• DocumentCode
    23025
  • Title

    Automatic Recognition of Isolated Buildings on Single-Aspect SAR Image Using Range Detector

  • Author

    Shanshan Chen ; Haipeng Wang ; Feng Xu ; Ya-Qiu Jin

  • Author_Institution
    Key Lab. for Inf. Sci. of Electromagn. Waves (MoE), Fudan Univ., Shanghai, China
  • Volume
    12
  • Issue
    2
  • fYear
    2015
  • fDate
    Feb. 2015
  • Firstpage
    219
  • Lastpage
    223
  • Abstract
    Man-made building objects mostly with vertical wall structures may present distinct scattering patterns, e.g., wall/roof upfront scattering, wall-ground double scattering, etc., along the range dimension in high-resolution synthetic aperture radar (SAR) images. In this letter, a 1-D detector, referred to as the “range detector,” is presented for building detection, which operates only along the range direction. Experiments show that this range detector can effectively detect and extract the footprint of the illuminated wall of a cuboid building, with which the outline of the building image can be captured by marching the footprint toward radar. This approach is applied to an airborne Pi-SAR image of Sendai, Japan, and more than 80% of the buildings can be identified. The building height and length are also estimated, and the errors are found around 4-5 m based on optical image.
  • Keywords
    geophysical image processing; image recognition; radar imaging; remote sensing by radar; synthetic aperture radar; Japan; Sendai; airborne Pi-SAR image; building image outline; cuboid building; high-resolution SAR images; illuminated wall; isolated building automatic recognition; man-made building objects; optical image; range detector; scattering patterns; single-aspect SAR image; synthetic aperture radar; vertical wall structures; wall-ground double scattering; Buildings; Detectors; Image recognition; Optical imaging; Radar imaging; Scattering; Synthetic aperture radar; Automatic target recognition (ATR); building objects; range detector; synthetic aperture radar (SAR) image;
  • fLanguage
    English
  • Journal_Title
    Geoscience and Remote Sensing Letters, IEEE
  • Publisher
    ieee
  • ISSN
    1545-598X
  • Type

    jour

  • DOI
    10.1109/LGRS.2014.2327125
  • Filename
    6876126