• DocumentCode
    35769
  • Title

    Object-Based Change Detection of Very High Resolution Satellite Imagery Using the Cross-Sharpening of Multitemporal Data

  • Author

    Biao Wang ; Seokkeun Choi ; Younggi Byun ; Soungki Lee ; Jaewan Choi

  • Author_Institution
    Sch. of Civil Eng., Chungbuk Nat. Univ., Cheongju, South Korea
  • Volume
    12
  • Issue
    5
  • fYear
    2015
  • fDate
    May-15
  • Firstpage
    1151
  • Lastpage
    1155
  • Abstract
    In this letter, we present a method for unsupervised change detection based on the cross-sharpening of multitemporal images and image segmentation. Our method effectively reduces the change detection errors caused by relief or spatial displacement between multitemporal images with different acquisition angles. A total of four cross-sharpened images, including two general pansharpened images, were generated. Then, two pairs of cross-sharpened images were analyzed using change detection indexes. The effectiveness of the proposed method compared with other unsupervised change detection methods is demonstrated through experimentation.
  • Keywords
    geophysical image processing; image resolution; image segmentation; remote sensing; acquisition angles; change detection indexes; cross-sharpened images; general pansharpened images; image segmentation; multitemporal images; object-based change detection errors; relief displacement; spatial displacement; unsupervised change detection methods; very high resolution satellite imagery; Change detection algorithms; Correlation; Image resolution; Image segmentation; Indexes; Remote sensing; Satellites; Cross-sharpening; image segmentation; spatial displacement; unsupervised change detection;
  • fLanguage
    English
  • Journal_Title
    Geoscience and Remote Sensing Letters, IEEE
  • Publisher
    ieee
  • ISSN
    1545-598X
  • Type

    jour

  • DOI
    10.1109/LGRS.2014.2386878
  • Filename
    7021897