Abstract

We consider the problem of acquiring models for unknown materials in airborne 0.4–2.5 μm hyperspectral imagery and using these models to identify the unknown materials in image data obtained under significantly different conditions. The material models are generated with use of an airborne sensor spectrum measured under unknown conditions and a physical model for spectral variability. For computational efficiency, the material models are represented by using low-dimensional spectral subspaces. We demonstrate the effectiveness of the material models by using a set of material tracking experiments in HYDICE images acquired in forest and desert environments over widely varying conditions. We show that techniques based on the new representation significantly outperform methods based on direct spectral matching.

© 2001 Optical Society of America

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References

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  1. P. Besl, R. Jain, “Three-dimensional object recognition,” ACM Comput. Surv. 17, 75–145 (1985).
    [Crossref]
  2. T. O. Binford, “Survey of model-based image analysis systems,” Int. J. Robot. Res. 1, 18–64 (1982).
    [Crossref]
  3. R. Chin, C. Dyer, “Model-based recognition in robot vision,” ACM Comp. Surv. 18, 67–108 (1986).
    [Crossref]
  4. A. K. Jain, P. J. Flynn, editors. Three-Dimensional Object Recognition Systems (Elsevier, Amsterdam, 1993).
  5. D. P. Huttenlocher, S. Ullman, “Recognizing solid objects by alignment,” Int. J. Comput. Vision 5, 195–212 (1990).
    [Crossref]
  6. D. Lowe, Perceptual Organization and Visual Recognition (Kluwer Academic, Norwell, Mass., 1985).
  7. W. E. L. Grimson, D. P. Huttenlocher, “On the sensitivity of the Hough transform for object recognition,” IEEE Trans. Pattern Anal. Mach. Intell. 12, 255–274 (1990).
    [Crossref]
  8. A. Pentland, “Perceptual organization and representation of natural form,” Artif. Intell. 28, 293–331 (1986).
    [Crossref]
  9. S. Dickinson, A. Pentland, A. Rosenfeld, “3-D shape recovery using distributed aspect matching,” IEEE Trans. Pattern Anal. Mach. Intell. 14, 174–198 (1992).
    [Crossref]
  10. M. Swain, D. Ballard, “Color indexing,” Int. J. Comput. Vision 7, 11–32 (1991).
    [Crossref]
  11. G. Healey, D. Slater, “Global color constancy: recognition of objects by use of illumination-invariant properties of color distributions,” J. Opt. Soc. Am. A 11, 3003–3010 (1994).
    [Crossref]
  12. G. Healey, D. Slater, “Computing illumination-invariant descriptors of spatially filtered color image regions,” IEEE Trans. Image Process. 6, 1002–1013 (1997).
    [Crossref] [PubMed]
  13. G. Healey, A. Jain, “Retrieving multispectral satellite images using physics-based invariant representations,” IEEE Trans. Pattern Anal. Mach. Intell. 18, 842–848 (1996).
    [Crossref]
  14. D. Judd, D. MacAdam, G. Wyszecki, “Spectral distribution of typical daylight as a function of correlated color temperature,” J. Opt. Soc. Am. 54, 1031–1040 (1964).
    [Crossref]
  15. D. Slater, G. Healey, “Analyzing the spectral dimensionality of outdoor visible and near-infrared illumination functions,” J. Opt. Soc. Am. A 15, 2913–2920 (1998).
    [Crossref]
  16. R. W. Basedow, D. C. Armer, M. E. Anderson, “HYDICE system: implementation and performance,” in Imaging Spectrometry, M. R. Descour, J. M. Mooney, D. L. Perry, L. R. Illing, eds., Proc. SPIE2480, 258–267 (1995).
    [Crossref]
  17. G. Vane, R. Green, T. Chrien, H. Enmark, E. Hansen, W. Porter, “The airborne visible infrared imaging spectrometer,” Remote Sens. Environ. 44, 127–143 (1993).
    [Crossref]
  18. C. G. Simi, S. G. Beaven, E. M. Winter, C. LaSota, J. Parish, R. Dixon, “Night vision imaging spectrometer (NVIS) performance parameters and their impact on various detection algorithms,” in Algorithms for Multispectral, Hyperspectral, and Ultraspectral Imagery VI, S. S. Shen, M. R. Descour, eds., Proc. SPIE4049, 218–229 (2000).
    [Crossref]
  19. G. Healey, D. Slater, “Models and methods for automated material identification in hyperspectral imagery acquired under unknown illumination and atmospheric conditions,” IEEE Trans. Geosci. Remote Sens. 37, 2706–2717 (1999).
    [Crossref]
  20. A. Berk, L. S. Bernstein, D. C. Robertson, “MODTRAN: a moderate resolution model for LOWTRAN 7,” (Geophysics Laboratory, Bedford, Mass.1989).
  21. J. R. Schott, Remote Sensing: The Image Chain Approach (Oxford U. Press, New York, 1997).
  22. Z. Pan, G. Healey, D. Slater, “Modeling the spectral variability of ground irradiance functions,” in Algorithms for Multispectral, Hyperspectral, and Ultraspectral Imagery VI, S. S. Shen, M. R. Descour, eds., Proc. SPIE4049, 82–93 (2000).
    [Crossref]
  23. G. H. Golub, C. F. van Loan, Matrix Computations (Johns HopkinsU. Press, Baltimore, Md., 1983).
  24. P. Suen, G. Healey, D. Slater, “Material identification over variation of scene conditions and viewing geometry,” in Algorithms for Multispectral, Hyperspectral, and Ultraspectral Imagery VI, S. S. Shen, M. R. Descour, eds., Proc. SPIE4049, 18–29 (2000).
    [Crossref]
  25. R. Duda, P. Hart, Pattern Classification and Scene Analysis (Wiley-Interscience, New York, 1973).
  26. F. A. Kruse, A. B. Lefkoff, J. W. Boardman, K. B. Heide-brecht, A. F. H. Goetz, “The spectral image processing system (SIPS)—interactive visualization and analysis of imaging spectrometer data,” Remote Sens. Environ. 44, 145–163 (1993).
    [Crossref]
  27. A. Leon-Garcia, Probability and Random Processes for Electrical Engineering, 2nd ed. (Addison-Wesley, Reading, Mass., 1994).

