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All issues Volume 10 (2015) J. Eur. Opt. Soc.-Rapid Publ., 10 (2015) 15037 References
Open Access
Issue
J. Eur. Opt. Soc.-Rapid Publ.
Volume 10, 2015
Article Number 15037
Number of page(s) 7
DOI https://doi.org/10.2971/jeos.2015.15037
Published online 12 July 2015
  1. N. Hagen, and M. W. Kudenov, “Review of snapshot spectral imaging technologies,” Opt. Eng. 52, 090901 (2013). [NASA ADS] [CrossRef] [Google Scholar]
  2. R. C. Lyon, D. S. Lester, E. N. Lewis, E. Lee, L. X. Yu, E. H. Jefferson, and A. S. Hussain, “Near-infrared spectral imaging for quality assurance of pharmaceutical products: Analysis of tablets to assess powder blend homogeneity,” AAPS PharmSciTech. 3, 1–15 (2002). [CrossRef] [Google Scholar]
  3. C. Zhang, B. Zhao, and B. Xiangli, “Wide-field-of-view polarization interference imaging spectrometer,” Appl. Opt. 43, 6090–6094 (2004). [NASA ADS] [CrossRef] [Google Scholar]
  4. Y. Xu, R. Xu, F. Li, and J. Wang, “Verification of programmable, large-FOV spectral imaging technology based on a staring/scanning area-array detector,” Proc. SPIE 9263, 92630I (2014). [NASA ADS] [CrossRef] [Google Scholar]
  5. Z. Pan, G. Healey, M. Prasad, and B. Tromberg, “Face recognition in hyperspectral images,” IEEE T. Pattern Anal. 25, 1552–1560 (2003). [CrossRef] [Google Scholar]
  6. H. Chang, A. Koschan, M. Abidi, S. G. Kong, and C.-H. Won, “Multispectral visible and infrared imaging for face recognition,” in Proceedings to the IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, 1-6 (IEEE, Anchorage, 2008). [Google Scholar]
  7. P. J. Nystrom, and L. K. Mestha, “Automatically focusing a spectral imaging system onto an object in a scene,” US20140240511 A1 (2014). [Google Scholar]
  8. C. Feng, X. Zhang, L. Shen, and S. Zhuo, “Multi-spectral imaging system for shadow detection and attenuation,” US20140240477 A1 (2014). [Google Scholar]
  9. H. Maeng, S. Liao, D. Kang, S.-W. Lee, and A. K. Jain, “Nighttime face recognition at long distance: Cross-distance and crossspectral matching,” in Computer Vision - ACCV 2012, K. M. Lee, Y. Matsushita, J. M. Rehg, and Z. Hu, eds., 708–721 (Springer Berlin Heidelberg, 2013). [Google Scholar]
  10. J. Antila, R. Mannila, U. Kantojärvi, C. Holmlund, A. Rissanen, I. Näkki, J. Ollila, and H. Saari, “Spectral imaging device based on a tuneable MEMS Fabry-Perot interferometer,” Proc. SPIE 8374, 83740F (2012). [NASA ADS] [CrossRef] [Google Scholar]
  11. P. Jacquinot, “The luminosity of spectrometers with prisms, gratings, or Fabry-Pérot etalons,” J. Opt. Soc. Am. 44, 761–765 (1954). [NASA ADS] [CrossRef] [Google Scholar]
  12. J. Praks, A. Kestilä, M. Hallikainen, H. Saari, J. Antila, P. Janhunen, and R. Vainio, “Aalto-1 - An experimental nanosatellite for hyperspectral remote sensing,” in Proceedings to the IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 4367-4370 (IEEE, Vancouver, 2011). [Google Scholar]
  13. H. Saari, I. Pölönen, H. Salo, E. Honkavaara, T. Hakala, C. Holmlund, J. Mäkynen, R. Mannila, T. Antila, and A. Akujärvi, “Miniaturized hyperspectral imager calibration and UAV flight campaigns”, Proc. SPIE 8889, 88891O (2013). [NASA ADS] [CrossRef] [Google Scholar]
  14. E. Honkavaara, J. Kaivosoja, J. Mäkynen, I. Pellikka, L. Pesonen, H. Saari, H. Salo, T. Hakala, L. Marklelin, and T. Rosnell, “Hyperspectral reflectance signatures and point clouds for precision agriculture by light weight UAV imaging system”, ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci. I-7, 353–358 (2012). [CrossRef] [Google Scholar]
  15. T. J. Kentischer, W. Schmidt, M. Sigwarth, and M. v. Uexküll, “TESOS, a double Fabry-Perot instrument for solar spectroscopy,” Astron. Astrophys. 340, 569–578 (1998). [NASA ADS] [Google Scholar]
  16. E. Hecht, Optics (fourth edition, Addison Wesley, San Francisco, 2002). [Google Scholar]
  17. J. M. Vaughan, The Fabry-Perot interferometer - History, theory, practice and applications (IOP Publishing Ltd, Bristol, 1989). [Google Scholar]
  18. W. H. Steel, Interferometry (Cambridge University Press, New York, 1967). [Google Scholar]
  19. H. A. Macleod, Thin-film optical filters (fourth edition, CRC Press, Boca Raton, 2010). [CrossRef] [Google Scholar]
  20. O. El Gawhary, M. C. Dheur, S. F. Pereira, and J. J. M. Braat, “Extension of the classical Fabry-Perot formula to 1D multilayered structures,” Appl. Phys. B 111, 637–645 (2013). [NASA ADS] [CrossRef] [Google Scholar]
  21. I. Livshits, Z. Hou, P. van Grol, Y. Shao, M. van Turnhout, P. Urbach, and F. Bociort, “Using saddle points for challenging optical design tasks,” Proc. SPIE 9192, 919204 (2014). [NASA ADS] [CrossRef] [Google Scholar]
  22. http://www.rikola.fi/site/?page_id=46 [Google Scholar]
  23. http://goochandhousego.com/news/ miniature-spectral-imaging-camera/ [Google Scholar]
  24. B. Schmitt, J. P. Borgogno, G. Albrand, and E. Pelletier, “In situ and air index measurements: influence of the deposition parameters on the shift of TiO2/SiO2 Fabry-Perot filters,” Appl. Opt. 25, 3909–3915 (1986). [NASA ADS] [CrossRef] [Google Scholar]
  25. D. C. Brown, “Decentering distortion of lenses,” Photogramm. Eng. 32, 444–462 (1966). [Google Scholar]
  26. M. Aggarwal, H. Hua, and N. Ahuja, “On cosine-fourth and vignetting effects in real lenses,” Proceedings to the Eighth IEEE International Conference on Computer Vision, 472-479 (IEEE, Vancouver, 2001). [Google Scholar]
  27. CODE V Systems Analysis Reference Manual 10.6 (Synopsys, 2013). [Google Scholar]

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