• DocumentCode
    30081
  • Title

    InSAR Image Regularization and DEM Error Correction With Fractal Surface Scattering Model

  • Author

    Danudirdjo, D. ; Hirose, Akira

  • Author_Institution
    Dept. of Electr. Eng. & Inf. Syst., Univ. of Tokyo, Tokyo, Japan
  • Volume
    53
  • Issue
    3
  • fYear
    2015
  • fDate
    Mar-15
  • Firstpage
    1427
  • Lastpage
    1439
  • Abstract
    This paper presents a method for removing spikes in digital elevation models (DEMs) caused by residues in interferometric synthetic aperture radar (InSAR) phase image. We consider that the scattering mechanism is properly modeled by the small perturbation method for fractal surfaces and present a model that relates the phase and magnitude in InSAR image. This data model provides the regularization term of the method, without directly enforcing smooth phase or magnitude. Noise models are given by additive Gaussian for the phase and multiplicative non-unit-mean gamma for the magnitude. Experiments with simulated and real L-band data show that the proposed method considerably improves DEM accuracy and simultaneously suppresses speckle and phase noise.
  • Keywords
    digital elevation models; electromagnetic wave scattering; fractals; geophysical image processing; radar imaging; radar interferometry; random noise; remote sensing by radar; synthetic aperture radar; DEM accuracy; DEM error correction; DEM spike removal; InSAR image regularization; InSAR phase image residues; additive Gaussian noise model; digital elevation models; fractal surface scattering model; fractal surfaces; interferometric synthetic aperture radar; magnitude noise; multiplicative nonunit mean gamma noise model; phase noise suppression; real L-band data; scattering mechanism; simulated L-band data; speckle suppression; Data models; Fractals; Noise; Scattering; Surface topography; Surface treatment; Synthetic aperture radar; Digital elevation model (DEM); fractals; image denoising; speckle; synthetic aperture radar (SAR);
  • fLanguage
    English
  • Journal_Title
    Geoscience and Remote Sensing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0196-2892
  • Type

    jour

  • DOI
    10.1109/TGRS.2014.2341254
  • Filename
    6879260