A Possibility-Based Model to Index Remote Sensing Images

  • Paola Carrara
  • Gabriella Pasi
  • Monica Pepe
  • Anna Rampini


Recently, several environmental applications took advantage of the use and analysis of remote sensing images, since they are intrinsically referred to the spatial distribution of the phenomena of interest. Remote sensing is widely employed for land monitoring, land planning and risk prevention; its ultimate aim is to identify specific image contents to create thematic maps. An efficient management of large collections of remote sensing images and effective retrieval mechanisms are therefore becoming a need, so that remote sensing images have been included in the list of Grand Challenges application fields for visual information management systems or Content-Based Information Retrieval (CBIR) systems [24]: in fact this application area justifies the use of large computers and storage capacity necessary for visual databases.


Information Retrieval Image Retrieval Spectral Signature Information Item Reference Class 
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.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Anderson J.T., Stonebraker M. (1994) Sequoia 2000 metadata schema for satellite images. ACM SIGMOD Record 23(4):42–48.CrossRefGoogle Scholar
  2. 2.
    Barros J., French J., Martin W., Kelly P., White J.M. (1994) Indexing Multispectral Images for Content-Based Retrieval. In: Image and Information Systems: Applications and Opportunities (23rd AIPR Workshop), Proc. of SPIE 2368, Washington DC, Oct. 1994, pp. 25–36.Google Scholar
  3. 3.
    Bergman L.D., Castelli V., Li C.-S. (1997) Progressive Content-Based Retrieval from satellite image archives. D-Lib Magazine, October 1007, [Online] , <>Google Scholar
  4. 4.
    Bretschneider T., Cavet R., Cao O. (2002) Retrieval of remotely sensed imagery using spectral information content. In: Proc. of the International Geoscience and Remote Sensing Symposium, Vol. 4, pp. 2253–2256.CrossRefGoogle Scholar
  5. 5.
    Capodiferro L., Kiranyaz S., Gabbouj M. (2003) Evaluation criteria and evaluation report. Deliverable of the Project ‘Network of excellence in Content-based semantic scene analysis and Information Retrieval’, IST-2001–32795.Google Scholar
  6. 6.
    Carrara P., Galli C., Rampini A. (2000) A Database for Remote Sensing Image Retrieval by Spectral Features. ITIM-CNR Tech. Rep.Google Scholar
  7. 7.
    Chang D., Moon B., Acharya A., Shock C., Sussman A., Saltz J.H. (1997) Titan: A high-performance remote sensing database. In: Proc. of the International Conference on Data Engineering, pp. 375–384.Google Scholar
  8. 8.
    Congalton R.G. (1991) A review of Assessing the Accuracy of Classification of Remotely Sensed Data. Remote Sens. Environ. 37:35–46.CrossRefGoogle Scholar
  9. 9.
    Del Bimbo A. (1999) Visual Information Retrieval. Morgan Kaufmann Publishers, San Francisco, CA.Google Scholar
  10. 10.
    Dubois D., Prade H. (1988) Possibility Theory: An Approach to Computerized Processing of Uncertainty. Plenum Press, New York.CrossRefGoogle Scholar
  11. 11.
    Eakins J.P. (2001) Retrieval of Still Images by Content. In: Agosti M., Crestani F., Pasi G. (Eds.) Lectures in Information Retrieval. Springer, Berlin Heidelberg New York, pp. 110–138.Google Scholar
  12. 12.
    Ghezzi P.P., Binaghi E., Galli C., Rampini A. (1997) Integrazione di Tecniche di Clustering ‘Split and Merge’ e Fuzzy per la Classificazione di Immagini. In: Proc. of the First Nat. Conf. ASITA, Parma (Italy), pp. 149–150.Google Scholar
