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Affine Illumination Compensation on Hyperspectral/Multiangular Remote Sensing Images

  • Pedro Latorre Carmona
  • Luis Alonso
  • Filiberto Pla
  • Jose E. Moreno
  • Crystal Schaaf
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6754)

Abstract

The huge amount of information some of the new optical satellites developed nowadays will create demands to quickly and reliably compensate for changes in the atmospheric transmittance and varying solar illumination conditions. In this paper three different forms of affine transformation models (general, particular and diagonal) are considered as candidates for rapid compensation of illumination variations. They are tested on a group of three pairs of CHRIS-PROBA radiance images obtained in a test field in Barrax (Spain), and where there is a difference in the atmospheric as well as in the geometrical acquisition conditions. Results indicate that the proposed methodology is satisfactory for practical normalization of varying illumination and atmospheric conditions in remotely sensed images required for operational applications.

Keywords

Affine illumination compensation hyperspectral/multiangular images 

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References

  1. 1.
    Kuan, C.Y., Healey, G.: Retrieving multispectral satellite images using physics-based invariant representations. IEEE Trans. on Pat. Analysis and Mach. Intel. 18, 842–848 (1996)CrossRefGoogle Scholar
  2. 2.
    Kuan, C.Y., Healey, G.: Using spatial filtering to improve spectral distribution invariants. In: Proc. SPIE, vol. 6233, pp. 62330G1–62330G12 (2006)Google Scholar
  3. 3.
    Finlayson, G.D., Drew, M.S., Funt, B.V.: Spectral sharpening: sensor transformations for improved color constancy. Journal of the Opt. Soc. of America, A 11, 1553–1563 (1994)CrossRefGoogle Scholar
  4. 4.
    Wyszecki, G., Stiles, W.S.: Color Science: concepts and methods. Wiley, Chichester (2000)Google Scholar
  5. 5.
    Lenz, R., Tran, L.V., Meer, P.: Moment based normalization of color images. In: IEEE 3rd Workshop on Multimedia Signal Processing, pp. 103–108 (1998)Google Scholar
  6. 6.
    Finlayson, G., Chatterjee, S.S., Funt, B.V.: Color Angular Indexing. In: Buxton, B.F., Cipolla, R. (eds.) ECCV 1996. LNCS, vol. 1065, pp. 16–27. Springer, Heidelberg (1996)CrossRefGoogle Scholar
  7. 7.
    Vermote, E.F., Tanré, D., Deuzé, J.L., Herman, M., Morcrette, J.J.: Second Simulation of the Satellite Signal in the Solar Spectrum: an overview. IEEE TGARS 35, 675–686 (1997)Google Scholar
  8. 8.
    ”SEN2FLEX Data Acquisition Report” Project Contract No. 19187/05/I-EC (2005)Google Scholar
  9. 9.
    Heikkila, J.: Pattern Matching with Affine Moment Descriptors. Pattern Recognition 37, 1825–1834 (2004)CrossRefzbMATHGoogle Scholar
  10. 10.
    Sprinzak, J., Werman, M.: Affine Point Matching. Pat. Rec. Letters 15, 337–339 (1994)CrossRefGoogle Scholar
  11. 11.
    Schonemann, P.H.: A generalized solution of the orthogonal Procrustes problem. Psychometrika 31, 1–10 (1966)MathSciNetCrossRefzbMATHGoogle Scholar
  12. 12.
    Varah, J.M.: On the numerical solution of ill-conditioned linear systems with applications to ill-posed problems. SIAM Journal on Numerical Analysis 10, 257–267 (1973)MathSciNetCrossRefzbMATHGoogle Scholar
  13. 13.
    Espen, P.V.: Spectrum evaluation. In: Handbook of X-Ray Spectr., Marcel Dekker, New York (2001)Google Scholar
  14. 14.
    Gascon, F., Berger, M.: GMES Sentinel-2 Mission requirements document, T.R., European Space Agency (2007)Google Scholar
  15. 15.
    Weiss, S.: Measurement data deffinition and format description for MERIS. T.R. Astrium GmbH (2001)Google Scholar
  16. 16.
    Latorre Carmona, P., Lenz, R., Pla, F., Sotoca, J.M.: Affine Illumination Compensation for Multispectral Images. In: Ersbøll, B.K., Pedersen, K.S. (eds.) SCIA 2007. LNCS, vol. 4522, pp. 522–531. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  17. 17.
    Latorre Carmona, P., Moreno, J.E., Pla, F., Schaaf, C.B.: Affine Compensation of Illumination in Hyperspectral Remote Sensing Images. In: IEEE IGARSS (2009)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Pedro Latorre Carmona
    • 1
  • Luis Alonso
    • 2
  • Filiberto Pla
    • 1
  • Jose E. Moreno
    • 2
  • Crystal Schaaf
    • 3
  1. 1.Dept. Lenguajes y Sistemas InformáticosJaume I UniversitySpain
  2. 2.Departamento de Física de la Tierra y TermodinámicaUniversidad de ValenciaSpain
  3. 3.Department of Geography and Environment, Center for Remote SensingBoston UniversityUSA

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