1999 (1)

G. Healey, D. Slater, “Models and methods for automated material identification in hyperspectral imagery acquired under unknown illumination and atmospheric conditions,” IEEE Trans. Geosci. Remote Sens. 37, 2706–2717 (1999).
[Crossref]

1998 (1)

1997 (1)

G. Healey, D. Slater, “Computing illumination-invariant descriptors of spatially filtered color image regions,” IEEE Trans. Image Process. 6, 1002–1013 (1997).
[Crossref] [PubMed]

1996 (1)

G. Healey, A. Jain, “Retrieving multispectral satellite images using physics-based invariant representations,” IEEE Trans. Pattern Anal. Mach. Intell. 18, 842–848 (1996).
[Crossref]

1994 (1)

1993 (2)

G. Vane, R. Green, T. Chrien, H. Enmark, E. Hansen, W. Porter, “The airborne visible infrared imaging spectrometer,” Remote Sens. Environ. 44, 127–143 (1993).
[Crossref]

F. A. Kruse, A. B. Lefkoff, J. W. Boardman, K. B. Heide-brecht, A. F. H. Goetz, “The spectral image processing system (SIPS)—interactive visualization and analysis of imaging spectrometer data,” Remote Sens. Environ. 44, 145–163 (1993).
[Crossref]

1992 (1)

S. Dickinson, A. Pentland, A. Rosenfeld, “3-D shape recovery using distributed aspect matching,” IEEE Trans. Pattern Anal. Mach. Intell. 14, 174–198 (1992).
[Crossref]

1991 (1)

