OSA's Digital Library

Applied Optics

Applied Optics


  • Editor: James C. Wyant
  • Vol. 47, Iss. 28 — Oct. 1, 2008
  • pp: F61–F70

Automated target detection system for hyperspectral imaging sensors

Marc A. Kolodner  »View Author Affiliations

Applied Optics, Vol. 47, Issue 28, pp. F61-F70 (2008)

View Full Text Article

Enhanced HTML    Acrobat PDF (2380 KB)

Browse Journals / Lookup Meetings

Browse by Journal and Year


Lookup Conference Papers

Close Browse Journals / Lookup Meetings

Article Tools



Over the past several years, hyperspectral sensor technology has evolved to the point where real-time processing for operational applications is achievable. Algorithms supporting such sensors must be fully automated and robust. Our approach, for target detection applications, is to select signatures from a target reflectance library database and project them to the at-sensor and collection-specific radiance domain using the weather forecast or radiosonde data. This enables platform-based detection immediately following data acquisition without the need for further atmospheric compensation. One advantage of this method for reflective hyperspectral sensors is the ability to predict the radiance signatures of targets under multiple illumination conditions. A three-phase approach is implemented, where the library generation and data acquisition phases provide the necessary input for the automated detection phase. In addition to employing the target detector itself, this final phase includes a series of automated filters, adaptive thresholding, and confidence assignments to extract the optimal information from the detection scores for each spectral class. Our prototype software is applied to 50 reflective hyperspectral datacubes to measure detection performance over a range of targets, backgrounds, and environmental conditions.

© 2008 Optical Society of America

OCIS Codes
(100.4145) Image processing : Motion, hyperspectral image processing
(010.5620) Atmospheric and oceanic optics : Radiative transfer

ToC Category:

Original Manuscript: March 3, 2008
Revised Manuscript: April 14, 2008
Manuscript Accepted: June 27, 2008
Published: July 18, 2008

Marc A. Kolodner, "Automated target detection system for hyperspectral imaging sensors," Appl. Opt. 47, F61-F70 (2008)

Sort:  Author  |  Year  |  Journal  |  Reset  


  1. S. Kraut, L. L. Scharf, and L. T. McWhorter, “Adaptive subspace detectors,” IEEE Trans. Signal Process. 49, 1-16 (2001). [CrossRef]
  2. D. G. Manolakis and G. A. Shaw, “Detection algorithms for hyperspectral imaging applications,” IEEE Signal Process. Mag. 19, 29-43 (2002). [CrossRef]
  3. B. Thai and G. E. Healey, “Invariant subpixel material detection in hyperspectral imagery,” IEEE Trans. Geosci. Remote Sens. 40, 599-608 (2002). [CrossRef]
  4. C. M. Stellman, G. G. Hazel, F. Bucholtz, J. V. Michalowicz, A. D. Stocker, and W. E. Schaff, “Real time hyperspectral target detection and cuing,” Opt. Eng. 39, 1928-1935 (2000). [CrossRef]
  5. C. G. Simi, E. M. Winter, M. J. Schlangen, and A. B. Hill, “On-board processing for COMPASS,” Proc. SPIE 4381, 137-142 (2001). [CrossRef]
  6. B. P. Stevenson, R. O'Connor, W. B. Kendall, A. D. Stocker, W. E. Schaff, D. Alexa, J. A. Salvador, M. T. Eismann, K. J. Barnard, and J. C. Kershenstein, “Design and performance of the Civil Air Patrol ARCHER Hyperspectral Processing System,” Proc. SPIE 5806, 731-742 (2005). [CrossRef]
  7. T. Cooley, G. P. Anderson, G. W. Felde, M. L. Hoke, A. J. Ratkowski, J. H. Chetwynd, J. A. Gardner, S. M. Adler-Golden, M. W. Matthew, A. Berk, L. S. Bernstein, P. K. Acharya, D. Miller, and P. Lewis, “FLAASH, a MODTRAN4-based atmospheric correction algorithm, its application and validation,” in 2002 IEEE International Geoscience and Remote Sensing Symposium (IEEE, 2002), Vol. 3, pp. 1414-1418.
  8. “Atmospheric Correction Now (ACORN) user's guide,” Advanced Imaging and Spectroscopy LLC, http://www.imspec.com.
  9. “Atmospheric Correction (ATCOR) user's guide,” Geosystems Germany, http://www.geosystems.de/atcor.
  10. G. Vane, R. O. Green, T. G. Chrien, H. T. Enmark, E. G. Hansen, and W. M. Porter, “The Airborne Visible Infrared Imaging Spectrometer,” Remote Sens. Environ. 44, 127-143 (1993). [CrossRef]
  11. R. W. Basedow, D. C. Carmer, and M. E. Anderson, “HYDICE system: implementation and performance,” Proc. SPIE 2480, 258-267 (1995). [CrossRef]
  12. C. G. Simi, E. M. Winter, M. M. Williams, and D. C. Driscoll, “Compact Airborne Spectral Sensor (COMPASS),” Proc. SPIE 4381, 129-136 (2001). [CrossRef]
  13. J. A. Hackwell, D. W. Warren, R. P. Bongiovi, S. J. Hansel, T. L. Hayhurst, D. L. Mabry, M. G. Sivjee, and J. W. Skinner, “LWIR/MWIR imaging hyperspectral sensor for airborne and ground-based remote sensing,” Proc. SPIE 2819, 102-107 (1996). [CrossRef]
  14. “Environment for Visualizing Images (ENVI) user's guide,” ITT Visual Information Solutions, Boulder, Colorado, http://www.ittvis.com.
  15. J. Dudhia, D. O. Gill, K. W. Manning, W. Wang, and C. Bruyere, “PSU/NCAR Mesoscale Modeling System tutorial class notes and user's guide (MM5 Modeling System Version 3),” University Corporation for Atmospheric Research (UCAR), http://www.mmm.ucar.edu/mm5/documents/tutorial-v3-notes.html(2005).
  16. “Radiosonde Database Access,” Forecast Systems Laboratory, National Oceanic and Atmospheric Administration (NOAA), Boulder, Colorado, http://raob.fsl.noaa.gov.
  17. G. P. Anderson, A. Berk, P. K. Acharya, M. W. Matthew, L. S. Bernstein, J. H. Chetwynd Jr., H. Dothe, S. M. Adler-Golden, A. J. Ratkowski, G. W. Felde, J. A. Gardner, M. L. Hoke, S. C. Richtsmeier, B. Pukall, J. B. Mello, and L. S. Jeong, “MODTRAN4: radiative transfer modeling for remote sensing,” Proc. SPIE 4049, 176-183 (2000). [CrossRef]
  18. T. S. Spisz, Y. Fang, R. H. Reeves, C. K. Seymour, I. N. Bankman, and J. H. Hoh, “Automated sizing of DNA fragments in atomic force microscope images,” Med. Biol. Eng. Comput. 36, 667-672 (1998). [CrossRef]
  19. A. Banerjee, P. Burlina, and C. P. Diehl, “A support vector method for anomaly detection in hyperspectral imagery,” IEEE Trans. Geosci. Remote Sens. 44, 2282-2291 (2006). [CrossRef]
  20. M. A. Kolodner, P. K. Murphy, and E. E. Hume, Jr., “Radiance library forecasting for time-critical hyperspectral target detection systems,” U.S. patent 7,043,369 (9 May 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