• DocumentCode
    3297032
  • Title

    Sequence Similarity and Multi-Date Image Segmentation

  • Author

    Ketterlin, Alain ; Gancarski, Pierre

  • Author_Institution
    Univ. Louis Pasteur, Strasbourg
  • fYear
    2007
  • fDate
    18-20 July 2007
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    Multi-date images present new challenges and new opportunities for image analysis. This paper considers the task of segmenting a multi-date image by clustering its pixels without requiring perfect time-based alignment. It first introduces the problem, and then proceeds with the definition of a similarity measure between sequences of observations, i.e., pixels. This is followed by an explanation of how to use this similarity measure to apply well known clustering algorithms. The paper concludes by some brief experiment descriptions.
  • Keywords
    data analysis; image segmentation; pattern clustering; remote sensing; clustering algorithms; image analysis; multidate image segmentation; pixels clustering; sequence similarity; Clustering algorithms; Data analysis; Image segmentation; Image sensors; Image sequence analysis; Pixel; Sensor phenomena and characterization; Time measurement; Tin; Wavelength measurement;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Analysis of Multi-temporal Remote Sensing Images, 2007. MultiTemp 2007. International Workshop on the
  • Conference_Location
    Leuven
  • Print_ISBN
    1-4244-0845-8
  • Electronic_ISBN
    1-4244-0846-6
  • Type

    conf

  • DOI
    10.1109/MULTITEMP.2007.4293034
  • Filename
    4293034