• DocumentCode
    2125041
  • Title

    Sensitive fusion and segmentation of geophysical images in a complex space of information features on base SVM methodology

  • Author

    Akhmetshin, A.M.

  • Author_Institution
    Dniepropetrovsk Nat. Univ., Ukraine
  • Volume
    4
  • fYear
    2002
  • fDate
    24-28 June 2002
  • Firstpage
    2414
  • Abstract
    The present paper outlines a new effective method of multiparameter images sensitive fusion. The support vector machines (SVM) methodology is used.
  • Keywords
    geophysical signal processing; geophysical techniques; image segmentation; learning automata; multidimensional signal processing; remote sensing; sensor fusion; SVM method; complex space information features; geophysical measurement technique; image fusion; image processing; image segmentation; land surface; multidimensional image processing; multiparameter images; remote sensing; sensitive fusion; support vector machine; support vector machines; terrain mapping; Brightness; Coordinate measuring machines; Geophysical measurements; Image analysis; Image fusion; Image segmentation; Magnetic analysis; Multidimensional systems; Support vector machines; Visualization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Geoscience and Remote Sensing Symposium, 2002. IGARSS '02. 2002 IEEE International
  • Print_ISBN
    0-7803-7536-X
  • Type

    conf

  • DOI
    10.1109/IGARSS.2002.1026561
  • Filename
    1026561
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2125041