M. Swain, D. Ballard, “Color indexing,” Int. J. Comput. Vision 7, 11–32 (1991).
[Crossref]

1990 (2)

D. P. Huttenlocher, S. Ullman, “Recognizing solid objects by alignment,” Int. J. Comput. Vision 5, 195–212 (1990).
[Crossref]

W. E. L. Grimson, D. P. Huttenlocher, “On the sensitivity of the Hough transform for object recognition,” IEEE Trans. Pattern Anal. Mach. Intell. 12, 255–274 (1990).
[Crossref]

1986 (2)

A. Pentland, “Perceptual organization and representation of natural form,” Artif. Intell. 28, 293–331 (1986).
[Crossref]

R. Chin, C. Dyer, “Model-based recognition in robot vision,” ACM Comp. Surv. 18, 67–108 (1986).
[Crossref]

1985 (1)

P. Besl, R. Jain, “Three-dimensional object recognition,” ACM Comput. Surv. 17, 75–145 (1985).
[Crossref]

1982 (1)

T. O. Binford, “Survey of model-based image analysis systems,” Int. J. Robot. Res. 1, 18–64 (1982).
[Crossref]

1964 (1)

Anderson, M. E.

R. W. Basedow, D. C. Armer, M. E. Anderson, “HYDICE system: implementation and performance,” in Imaging Spectrometry, M. R. Descour, J. M. Mooney, D. L. Perry, L. R. Illing, eds., Proc. SPIE2480, 258–267 (1995).
[Crossref]

Armer, D. C.

R. W. Basedow, D. C. Armer, M. E. Anderson, “HYDICE system: implementation and performance,” in Imaging Spectrometry, M. R. Descour, J. M. Mooney, D. L. Perry, L. R. Illing, eds., Proc. SPIE2480, 258–267 (1995).
[Crossref]

Ballard, D.

M. Swain, D. Ballard, “Color indexing,” Int. J. Comput. Vision 7, 11–32 (1991).
[Crossref]

Basedow, R. W.

R. W. Basedow, D. C. Armer, M. E. Anderson, “HYDICE system: implementation and performance,” in Imaging Spectrometry, M. R. Descour, J. M. Mooney, D. L. Perry, L. R. Illing, eds., Proc. SPIE2480, 258–267 (1995).
[Crossref]

Beaven, S. G.

C. G. Simi, S. G. Beaven, E. M. Winter, C. LaSota, J. Parish, R. Dixon, “Night vision imaging spectrometer (NVIS) performance parameters and their impact on various detection algorithms,” in Algorithms for Multispectral, Hyperspectral, and Ultraspectral Imagery VI, S. S. Shen, M. R. Descour, eds., Proc. SPIE4049, 218–229 (2000).
[Crossref]

Berk, A.

A. Berk, L. S. Bernstein, D. C. Robertson, “MODTRAN: a moderate resolution model for LOWTRAN 7,” (Geophysics Laboratory, Bedford, Mass.1989).

Bernstein, L. S.

A. Berk, L. S. Bernstein, D. C. Robertson, “MODTRAN: a moderate resolution model for LOWTRAN 7,” (Geophysics Laboratory, Bedford, Mass.1989).

Besl, P.

P. Besl, R. Jain, “Three-dimensional object recognition,” ACM Comput. Surv. 17, 75–145 (1985).
[Crossref]

Binford, T. O.

T. O. Binford, “Survey of model-based image analysis systems,” Int. J. Robot. Res. 1, 18–64 (1982).
[Crossref]

Boardman, J. W.

F. A. Kruse, A. B. Lefkoff, J. W. Boardman, K. B. Heide-brecht, A. F. H. Goetz, “The spectral image processing system (SIPS)—interactive visualization and analysis of imaging spectrometer data,” Remote Sens. Environ. 44, 145–163 (1993).
[Crossref]

Chin, R.

R. Chin, C. Dyer, “Model-based recognition in robot vision,” ACM Comp. Surv. 18, 67–108 (1986).
[Crossref]

Chrien, T.

