• DocumentCode
    3722641
  • Title

    Fusion of Polarization Image Using Bidimensional Empirical Mode Decomposition

  • Author

    Dexiang Zhang;Jiaxing Li;Zihong Chen;Jingjing Zhang

  • Author_Institution
    Key Lab. of Intell. Comput. &
  • fYear
    2015
  • Firstpage
    206
  • Lastpage
    209
  • Abstract
    Empirical mode decomposition (EMD) provides a powerful tool for adaptive multiscale analysis of nonstationary signals. Bidimensional empirical mode decomposition (BEMD) techniques decompose an image into several bidimensional intrinsic mode functions (BIMFs) and a bidimensional residue (BR). Firstly, several polarization images can be decomposed into several BIMFs with multi-scales using BEMD. For the BIMF coefficients, the teager energy-based method is used. For the each BIMF coefficients, the area-based teager energy larger value of information measurement is used to select the better coefficients for fusion. At last the fused image can be obtained by utilizing inverse transform for fused image. Experimental results show that the proposed algorithm gives more satisfactory results than the traditional image fusion algorithms in preserving the edges and texture information.
  • Keywords
    "Image fusion","Empirical mode decomposition","Interpolation","Entropy","Algorithm design and analysis","Automation"
  • Publisher
    ieee
  • Conference_Titel
    Computer Science and Mechanical Automation (CSMA), 2015 International Conference on
  • Type

    conf

  • DOI
    10.1109/CSMA.2015.48
  • Filename
    7371652