OSA's Digital Library

Applied Optics

Applied Optics


  • Editor: James C. Wyant
  • Vol. 47, Iss. 28 — Oct. 1, 2008
  • pp: F71–F76

Design and fabrication of a low-cost, multispectral imaging system

Scott A. Mathews  »View Author Affiliations

Applied Optics, Vol. 47, Issue 28, pp. F71-F76 (2008)

View Full Text Article

Enhanced HTML    Acrobat PDF (3807 KB)

Browse Journals / Lookup Meetings

Browse by Journal and Year


Lookup Conference Papers

Close Browse Journals / Lookup Meetings

Article Tools



This paper reports the design and construction of a low-cost, multispectral imaging system using a single, large format CCD and an array of 18 individual lenses coupled to individual spectral filters. The system allows the simultaneous acquisition of 18 subimages, each with potentially different optical information. The subimages are combined to create a composite image, highlighting the desired spectral information. Because all the subimages are acquired simultaneously, the composite image shows no motion artifact. Although the present configuration uses 17 narrow bandpass optical filters to obtain multispectral information from a scene, the system is designed to be a general purpose, multiaperture platform, easily reconfigured for other multiaperture imaging modes.

© 2008 Optical Society of America

OCIS Codes
(040.1490) Detectors : Cameras
(040.1520) Detectors : CCD, charge-coupled device
(110.4234) Imaging systems : Multispectral and hyperspectral imaging

ToC Category:
Spectral Imaging Sensors

Original Manuscript: March 13, 2008
Revised Manuscript: June 5, 2008
Manuscript Accepted: June 27, 2008
Published: July 23, 2008

Scott A. Mathews, "Design and fabrication of a low-cost, multispectral imaging system," Appl. Opt. 47, F71-F76 (2008)

Sort:  Author  |  Year  |  Journal  |  Reset  


  1. J. A. Benediktsson, J. A. Palmason, and J. R. Sveinsson, “Classification of hyperspectral data from urban areas based on extended morphological profiles,” IEEE Trans. Geosci. Remote Sens. 43, 480-491 (2005). [CrossRef]
  2. D. G. Goodenough, J. Pearlman, H. Chen, A. Dyk, T. Han, J. Li, J. Miller, and K. O. Niemann, “Forest information from hyperspectral sensing,” in IEEE Proceedings on Geoscience and Remote Sensing (IEEE, 2004), Vol. 4, pp. 2585-2589.
  3. T. Vo-Dinh, “A hyperspectral imaging system for in vivo optical diagnostics,” IEEE Eng. Med. Biol. Magazine 23(5), 40-49 (2004). [CrossRef]
  4. J. A. Timlin, M. B. Sinclair, D. M. Haaland, J. Martinez, M. Manginell, S. M. Brozk, J. F. Guzowski, and M. Werner-Washburne, “Hyperspectral imaging of biological targets: the difference a high resolution spectral dimension and multivariate analysis can make,” in IEEE Symposium on Biomedical Imaging (IEEE, 2004), Vol. 2, pp. 1529-1532.
  5. C.-I. Chang, E. Sun, and M. L. G. Althouse, “An unsupervised interference rejection approach to target detection and classification for hyperspectral imagery,” Opt. Eng. 37, 735-743(1998). [CrossRef]
  6. H. Ren, Q. Du, J. Wang, C.-I. Chang, J. O. Jensen, and J. L. Jensen, “Automatic target recognition for hyperspectral imagery using high-order statistics,” IEEE Trans. Aerosp. Electron. Syst. 42, 1372-1385 (2006). [CrossRef]
  7. G. Themelis, J. S. Yoo, and V. Ntziachristos, “Multispectral imaging using multiple-bandpass filters,” Opt. Lett. 33, 1023-1025 (2008). [CrossRef] [PubMed]
  8. E. M. Winter, “Methods for determining best multispectral bands using hyperspectral data,” in IEEE Aerospace Conference (IEEE, 2007), pp. 1-6. [CrossRef]
  9. E. Hecht, “Familiar aspects of the interaction of light and matter,” in Optics, 4th ed. (Addison-Wesley, 2002), pp. 131-136.
  10. C. Boyce, A. Ross, M. Monaco, L. Hornak, and X. Li, “Multispectral iris analysis: a preliminary study,” in IEEE Conference on Computer Vision and Pattern Recognition (IEEE, 2006), pp. 51-51.
  11. M. J. Wabomba, Y. Sulub, and G. W. Small, “Remote detection of volatile organic compounds by passive multispectral infrared imaging measurements,” Appl. Spectrosc. 61, 349-358(2007). [CrossRef] [PubMed]
  12. A. Weisberg, M. Najarian, B. Borowski, J. Lisowski, and B. Miller, “Spectral angle automatic cluster routine (SAALT): an unsupervised multispectral clustering algorithm,” in IEEE Proceedings, Aerospace Conference 1999 (IEEE, 1999), pp. 307-317.
  13. J. R. Mansfield, M. G. Sowa, J. R. Payette, B. Abdulrauf, M. F. Stranc, and H. H. Mantsch, “Tissue viability by multispectral near infrared imaging: a Fuzzy C-Mean Clustering Analysis,” IEEE Trans. Med. Imaging 17, 1011-1018 (1998). [CrossRef]
  14. E. Preston, T. Begman, R. Gorenflo, D. Hermann, E. Kopala, T. Kuzma, L. Lazofson, and R. Orkis, “Development of a field-portable imaging system for scene classification using multispectral data fusion algorithms,” IEEE Aerosp. Electron. Syst. Mag. 9, 13-19 (1994). [CrossRef]
  15. R. Shogenji, Y. Kitamura, K. Yamada, S. Miyatake, and J. Tanida, “Multispectral imaging using compact compound optics,” Opt. Express 12, 1643-1655 (2004). [CrossRef] [PubMed]
  16. B. Zitová and J. Flusser, “Image registration methods: a survey,” Image Vision Comput. 21, 977-1000 (2003). [CrossRef]
  17. J. Batlle, J. Marti, P. Ridao, and J. Amat, “A new FPGA/DSP-based parallel architecture for real-time image processing,” Real-Time Imag. 8, 345-356 (2002). [CrossRef]
  18. J. C. Ramella-Roman and S. A. Mathews, “Spectroscopic measurement of oxygen saturation in the retina,” IEEE J. Sel. Top. Quantum Electron. 13, 1697-1703 (2007). [CrossRef]
  19. R. Barnard, V. P. Pauca, T. C. Torgersen, R. J. Plemmons, S. Prasad, J. van der Gracht, J. Nagy, J. Chung, G. Behrmann, S. Mathews, and M. Mirotznik, “High-resolution iris image reconstruction from low-resolution imagery,” Proc. SPIE 6313, D1-D13 (2006).

Cited By

Alert me when this paper is cited

OSA is able to provide readers links to articles that cite this paper by participating in CrossRef's Cited-By Linking service. CrossRef includes content from more than 3000 publishers and societies. In addition to listing OSA journal articles that cite this paper, citing articles from other participating publishers will also be listed.

« Previous Article  |  Next Article »

OSA is a member of CrossRef.

CrossCheck Deposited