G. Vane, R. Green, T. Chrien, H. Enmark, E. Hansen, W. Porter, “The airborne visible infrared imaging spectrometer,” Remote Sens. Environ. 44, 127–143 (1993).
[Crossref]

Dickinson, S.

S. Dickinson, A. Pentland, A. Rosenfeld, “3-D shape recovery using distributed aspect matching,” IEEE Trans. Pattern Anal. Mach. Intell. 14, 174–198 (1992).
[Crossref]

Dixon, R.

C. G. Simi, S. G. Beaven, E. M. Winter, C. LaSota, J. Parish, R. Dixon, “Night vision imaging spectrometer (NVIS) performance parameters and their impact on various detection algorithms,” in Algorithms for Multispectral, Hyperspectral, and Ultraspectral Imagery VI, S. S. Shen, M. R. Descour, eds., Proc. SPIE4049, 218–229 (2000).
[Crossref]

Duda, R.

R. Duda, P. Hart, Pattern Classification and Scene Analysis (Wiley-Interscience, New York, 1973).

Dyer, C.

R. Chin, C. Dyer, “Model-based recognition in robot vision,” ACM Comp. Surv. 18, 67–108 (1986).
[Crossref]

Enmark, H.

G. Vane, R. Green, T. Chrien, H. Enmark, E. Hansen, W. Porter, “The airborne visible infrared imaging spectrometer,” Remote Sens. Environ. 44, 127–143 (1993).
[Crossref]

Goetz, A. F. H.

F. A. Kruse, A. B. Lefkoff, J. W. Boardman, K. B. Heide-brecht, A. F. H. Goetz, “The spectral image processing system (SIPS)—interactive visualization and analysis of imaging spectrometer data,” Remote Sens. Environ. 44, 145–163 (1993).
[Crossref]

Golub, G. H.

G. H. Golub, C. F. van Loan, Matrix Computations (Johns HopkinsU. Press, Baltimore, Md., 1983).

Green, R.

G. Vane, R. Green, T. Chrien, H. Enmark, E. Hansen, W. Porter, “The airborne visible infrared imaging spectrometer,” Remote Sens. Environ. 44, 127–143 (1993).
[Crossref]

Grimson, W. E. L.

W. E. L. Grimson, D. P. Huttenlocher, “On the sensitivity of the Hough transform for object recognition,” IEEE Trans. Pattern Anal. Mach. Intell. 12, 255–274 (1990).
[Crossref]

Hansen, E.

G. Vane, R. Green, T. Chrien, H. Enmark, E. Hansen, W. Porter, “The airborne visible infrared imaging spectrometer,” Remote Sens. Environ. 44, 127–143 (1993).
[Crossref]

Hart, P.

R. Duda, P. Hart, Pattern Classification and Scene Analysis (Wiley-Interscience, New York, 1973).

Healey, G.

G. Healey, D. Slater, “Models and methods for automated material identification in hyperspectral imagery acquired under unknown illumination and atmospheric conditions,” IEEE Trans. Geosci. Remote Sens. 37, 2706–2717 (1999).
[Crossref]

D. Slater, G. Healey, “Analyzing the spectral dimensionality of outdoor visible and near-infrared illumination functions,” J. Opt. Soc. Am. A 15, 2913–2920 (1998).
[Crossref]

G. Healey, D. Slater, “Computing illumination-invariant descriptors of spatially filtered color image regions,” IEEE Trans. Image Process. 6, 1002–1013 (1997).
[Crossref] [PubMed]

G. Healey, A. Jain, “Retrieving multispectral satellite images using physics-based invariant representations,” IEEE Trans. Pattern Anal. Mach. Intell. 18, 842–848 (1996).
[Crossref]

G. Healey, D. Slater, “Global color constancy: recognition of objects by use of illumination-invariant properties of color distributions,” J. Opt. Soc. Am. A 11, 3003–3010 (1994).
[Crossref]

Z. Pan, G. Healey, D. Slater, “Modeling the spectral variability of ground irradiance functions,” in Algorithms for Multispectral, Hyperspectral, and Ultraspectral Imagery VI, S. S. Shen, M. R. Descour, eds., Proc. SPIE4049, 82–93 (2000).
[Crossref]

P. Suen, G. Healey, D. Slater, “Material identification over variation of scene conditions and viewing geometry,” in Algorithms for Multispectral, Hyperspectral, and Ultraspectral Imagery VI, S. S. Shen, M. R. Descour, eds., Proc. SPIE4049, 18–29 (2000).
[Crossref]

Heide-brecht, K. B.

