• DocumentCode
    291635
  • Title

    Use of fuzzy logic for unsupervised classification of remotely sensed images

  • Author

    Mouchot, Marie Catherine ; Solaiman, Basel ; Parra, Alfonso

  • Author_Institution
    Dept. Image et Traitment de l´´Inf., Ecole Nat. des Telecomm. de Bretagne, Brest, France
  • Volume
    2
  • fYear
    1994
  • fDate
    8-12 Aug. 1994
  • Firstpage
    1163
  • Abstract
    Fuzzy logic offers an opportunity to overcome some of the limitations attached to conventional classifications by providing weighted description, by means of membership values, of each pixel to generic categories of land occupation areas. These membership values are obtained by adjustment of pre-defined membership functions, expressed by means of linguistic predicates, to experimental conditions using solely information contained in the image itself. The image is then classified according to the membership values using different fuzzy rules. A winter time TM image of Brittany (France) was processed according to this method.
  • Keywords
    fuzzy logic; geophysical signal processing; geophysical techniques; geophysics computing; image classification; remote sensing; Brittany; France; fuzzy logic; fuzzy rule; generic categories; geophysical measurement technique; geophysics computing; image classification; land occupation area; land occupation areas; land surface terrain mapping; linguistic predicate; linguistic predicates; membership values; optical imaging; remote sensing; unsupervised classification; weighted description; Data mining; Educational institutions; Facsimile; Fuzzy logic; Fuzzy sets; Pixel; Remote sensing; Shape; Telephony;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Geoscience and Remote Sensing Symposium, 1994. IGARSS '94. Surface and Atmospheric Remote Sensing: Technologies, Data Analysis and Interpretation., International
  • Print_ISBN
    0-7803-1497-2
  • Type

    conf

  • DOI
    10.1109/IGARSS.1994.399373
  • Filename
    399373