• DocumentCode
    593534
  • Title

    Structured l2−l1 experiment design regularization approach for near real time enhancement of low resolution fractional SAR imagery

  • Author

    Shkvarko, Yuriy V. ; Tuxpan, Jose ; Yanez, Israel

  • Author_Institution
    Department of Telecommunications, Center for Advanced Research and Education of the National Polytechnic Institute, CINVESTAV-IPN, Guadalajara, Mexico
  • fYear
    2012
  • fDate
    Oct. 31 2012-Nov. 2 2012
  • Firstpage
    274
  • Lastpage
    277
  • Abstract
    The descriptive experiment design regularization (DEDR) paradigm is aggregated with the variational analysis approach that combines the l2 image metric with the l1 sparse image gradient map metric structures in the solution space. The proposed l2−l1 structured total variation DEDR (STV-DEDR) framework is particularly adapted for enhanced imaging with low resolution side looking airborne radar/fractional SAR sensors putting in a single optimization frame adaptive SAR image despeckling and resolution enhancement that exploits the structured desired image sparseness properties. The STV-DEDR method implemented in a contractive mapping iterative fashion outperforms the competing nonparametric adaptive radar imaging techniques both in resolution enhancement and computational complexity as verified in the simulations.
  • Keywords
    Image reconstruction; Image resolution; Imaging; Measurement; Radar imaging; Synthetic aperture radar; Descriptive experiment design regularization; fractional synthetic aperture radar; image enhancement; remote sensing; structured total variation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Radar Conference (EuRAD), 2012 9th European
  • Conference_Location
    Amsterdam, Netherlands
  • Print_ISBN
    978-1-4673-2471-7
  • Type

    conf

  • Filename
    6450650