F. A. Kruse, A. B. Lefkoff, J. W. Boardman, K. B. Heide-brecht, A. F. H. Goetz, “The spectral image processing system (SIPS)—interactive visualization and analysis of imaging spectrometer data,” Remote Sens. Environ. 44, 145–163 (1993).
[Crossref]

Huttenlocher, D. P.

W. E. L. Grimson, D. P. Huttenlocher, “On the sensitivity of the Hough transform for object recognition,” IEEE Trans. Pattern Anal. Mach. Intell. 12, 255–274 (1990).
[Crossref]

D. P. Huttenlocher, S. Ullman, “Recognizing solid objects by alignment,” Int. J. Comput. Vision 5, 195–212 (1990).
[Crossref]

Jain, A.

G. Healey, A. Jain, “Retrieving multispectral satellite images using physics-based invariant representations,” IEEE Trans. Pattern Anal. Mach. Intell. 18, 842–848 (1996).
[Crossref]

Jain, R.

P. Besl, R. Jain, “Three-dimensional object recognition,” ACM Comput. Surv. 17, 75–145 (1985).
[Crossref]

Judd, D.

Kruse, F. A.

F. A. Kruse, A. B. Lefkoff, J. W. Boardman, K. B. Heide-brecht, A. F. H. Goetz, “The spectral image processing system (SIPS)—interactive visualization and analysis of imaging spectrometer data,” Remote Sens. Environ. 44, 145–163 (1993).
[Crossref]

LaSota, C.

C. G. Simi, S. G. Beaven, E. M. Winter, C. LaSota, J. Parish, R. Dixon, “Night vision imaging spectrometer (NVIS) performance parameters and their impact on various detection algorithms,” in Algorithms for Multispectral, Hyperspectral, and Ultraspectral Imagery VI, S. S. Shen, M. R. Descour, eds., Proc. SPIE4049, 218–229 (2000).
[Crossref]

Lefkoff, A. B.

F. A. Kruse, A. B. Lefkoff, J. W. Boardman, K. B. Heide-brecht, A. F. H. Goetz, “The spectral image processing system (SIPS)—interactive visualization and analysis of imaging spectrometer data,” Remote Sens. Environ. 44, 145–163 (1993).
[Crossref]

Leon-Garcia, A.

A. Leon-Garcia, Probability and Random Processes for Electrical Engineering, 2nd ed. (Addison-Wesley, Reading, Mass., 1994).

Lowe, D.

D. Lowe, Perceptual Organization and Visual Recognition (Kluwer Academic, Norwell, Mass., 1985).

MacAdam, D.

Pan, Z.

Z. Pan, G. Healey, D. Slater, “Modeling the spectral variability of ground irradiance functions,” in Algorithms for Multispectral, Hyperspectral, and Ultraspectral Imagery VI, S. S. Shen, M. R. Descour, eds., Proc. SPIE4049, 82–93 (2000).
[Crossref]

Parish, J.

C. G. Simi, S. G. Beaven, E. M. Winter, C. LaSota, J. Parish, R. Dixon, “Night vision imaging spectrometer (NVIS) performance parameters and their impact on various detection algorithms,” in Algorithms for Multispectral, Hyperspectral, and Ultraspectral Imagery VI, S. S. Shen, M. R. Descour, eds., Proc. SPIE4049, 218–229 (2000).
[Crossref]

Pentland, A.