  13. 13.
    Jain A.K., Vailaya A. (1998) Shape-based retrieval: A case study with trademark image databases. Pattern Recognition 31(9):1369–1390.CrossRefGoogle Scholar
  14. 14.
    Koperski K., Marchisio G.B. (2000) Multi-level Indexing and GIS Enhanced Learning for Satellite Imagery. In: Proc. of the Workshop on Multimedia Data Mining MDM/KDD2000, Boston (MA) USA, pp. 8–13.Google Scholar
  15. 15.
    Miyamoto S. (1990) Fuzzy Sets in Information Retrieval and Cluster Analysis. Kluwer Academic Publishers, Dordrecht.CrossRefGoogle Scholar
  16. 16.
    Niblack W., et al. (1993) The QBIC Project: Query by image by content using color, texture, and shape. In: Niblack W., Jain R. (Eds.) Proc. of Storage and Retrieval for Image and Video Databases, Vol. 1908, SPIE Press, Bellingham, WA, pp. 173–187.CrossRefGoogle Scholar
  17. 17.
    Petrakis E.G.M., Orphanoudakis S.C. (1993) Methodology for the Representation, Indexing and Retrieval of Images by Content. Image and Vision Computing 11(8):504–521.CrossRefGoogle Scholar
  18. 18.
    Petrakis E.G.M., Faloutsos C. (1994) Similarity Searching in Large Image Databases. Technical Report CS-TR-3388, College Park, MD, USA.Google Scholar
  19. 19.
    Robertson S. (2001) Evaluation in Information Retrieval. In: Agosti M., Crestani F., Pasi G. (Eds.) Lectures in Information Retrieval. Springer, Berlin Heidelberg New York, pp. 81–92.CrossRefGoogle Scholar
  20. 20.
    Rui Y., Huang T.S., Chang S.F. (1999) Image retrieval: Past, present, and future. Journal of Visual Communication and Image Representation 10:1–23.CrossRefGoogle Scholar
  21. 21.
    Salton G., McGill M. (1983) Introduction to Modern Information Retrieval. McGraw-Hill, New York.Google Scholar
  22. 22.
    Schowengerdt R.A. (1997) Models and Methods for Image Processing, Academic Press, San Diego.Google Scholar
  23. 23.
    Sheikholeslami G., Zhang A., Bian T. (1999) A Multiresolution Content-based Retrieval Approach for Geographic Images. Geoinformatica 3(2):109–139.CrossRefGoogle Scholar
  24. 24.
    Smeulders A.W.M., Worring M., Santini S., Gupta A., Jain R. (2000) ContentBased Image Retrieval at the end of the early years. IEEE Transactions on Pattern Analysis and Machine Intwlligence 22(12):1349–1380.CrossRefGoogle Scholar
  25. 25.
    Stephenson T., Voorhees H. (1995) IMACT: An interactive, multiterabyte image archive. In: Proc. of the IEEE Symposium on Mass Storage Systems, pp. 146–161.CrossRefGoogle Scholar
  26. 26.
    Val Cura L.M., Leite N.J., Bauzer Medeiros C. (2000) An Architecture for Content-Based Retrieval of Remote Sensing Images. In: Proc. of the IEEE International Conference on Multimedia and Expo, New York City, NY (USA), pp. 303–306.Google Scholar
  27. 27.
    Vellaikal A., Kuo C.C., Dao S. (1995) Content-Based Retrieval of Remote Sensed Images Using Vector Quantization. In: Proc. of SPIE Visual Information Processing, Vol. 2488, pp. 178–189.Google Scholar
  28. 28.
    Zadeh L.A. (1975) The Concept of a Linguistic Variable and its Application to Approximate Reasoning I-II. Information Sciences 8:199–249.CrossRefGoogle Scholar
  29. 29.
    Zadeh L.A. (1978) Fuzzy Sets as a Basis for a Theory of Possibility. Fuzzy Sets and Systems 1:3–28.CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Paola Carrara
    • 1
  • Gabriella Pasi
    • 2
  • Monica Pepe
    • 1
  • Anna Rampini
    • 1
  1. 1.IREA-CNRMilanItaly
  2. 2.ITC-CNRMilanItaly

Personalised recommendations