• DocumentCode
    2818327
  • Title

    Bayesian TV denoising of SAR images

  • Author

    Vega, Miguel ; Mateos, Javier ; Molina, Rafael ; Katsaggelos, Aggelos K.

  • Author_Institution
    Dept. de Lenguajes y Sist. Informaticos, Univ. de Granada, Granada, Spain
  • fYear
    2011
  • fDate
    11-14 Sept. 2011
  • Firstpage
    165
  • Lastpage
    168
  • Abstract
    Synthetic aperture radar (SAR) imagery suffers from the speckle phenomenon. Speckle gives rise to the presence of multiplicative noise which severely degrades the observed images. It is known that logarithmically transformed speckle can be well approximated by a Gaussian distribution. In this paper we propose an algorithm for despeckling images, within the log-transformed spatial domain, using a TV prior whose model parameter is automatically determined using the Evidence Analysis within the Hierarchical Bayesian Paradigm. The effectiveness of the proposed algorithm, over both synthetically speckled and real SAR images, is studied.
  • Keywords
    Bayes methods; Gaussian distribution; image denoising; radar imaging; speckle; synthetic aperture radar; Bayesian TV denoising; Gaussian distribution; SAR images; evidence analysis; hierarchical Bayesian paradigm; log transformed spatial domain; speckle phenomenon; synthetic aperture radar imagery; Algorithm design and analysis; Bayesian methods; Image restoration; Noise; Speckle; Synthetic aperture radar; TV; Bayesian methods; SAR images denoising; despeckling; image restoration; parameter estimation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image Processing (ICIP), 2011 18th IEEE International Conference on
  • Conference_Location
    Brussels
  • ISSN
    1522-4880
  • Print_ISBN
    978-1-4577-1304-0
  • Electronic_ISBN
    1522-4880
  • Type

    conf

  • DOI
    10.1109/ICIP.2011.6115772
  • Filename
    6115772