• DocumentCode
    1651904
  • Title

    Unsupervised spectral pattern recognition for multispectral images by means of a genetic programming approach

  • Author

    De Falco, I. ; Tarantino, E. ; Della Cioppa, A.

  • Author_Institution
    ISPAIM, Nat. Res. Council of Italy, Naples, Italy
  • Volume
    1
  • fYear
    2002
  • Firstpage
    231
  • Abstract
    An innovative approach to spectral pattern recognition for multispectral images based on genetic programming is introduced. The problem is faced in terms of unsupervised pixel classification. The system is tested on a multispectral image with 31 spectral bands and 256-256 pixels. A good quality clustered output image is obtained.
  • Keywords
    genetic algorithms; pattern recognition; unsupervised learning; clustered output image; genetic programming; genetic programming approach; multispectral images; unsupervised pixel classification; unsupervised spectral pattern recognition; Councils; Digital images; Genetic programming; Image analysis; Multispectral imaging; Pattern recognition; Pixel; Remote monitoring; Water pollution; Weather forecasting;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Evolutionary Computation, 2002. CEC '02. Proceedings of the 2002 Congress on
  • Conference_Location
    Honolulu, HI, USA
  • Print_ISBN
    0-7803-7282-4
  • Type

    conf

  • DOI
    10.1109/CEC.2002.1006239
  • Filename
    1006239