S. Dickinson, A. Pentland, A. Rosenfeld, “3-D shape recovery using distributed aspect matching,” IEEE Trans. Pattern Anal. Mach. Intell. 14, 174–198 (1992).
[Crossref]

A. Pentland, “Perceptual organization and representation of natural form,” Artif. Intell. 28, 293–331 (1986).
[Crossref]

Porter, W.

G. Vane, R. Green, T. Chrien, H. Enmark, E. Hansen, W. Porter, “The airborne visible infrared imaging spectrometer,” Remote Sens. Environ. 44, 127–143 (1993).
[Crossref]

Robertson, D. C.

A. Berk, L. S. Bernstein, D. C. Robertson, “MODTRAN: a moderate resolution model for LOWTRAN 7,” (Geophysics Laboratory, Bedford, Mass.1989).

Rosenfeld, A.

S. Dickinson, A. Pentland, A. Rosenfeld, “3-D shape recovery using distributed aspect matching,” IEEE Trans. Pattern Anal. Mach. Intell. 14, 174–198 (1992).
[Crossref]

Schott, J. R.

J. R. Schott, Remote Sensing: The Image Chain Approach (Oxford U. Press, New York, 1997).

Simi, C. G.

C. G. Simi, S. G. Beaven, E. M. Winter, C. LaSota, J. Parish, R. Dixon, “Night vision imaging spectrometer (NVIS) performance parameters and their impact on various detection algorithms,” in Algorithms for Multispectral, Hyperspectral, and Ultraspectral Imagery VI, S. S. Shen, M. R. Descour, eds., Proc. SPIE4049, 218–229 (2000).
[Crossref]

Slater, D.

G. Healey, D. Slater, “Models and methods for automated material identification in hyperspectral imagery acquired under unknown illumination and atmospheric conditions,” IEEE Trans. Geosci. Remote Sens. 37, 2706–2717 (1999).
[Crossref]

D. Slater, G. Healey, “Analyzing the spectral dimensionality of outdoor visible and near-infrared illumination functions,” J. Opt. Soc. Am. A 15, 2913–2920 (1998).
[Crossref]

G. Healey, D. Slater, “Computing illumination-invariant descriptors of spatially filtered color image regions,” IEEE Trans. Image Process. 6, 1002–1013 (1997).
[Crossref] [PubMed]

G. Healey, D. Slater, “Global color constancy: recognition of objects by use of illumination-invariant properties of color distributions,” J. Opt. Soc. Am. A 11, 3003–3010 (1994).
[Crossref]

Z. Pan, G. Healey, D. Slater, “Modeling the spectral variability of ground irradiance functions,” in Algorithms for Multispectral, Hyperspectral, and Ultraspectral Imagery VI, S. S. Shen, M. R. Descour, eds., Proc. SPIE4049, 82–93 (2000).
[Crossref]

P. Suen, G. Healey, D. Slater, “Material identification over variation of scene conditions and viewing geometry,” in Algorithms for Multispectral, Hyperspectral, and Ultraspectral Imagery VI, S. S. Shen, M. R. Descour, eds., Proc. SPIE4049, 18–29 (2000).
[Crossref]

Suen, P.

P. Suen, G. Healey, D. Slater, “Material identification over variation of scene conditions and viewing geometry,” in Algorithms for Multispectral, Hyperspectral, and Ultraspectral Imagery VI, S. S. Shen, M. R. Descour, eds., Proc. SPIE4049, 18–29 (2000).
[Crossref]

Swain, M.

M. Swain, D. Ballard, “Color indexing,” Int. J. Comput. Vision 7, 11–32 (1991).
[Crossref]

Ullman, S.

D. P. Huttenlocher, S. Ullman, “Recognizing solid objects by alignment,” Int. J. Comput. Vision 5, 195–212 (1990).
[Crossref]

van Loan, C. F.

G. H. Golub, C. F. van Loan, Matrix Computations (Johns HopkinsU. Press, Baltimore, Md., 1983).

Vane, G.

