• DocumentCode
    826688
  • Title

    Statistical and operational performance assessment of multitemporal SAR image filtering

  • Author

    Trouvé, Emmanuel ; Chambenoit, Yoann ; Classeau, Nicolas ; Bolon, Philippe

  • Author_Institution
    Lab. d´´Informatique, Syst., Traitement de l´´Inf. et de la Connaissance, Univ. de Savoie, Annecy, France
  • Volume
    41
  • Issue
    11
  • fYear
    2003
  • Firstpage
    2519
  • Lastpage
    2530
  • Abstract
    Multitemporal synthetic aperture radar (SAR) image filtering is a useful preprocessing step for many applications that require speckle reduction. Several multitemporal filters are now available with very different characteristics. In this paper, the performance of three multitemporal filters is assessed with respect to statistical and operational criteria. Statistical criteria include measures of bias, noise reduction, and preservation of both spatial and temporal information. Operational criteria evaluate the accuracy of manual detection of geographical features such as points, lines, and surfaces. This study was carried out with the help of ten photointerpreters. It uses a set of seven multitemporal SAR images from the European Remote Sensing 1 (ERS-1) satellite. It provides guidelines to select multitemporal filters according to the application and the subsequent processing.
  • Keywords
    adaptive filters; geophysical signal processing; image denoising; radar imaging; spaceborne radar; statistical analysis; synthetic aperture radar; terrain mapping; ERS-1 images; bias; multitemporal SAR image filtering; noise reduction; operational performance assessment; preprocessing; spatial information; speckle reduction; statistical assessment; synthetic aperture radar image; temporal information; Computer vision; Filtering; Filters; Manuals; Noise measurement; Noise reduction; Remote sensing; Satellites; Speckle; Synthetic aperture radar;
  • fLanguage
    English
  • Journal_Title
    Geoscience and Remote Sensing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0196-2892
  • Type

    jour

  • DOI
    10.1109/TGRS.2003.817270
  • Filename
    1245239