuits. (b) SOI MEMS chip combined with CPCs. (c) Oscillation platform combined with PCB board.
Fig. 7.
Fig. 7. Schematic showing the experimental system construction of a line-scan camera.
Fig. 8.
Fig. 8. (a) Photos showing the object – an array of LEDs when they are turned (i) off and (ii) on. In (a)(ii), the environment light is turned off, which is the actual experimental condition used. (b) The acquired raw data of (i) one period and (ii) the frame beginning. (c) The extracted effective outputs. (d) The recovered line image of the 6 turned-on LEDs.
Fig. 9.
Fig. 9. The reconstructed 1D image when (a) 12 LEDs are all turned on, (b) the 1st, 2nd, 5th, 6th, 8th, 9th, 10th and 12th LEDs are turned on, (c) the 1st, 3rd, 4th, 5th, 6th, 7th, 9th, 11th and 12th LEDs are turned on, (d) 40 LEDs arranged in alphabet shapes “W” and “M”. (e) The 2D image recovered by the cascaded line-scan camera using push-broom scanning.

Equations (7)

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

m i = j M a i j I ( x j )
M = AI
I = A 1 M
A 1 = 2 M + 1 ( 2 A T J )
d 2 / d 1 = sin θ max
L = ( 1 / 2 ) ( d 1 + d 2 ) cot θ max
N CPC sin θ max = N air sin θ max

Metrics