Advertisement

High-SNR Hyperspectral Night-Vision Image Acquisition with Multiplexing

  • Lianfa BaiEmail author
  • Jing Han
  • Jiang Yue
Chapter

Abstract

High-throughput and high-spectral resolution are essential requirements for spectrometers. Conventional slit-based spectrometers require the input slit to be narrow to achieve a reasonable resolution. However, too small a slit cannot gather enough radiation. Many designs have been presented to address these demands. One method (i.e. the Jacquinot advantage) maximised throughput without sacrificing spectral resolution. Over several decades, there have been two important, strongly investigated approaches to improving spectrometre performance. One resulted in the coded-aperture spectrometre (CAS); another resulted in the Fourier transform spectrometre (FTS). CAS replaced the slit with a two-dimensional coded matrix aperture (i.e. mask), introduced to increase light throughput without loss of spectral resolution. After more than half a century of development, the top CAS is the Hadamard transform spectrometre (HTS), whose encoded aperture theories are based on Hadamard matrices. However, there have more recently been some new static, multiplex CASs proposed, based on new mathematical models. In this chapter, we introduce the multiplexing measurements applied to spectrometers for high-SNR data acquisition.

References

  1. Bian, X., Zhang, T., Yan, L., Zhang, X., Fang, H., & Liu, H. (2013). Spatial–spectral method for classification of hyperspectral images. Optics Letters, 38, 815–817.CrossRefGoogle Scholar
  2. Cull, E. C., Gehm, M. E., Brady, D. J., Hsieh, C. R., Momtahan, O., & Adibi, A. (2007). Dispersion multiplexing with broadband filtering for miniature spectrometers. Applied Optics, 46, 365.CrossRefGoogle Scholar
  3. Damaschini, R. (1993). Limitation of the multiplex gain in Hadamard transform spectroscopy. Pure and Applied Optics, 2, 173–178.CrossRefGoogle Scholar
  4. Girard, A. (1963). Spectrometre a grilles. Applied optics, 2(1), 79–87.CrossRefGoogle Scholar
  5. Golay, M. J. E. (1949). Multi-slit spectrometry. Journal of the Optical Society of America, 39(6), 437–444.CrossRefGoogle Scholar
  6. Golay, M. J. E. (1951). Static multislit spectrometry and its application to the panoramic display of infrared spectra. Journal of the Optical Society of America, 41, 468–472.CrossRefGoogle Scholar
  7. Harwit, M., & Sloane, N. J. A. (1979). Hadamard transform optics (p. 1444). New York: Academic Press.zbMATHGoogle Scholar
  8. Ibbett, R. N., Aspinall, D., & Grainger, J. F. (1968). Real-time multiplexing of dispersed spectra in any wavelength region. Applied Optics, 7(6), 1089–1094.CrossRefGoogle Scholar
  9. Lucke, R. L., Corson, M., McGlothlin, N. R., Butcher, S. D., Wood, D. L., Korwan, D. R., et al. (2011). Hyperspectral Imager for the Coastal Ocean: Instrument description and first images. Applied Optics, 50, 1501–1516.CrossRefGoogle Scholar
  10. Moses, W. J., Bowles, J. H., Lucke, R. L., & Corson, M. R. (2012). Impact of signal-to-noise ratio in a hyperspectral sensor on the accuracy of biophysical parameter estimation in case II waters. Optics Express, 20(4), 4309.CrossRefGoogle Scholar
  11. Mrozack, A., Marks, D. L., & Brady, D. J. (2012). Coded aperture spectroscopy with denoising through sparsity. Optics Express, 20, 2297–2309.CrossRefGoogle Scholar
  12. Shimano, N. (2006). Recovery of spectral reflectances of objects being imaged without prior knowledge. IEEE Transactions on Image Processing, 15, 1848–1856.CrossRefGoogle Scholar
  13. Snyder, D. L., Helstrom, C. W., Lanterman, A. D., Faisal, M., & White, R. L. (1995). Compensation for readout noise in CCD images. Journal of the Optical Society of America A. Optics and Image Science, 12, 272–283.CrossRefGoogle Scholar
  14. Streeter, L., Burling-Claridge, G. R., Cree, M. J., & Künnemeyer, R. (2009). Optical full Hadamard matrix multiplexing and noise effects. Applied Optics, 48, 2078–2085.CrossRefGoogle Scholar
  15. Sun, X., Hu, B., Li, L., & Wang, Z. (2012). An engineering prototype of Hadamard transform spectral imager based on digital micro-mirror Device. Optics & Laser Technology, 44, 210–217.CrossRefGoogle Scholar
  16. Tilotta, D. C., Hammaker, R. M., & Fateley, W. G. (1987). Multiplex advantage in Hadamard transform spectrometry utilizing solid-state encoding masks with uniform, bistable optical transmission defects. Applied Optics, 26, 4285–4292.CrossRefGoogle Scholar
  17. Wang, Z., Yue, J., & Han, J. (2017). High-SNR spectrum measurement based on Hadamard encoding and sparse reconstruction. Applied Physics, 123, 277.CrossRefGoogle Scholar
  18. Wuttig, A. (2005). Optimal transformations for optical multiplex measurements in the presence of photon noise. Applied Optics, 44, 2710–2719.CrossRefGoogle Scholar
  19. Xiang, D., & Arnold, M. A. (2011). Solid-state digital micro-mirror array spectrometre for Hadamard transform measurements of glucose and lactate in aqueous solutions. Applied Spectroscopy, 65, 1170–1180.CrossRefGoogle Scholar
  20. Xu, J., Hu, B., Feng, D., Fan, X., & Qian, Q. (2012). Analysis and study of the interlaced encoding pixels in Hadamard transform spectral imager based on DMD. Optics and Lasers in Engineering, 50, 458–464.CrossRefGoogle Scholar
  21. Yue, J., Han, J., & Li, L. (2018). Denoising analysis of spatial pixel multiplex coded spectrometre with Hadamard H-matrix. Optics Communications, 407, 355–360.CrossRefGoogle Scholar
  22. Yue, J., Han, J., Zhang, Y., & Bai, L. (2014). High-throughput deconvolution-resolved computational spectrometre. Chinese Optics Letters, 12, 043001.CrossRefGoogle Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  1. 1.School of Electronic and Optical EngineeringNanjing University of Science and TechnologyNanjingChina
  2. 2.School of Electronic and Optical EngineeringNanjing University of Science and TechnologyNanjingChina
  3. 3.National Key Laboratory of Transient PhysicsNanjing University of Science and TechnologyNanjingChina

Personalised recommendations