• DocumentCode
    2626753
  • Title

    Cloud detection based on texture segmentation by neural network methods

  • Author

    Visa, Ari ; Valkealahti, Kimmo ; Simula, Olli

  • Author_Institution
    Lab. of Inf. & Comput. Sci., Helsinki Univ. of Technol., Espoo, Finland
  • fYear
    1991
  • fDate
    18-21 Nov 1991
  • Firstpage
    1001
  • Abstract
    A novel method to detect and recognize clouds from remote sensing images is introduced. The detection and recognition of clouds are based on textures. The images are partitioned into homogeneously textured regions, and the interpretation of those textures is based on a texture map. This map is created by means of artificial neural network methodology. The use of neural network methods makes it possible to apply an unsupervised learning paradigm to train the map continuously. The texture map is created by a self-organizing process of feature vectors. This is performed in an unsupervised way. The labeling is achieved by a supervised process
  • Keywords
    atmospheric techniques; clouds; computerised pattern recognition; learning systems; neural nets; remote sensing; self-adjusting systems; atmospheric techniques; cloud detection; computerised pattern recognition; labeling; neural network methods; remote sensing images; self-organizing process; supervised process; texture segmentation; unsupervised learning; Clouds; Demand forecasting; Earth; Image segmentation; Laboratories; Lighting; Meteorology; Neural networks; Satellite broadcasting; Weather forecasting;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 1991. 1991 IEEE International Joint Conference on
  • Print_ISBN
    0-7803-0227-3
  • Type

    conf

  • DOI
    10.1109/IJCNN.1991.170529
  • Filename
    170529