G. Vane, R. Green, T. Chrien, H. Enmark, E. Hansen, W. Porter, “The airborne visible infrared imaging spectrometer,” Remote Sens. Environ. 44, 127–143 (1993).
[Crossref]

Winter, E. M.

C. G. Simi, S. G. Beaven, E. M. Winter, C. LaSota, J. Parish, R. Dixon, “Night vision imaging spectrometer (NVIS) performance parameters and their impact on various detection algorithms,” in Algorithms for Multispectral, Hyperspectral, and Ultraspectral Imagery VI, S. S. Shen, M. R. Descour, eds., Proc. SPIE4049, 218–229 (2000).
[Crossref]

Wyszecki, G.

ACM Comp. Surv. (1)

R. Chin, C. Dyer, “Model-based recognition in robot vision,” ACM Comp. Surv. 18, 67–108 (1986).
[Crossref]

ACM Comput. Surv. (1)

P. Besl, R. Jain, “Three-dimensional object recognition,” ACM Comput. Surv. 17, 75–145 (1985).
[Crossref]

Artif. Intell. (1)

A. Pentland, “Perceptual organization and representation of natural form,” Artif. Intell. 28, 293–331 (1986).
[Crossref]

IEEE Trans. Geosci. Remote Sens. (1)

G. Healey, D. Slater, “Models and methods for automated material identification in hyperspectral imagery acquired under unknown illumination and atmospheric conditions,” IEEE Trans. Geosci. Remote Sens. 37, 2706–2717 (1999).
[Crossref]

IEEE Trans. Image Process. (1)

G. Healey, D. Slater, “Computing illumination-invariant descriptors of spatially filtered color image regions,” IEEE Trans. Image Process. 6, 1002–1013 (1997).
[Crossref] [PubMed]

IEEE Trans. Pattern Anal. Mach. Intell. (3)

G. Healey, A. Jain, “Retrieving multispectral satellite images using physics-based invariant representations,” IEEE Trans. Pattern Anal. Mach. Intell. 18, 842–848 (1996).
[Crossref]

S. Dickinson, A. Pentland, A. Rosenfeld, “3-D shape recovery using distributed aspect matching,” IEEE Trans. Pattern Anal. Mach. Intell. 14, 174–198 (1992).
[Crossref]

W. E. L. Grimson, D. P. Huttenlocher, “On the sensitivity of the Hough transform for object recognition,” IEEE Trans. Pattern Anal. Mach. Intell. 12, 255–274 (1990).
[Crossref]

Int. J. Comput. Vision (2)

M. Swain, D. Ballard, “Color indexing,” Int. J. Comput. Vision 7, 11–32 (1991).
[Crossref]

D. P. Huttenlocher, S. Ullman, “Recognizing solid objects by alignment,” Int. J. Comput. Vision 5, 195–212 (1990).
[Crossref]

Int. J. Robot. Res. (1)

T. O. Binford, “Survey of model-based image analysis systems,” Int. J. Robot. Res. 1, 18–64 (1982).
[Crossref]

J. Opt. Soc. Am. (1)

J. Opt. Soc. Am. A (2)

Remote Sens. Environ. (2)

G. Vane, R. Green, T. Chrien, H. Enmark, E. Hansen, W. Porter, “The airborne visible infrared imaging spectrometer,” Remote Sens. Environ. 44, 127–143 (1993).
[Crossref]

F. A. Kruse, A. B. Lefkoff, J. W. Boardman, K. B. Heide-brecht, A. F. H. Goetz, “The spectral image processing system (SIPS)—interactive visualization and analysis of imaging spectrometer data,” Remote Sens. Environ. 44, 145–163 (1993).
[Crossref]

Other (11)

A. Leon-Garcia, Probability and Random Processes for Electrical Engineering, 2nd ed. (Addison-Wesley, Reading, Mass., 1994).

