• DocumentCode
    2322004
  • Title

    Fuzzy samples retrieval: A method of SAR image retrieval in urban areas

  • Author

    Shangtan, Tu ; Hong, Sun

  • Author_Institution
    Sch. of Electron. Inf., Wuhan Univ., Wuhan
  • fYear
    2009
  • fDate
    20-22 May 2009
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    As the retrieval entrance, description of retrieval objects plays an important role in CBSIR (Content-Based SAR (Synthetic Aperture Radar) Image Retrieval) systems. Most of the CBSIR systems take one Region of Interest (ROI) from the original image, which contains the retrieval object, as the retrieval entrance. Besides, freehand sketch retrieval methods are used extensively in CBOIR (Content-Based Optical Image Retrieval). But when the retrieval objects are fuzzy in SAR image, methods mentioned above are no longer applied because speckle noises make the description of retrieval objects unfeasible. In this paper, a method is proposed to describe the retrieval objects in SAR image, which is called Fuzzy Samples Retrieval (FSR). In the experiments FSR is compared with the retrieval based on ROI of original image and freehand sketch sample, the results show that FSR has a better performance in CBSIR systems.
  • Keywords
    fuzzy systems; geophysical techniques; geophysics computing; image retrieval; synthetic aperture radar; CBOIR; CBSIR; Content-Based Optical Image Retrieval; Content-Based SAR Image Retrieval systems; FSR; Fuzzy Samples Retrieval; SAR image; original image; retrieval object; speckle noises; urban areas; Adaptive optics; Content based retrieval; Fuzzy sets; Image retrieval; Optical noise; Optical sensors; Remote sensing; Speckle; Synthetic aperture radar; Urban areas;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Urban Remote Sensing Event, 2009 Joint
  • Conference_Location
    Shanghai
  • Print_ISBN
    978-1-4244-3460-2
  • Electronic_ISBN
    978-1-4244-3461-9
  • Type

    conf

  • DOI
    10.1109/URS.2009.5137671
  • Filename
    5137671