• DocumentCode
    576035
  • Title

    Blocked spectrum compressive sensing based on Root-MUSIC algorithm for SAR image

  • Author

    Li, Xiaobo ; Chen, Jie ; Zhu, Yanqing

  • Author_Institution
    Sch. of Electron. Inf. Eng., Beihang Univ., Beijing, China
  • fYear
    2012
  • fDate
    22-27 July 2012
  • Firstpage
    2094
  • Lastpage
    2096
  • Abstract
    In order to effectively reduce the storage volume of complex image data in high-resolution synthetic aperture radar (SAR), blocked spectrum compressive framework [1][2] based on Root-MUSIC algorithm is proposed. In this paper block-wise processing [3] of SAR image method is introduced, which can effectively reduce the storage space of measurement matrix. Gaussian random matrix is employed as observation matrix [4][5] to obtain observed value of each sub-block. Model parameters can be calculated by means of Root-MUSIC algorithm. Spectrum signal is reconstructed from small amount of measurements. Simulation results with real spatial-sparse SAR image demonstrate that data storage capacity can be reduced to as low as 1.17%, which validate the effectiveness of the method.
  • Keywords
    Gaussian processes; compressed sensing; image reconstruction; matrix algebra; radar imaging; synthetic aperture radar; Gaussian random matrix; SAR image method; block-wise processing; blocked spectrum compressive sensing; data storage capacity reduction; high-resolution synthetic aperture radar; measurement matrix; observation matrix; root-MUSIC algorithm; spatial-sparse SAR image; spectrum signal reconstruction; storage volume reduction; Compressed sensing; Discrete cosine transforms; Frequency domain analysis; Image reconstruction; Signal processing algorithms; Sparse matrices; Synthetic aperture radar; SAR image; block; compressive sensing; root-music algorithm; signal reconstruction;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Geoscience and Remote Sensing Symposium (IGARSS), 2012 IEEE International
  • Conference_Location
    Munich
  • ISSN
    2153-6996
  • Print_ISBN
    978-1-4673-1160-1
  • Electronic_ISBN
    2153-6996
  • Type

    conf

  • DOI
    10.1109/IGARSS.2012.6350959
  • Filename
    6350959