A. Berk, L. S. Bernstein, D. C. Robertson, “MODTRAN: a moderate resolution model for LOWTRAN 7,” (Geophysics Laboratory, Bedford, Mass.1989).

J. R. Schott, Remote Sensing: The Image Chain Approach (Oxford U. Press, New York, 1997).

Z. Pan, G. Healey, D. Slater, “Modeling the spectral variability of ground irradiance functions,” in Algorithms for Multispectral, Hyperspectral, and Ultraspectral Imagery VI, S. S. Shen, M. R. Descour, eds., Proc. SPIE4049, 82–93 (2000).
[Crossref]

G. H. Golub, C. F. van Loan, Matrix Computations (Johns HopkinsU. Press, Baltimore, Md., 1983).

P. Suen, G. Healey, D. Slater, “Material identification over variation of scene conditions and viewing geometry,” in Algorithms for Multispectral, Hyperspectral, and Ultraspectral Imagery VI, S. S. Shen, M. R. Descour, eds., Proc. SPIE4049, 18–29 (2000).
[Crossref]

R. Duda, P. Hart, Pattern Classification and Scene Analysis (Wiley-Interscience, New York, 1973).

C. G. Simi, S. G. Beaven, E. M. Winter, C. LaSota, J. Parish, R. Dixon, “Night vision imaging spectrometer (NVIS) performance parameters and their impact on various detection algorithms,” in Algorithms for Multispectral, Hyperspectral, and Ultraspectral Imagery VI, S. S. Shen, M. R. Descour, eds., Proc. SPIE4049, 218–229 (2000).
[Crossref]

D. Lowe, Perceptual Organization and Visual Recognition (Kluwer Academic, Norwell, Mass., 1985).

R. W. Basedow, D. C. Armer, M. E. Anderson, “HYDICE system: implementation and performance,” in Imaging Spectrometry, M. R. Descour, J. M. Mooney, D. L. Perry, L. R. Illing, eds., Proc. SPIE2480, 258–267 (1995).
[Crossref]

A. K. Jain, P. J. Flynn, editors. Three-Dimensional Object Recognition Systems (Elsevier, Amsterdam, 1993).

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Figures (11)

Fig. 1
Fig. 1

Imaging geometry.

Fig. 2
Fig. 2

Ground spectra I(λ) measured at different times in Boulder in summer 1997.

Fig. 3
Fig. 3

Maximum error as a function of subspace dimension.

Fig. 4
Fig. 4

ROC curves for exposed panels.

Fig. 5
Fig. 5

ROC curves for shaded panels.

Fig. 6
Fig. 6

ROC curves for concealed panels.

Fig. 7
Fig. 7

Results for forest scene 1: (a) invariant algorithm, (b) SAM algorithm.

Fig. 8
Fig. 8

Results for forest scene 2: (a) invariant algorithm, (b) SAM algorithm.

Fig. 9
Fig. 9

Results for forest scene 3: (a) invariant algorithm, (b) SAM algorithm.

Fig. 10
Fig. 10

Results for desert scene 1: (a) invariant algorithm, (b) SAM algorithm.

Fig. 11
Fig. 11

Results for desert scene 2: (a) invariant algorithm, (b) SAM algorithm.

Tables (2)

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Table 1 Range of Conditions for Spectral Modeling

Tables Icon

Table 2 Summary of HYDICE Scenes

Equations (10)

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L(x, y, λ)=Tu(λ)I(λ)R(x, y, λ)+P(λ),
I(λ)=Td(λ)KEo(λ)cos(α)+Es(θ, ϕ, λ)cos(θ)sin(θ)dθdϕ,
L(λ)=D(λ)R(λ)+P(λ),
L(λ)=D(λ)R(λ)+P(λ),
L(λ)=D(λ)D(λ) [L(λ)-P(λ)]+P(λ).
Lij=1Naijmj,1iC2,
E(N)=i=1C2Li-j=1Naijmj2
E(N)=E(N)i=1C2Li2.
D=L-i=1N(Lmi)mi,
arccosLL˜|L||L˜|.

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