• DocumentCode
    3068082
  • Title

    Target detection on high-resolution SAR image using Part-based CFAR Model

  • Author

    Chu He ; Yu Zhang ; Xin Su ; Xin Xu ; Ming-sheng Liao

  • Author_Institution
    Sch. of Electron. Inf., Wuhan Univ., Wuhan, China
  • fYear
    2013
  • fDate
    21-26 July 2013
  • Firstpage
    3570
  • Lastpage
    3573
  • Abstract
    This letter proposed a Part-based CFAR Model for object detection of power tower on high-resolution SAR images. Firstly, Part-based Model is used to describe the structure feature of the target, then Compressing Sensing approach is added to reduce the speckle by means of rebuilding background clutter, next, CFAR method is used to extract local shape and scale parameters, at last, Part-based CFAR Model combines these procedures together to form the finally algorithm, not only includes the distribution features, but also considers the structure relationship in the proposed approach. The algorithm is tested on TerraSAR-X data set with the resolution of 1m and 3m. Experiments show that unlike the CFAR method can only gives the high-light points of the targets; Part-based CFAR Model illuminates the target and its local components by plotting the bounding boxes around them.
  • Keywords
    geophysical image processing; object detection; radar imaging; remote sensing by radar; synthetic aperture radar; CFAR method; TerraSAR-X data set; compressing sensing approach; high-resolution SAR images; object detection; part-based CFAR model; target detection; Abstracts; Adaptation models; Image resolution; Snow; Transforms; CFAR; Compressing Sensing; Part-based Model; SAR; target detection;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Geoscience and Remote Sensing Symposium (IGARSS), 2013 IEEE International
  • Conference_Location
    Melbourne, VIC
  • ISSN
    2153-6996
  • Print_ISBN
    978-1-4799-1114-1
  • Type

    conf

  • DOI
    10.1109/IGARSS.2013.6723601
  • Filename
    6723601