• DocumentCode
    2138531
  • Title

    Experiments on image texture classification with K-views classifier, Markov random fields and cooccurrence probabilities

  • Author

    Hung, Chih-Cheng ; Karabudak, Dilek ; Pham, Minh ; Coleman, Tommy

  • Author_Institution
    Sch. of Comput. & Software Eng., Southern Polytech. State Univ., Marietta, GA
  • Volume
    6
  • fYear
    2004
  • fDate
    20-24 Sept. 2004
  • Firstpage
    3818
  • Abstract
    We compared three image classifiers which incorporate contextual information to classify each pixel in the raw images in this study. These procedures incorporate contextual information by using different features and classify the pixel into one of several predefined classes based on these features. These spatial classifiers strive to capture the spatial relationships encoded in the aerial photograph. The determination of the window size is a challenging issue in these spatial classifiers. Preliminary experimental results are provided in this report
  • Keywords
    Markov processes; feature extraction; geophysical signal processing; geophysical techniques; image classification; image texture; remote sensing; K-views classifier; Markov random fields; aerial photograph; contextual information; cooccurrence probability; image classifiers; image texture classification; pixel classification; spatial classifiers; spatial relationships; window size; Classification algorithms; Image classification; Image segmentation; Image texture; Markov random fields; Multispectral imaging; Narrowband; Pattern recognition; Pixel; Software engineering;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Geoscience and Remote Sensing Symposium, 2004. IGARSS '04. Proceedings. 2004 IEEE International
  • Conference_Location
    Anchorage, AK
  • Print_ISBN
    0-7803-8742-2
  • Type

    conf

  • DOI
    10.1109/IGARSS.2004.1369955
  • Filename
    1369955