• DocumentCode
    3067377
  • Title

    SAR image change detection by likelihood ratio test in multi-temporal time series

  • Author

    Xin Su ; Deledalle, Charles-Alban ; Tupin, Florence ; Hong Sun

  • Author_Institution
    Inst. Mines-Telecom, Telecom ParisTech, Paris, France
  • fYear
    2013
  • fDate
    21-26 July 2013
  • Firstpage
    3439
  • Lastpage
    3442
  • Abstract
    This paper presents a change detection method between two Synthetic Aperture Radar (SAR) images with similar incidence angles and using a likelihood ratio test (LRT). To address the composite hypothesis problem of the LRT, we propose to replace the noise-free values by their estimated results. Thus, a multi-temporal non local means denoising method proposed in [1] is used in this paper to estimate the noise-free values using both spatial and temporal information. The change detection results show the effective performance of the proposed method compared with the state of the art ones, such as log-ratio operator and generalized likelihood ratio test.
  • Keywords
    geophysical image processing; image denoising; remote sensing by radar; synthetic aperture radar; SAR image change detection; likelihood ratio test; log-ratio operator; multitemporal nonlocal means denoising method; multitemporal time series; noise-free values; spatial information; synthetic aperture radar; temporal information; Hidden Markov models; Noise; Noise measurement; Noise reduction; Speckle; Synthetic aperture radar; Likelihood Ratio Test (LRT); Multi-Temporal Denoising; Multi-Temporal Synthetic Aperture Radar (SAR); Non LocalMeans (NLM);
  • 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.2013.6723568
  • Filename
    6723568