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A Generalized Appriou’s Model for Evidential Classification of Multispectral Images: A Case Study of Algiers City

  • Abdenour Bouakache
  • Radja Khedam
  • Aichouche Belhadj-Aissa
  • Grégoire Mercier
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5259)

Abstract

In this paper, we shall describe an evidential supervised classifier of multispectral satellite images. The evidence theory of Dempster-Shafer (DST) is used to take into account the ignorance and the uncertainty related to data, and so, overcome the Bayesian classifier limits. Notice that application fields of DST are initially related on multisensor, multitemporal and multiscale data fusion. In this study, our contribution lies in developing an evidential classification process that can be seen as a multisource fusion process where each predefined thematic class is considered as one source of information. The evidential mass functions of the considered thematic hypotheses are estimated using Appriou’s transfer model whose we propose to generalize to a multi-class case. Developed DST-classifier has been tested on multispectral ETM+ image covering the urban north-eastern part of Algiers (Algeria). The spectral validation of obtained evidential classes allows us to confirm the accuracy of the resulting land cover map.

Keywords

Bare Soil Mass Function Multispectral Image Belief Function Evidence Theory 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. 1.
    Appriou, A.: Probabilités et incertitude en fusion de données multi-senseurs. Revue Scientifique et Technique de la Défense 11, 27–40 (1991)Google Scholar
  2. 2.
    Appriou, A.: Multisensor signal processing in the framework of the theory of evidence. In: NATO/RTO, Application of Mathematical Signal Processing Techniques to Mission Systems. ONERA, Toulouse, France (1999)Google Scholar
  3. 3.
    Bendjabour, A., Pieczenski, W.: Unsupervised Image Segmentation Using Dempster-Shafer Fusion in a Markov Fields Context. In: First International Conference on Multisource-Multisensor Information Fusion, Las Vegas, Nevada, USA, pp. 595–600 (1998)Google Scholar
  4. 4.
    Bloch, I.: Information Combination Operators for Data Fusion: A comparative review with classification. IEEE, Trans. Sys. Man Cybern. A 26, 52–67 (1996)CrossRefGoogle Scholar
  5. 5.
    Bloch, I.: Fusion d’informations en traitement du signal et des images. Edition Hermès Science, Paris, France, p. 319 (2003)Google Scholar
  6. 6.
    Celleux, G., Diday, E., Govaert, G., Lechevallier, Y., Ralambondrainy, H.: Classification automatique des données. Editions Dunod Informatique, Paris, France (1989)Google Scholar
  7. 7.
    Chatalic, P.: Raisonnement déductif en présence de connaissances imprécises et incertaines: Un système basé sur la théorie de Dempster-Shafer. Thèse Phd, Université Paul Sabatier, Toulouse, France, p. 357 (1986)Google Scholar
  8. 8.
    Dempster, A.P.: Upper and lower probabilities induced by a multivalued mapping. Annals of Mathematical Statistics 38(2), 325–339 (1967)MathSciNetCrossRefzbMATHGoogle Scholar
  9. 9.
    Denoeux, T.: Analysis of evidence-theoretic decision rules for pattern classification. Pattern Recognition 30(7), 1095–1107 (1997)CrossRefGoogle Scholar
  10. 10.
    Dubois, D., Prade, H.: A Set-Theoretic View on Belief Functions: Logical Operations and Approximations by Fuzzy Sets. International Journal of General Systems 12, 193–226 (1986)MathSciNetCrossRefGoogle Scholar
  11. 11.
    Dubois, D., Prade, H.: Possibility theory, an approach to the computerized processing of uncertainty. Plenum Press, New York (1988)zbMATHGoogle Scholar
  12. 12.
    Duda, R.O., Hart, P.E.: Pattern classification and scene analysis. J. Wiley & Sons, Chichester (1973)zbMATHGoogle Scholar
  13. 13.
    Khedam, R., Bouakache, A., Mercier, G., Belhadj-Aissa, A.: Fusion multitemporelle par la théorie de Dempster-Shafer pour la détection et la cartographie des changements. Application au milieu urbain et périurbain de la région d’Alger. Revue Télédétection 6(4), 359–404 (2006)Google Scholar
  14. 14.
    Le Hégarat-Mascle, S., Bloch, I., Vidal-Madjar, D.: Application of Dempster Shafer evidence theory to unsupervised classification in multisource remote sensing. IEEE Transactions on Geosciences and Remote Sensing 35(4), 1018–1031 (1997)CrossRefGoogle Scholar
  15. 15.
    Richards, J.A., Jia, X.: Remote Sensing Digital Image Analysis. An Introduction, 3rd edn. Springer, Berlin (1998)Google Scholar
  16. 16.
    Shafer, G.: A Mathematical Theory of Evidence, p. 312. Princeton University Press, Princeton (1976)zbMATHGoogle Scholar
  17. 17.
    Smarandache, F., Dezert, J.: Advances and Application of DSmT for Information Fusion, p. 418. American Research Press (2004)Google Scholar
  18. 18.
    Smets, P.: Constructing the pignistic probability function in a context of uncertainty. In: Proceedings of the 5th Annual Conference on Uncertainty in Artificial Intelligence UAI 1989, Windsor, Ontario, pp. 319–326. North Holland Publishing Co., Amsterdam (1989)Google Scholar
  19. 19.
    Smets, P.: The Combination of Evidence in the Transferable Belief Model. IEEE Transactions on Pattern Analysis and Machine Intelligence 12(5), 447–458 (1990)CrossRefGoogle Scholar
  20. 20.
    Vannoorenberghe, P.: Un état de l’art sur les fonctions de croyance appliquées au traitement de l’information. Rapport technique, CNRS, Université de Rouen, UFR des Sciences. Revue 13 20(20) (2004)Google Scholar
  21. 21.
    Zadeh, L.A.: Fuzzy algorithm. Inform. Contr. 12, 94–102 (1968)MathSciNetCrossRefzbMATHGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Abdenour Bouakache
    • 1
  • Radja Khedam
    • 1
  • Aichouche Belhadj-Aissa
    • 1
  • Grégoire Mercier
    • 2
  1. 1.Image Processing and Radiation Laboratory, Faculty of Electronic and Computer ScienceUniversity of Science and Technology Houari Boumediene (USTHB)AlgiersAlgeria
  2. 2.ITI DptGET/ENST Bretagne CS 83818Brest Cedex3France

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