• DocumentCode
    382273
  • Title

    Image registration in multispectral data sets

  • Author

    Mahdi, Hani ; Farag, Aly A.

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Louisville Univ., KY, USA
  • Volume
    2
  • fYear
    2002
  • fDate
    2002
  • Abstract
    The paper discusses the matching of two multispectral data sets using the genetic algorithm (GA) as a search technique for the global optimum estimates of the transformation parameters. It uses the simplest form of the affine transformation, where the scaling and rotation are ignored, to explain how the GAs, which are used in the registrations´ processes for the different bands, can cooperate. This cooperation between the GAs improves the speed of the matching process. The cooperation depends on the exchange of the intermediate results between the GAs. Therefore, the proposed approach demands the parallel realization of GAs. In addition, the proposed approach can be considered as a fusion method for the different decisions resulting form the registrations for the different bands. Landsat 7-band and 4-band aerial data set types are considered. The aerial data set type is used to explain how to the proposed approach speeds the matching process.
  • Keywords
    genetic algorithms; image matching; image registration; parallel algorithms; remote sensing; spectral analysis; Landsat 4-band aerial data set; Landsat 7-band aerial data set; aerial data set type; affine transformation; fusion method; genetic algorithm; global optimum estimates; image matching; image registration; matching process speed; multispectral data sets; parallel realization; rotation; scaling; search technique; transformation parameters; Focusing; Force measurement; Genetic algorithms; Hyperspectral imaging; Hyperspectral sensors; Image matching; Image registration; Image sensors; Remote sensing; Satellites;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image Processing. 2002. Proceedings. 2002 International Conference on
  • ISSN
    1522-4880
  • Print_ISBN
    0-7803-7622-6
  • Type

    conf

  • DOI
    10.1109/ICIP.2002.1039964
  • Filename
    1039964