• DocumentCode
    3406301
  • Title

    Pixel level multifocus image fusion based on variational decomposition in combination with structure tensor analysis

  • Author

    Zhang, Yongping ; He, Zhongkun ; Su, Rina ; Cheng, Fang ; Ding, Liang ; Mi, Quanmao

  • Author_Institution
    Sch. of Electron. & Inf. Eng., Ningbo Univ. of Technol., Ningbo, China
  • fYear
    2010
  • fDate
    24-28 Oct. 2010
  • Firstpage
    849
  • Lastpage
    852
  • Abstract
    An image fusion Algorithm based on variational decomposition and energy of edge is presented in this paper. Firstly, each source image is decomposed into a geometrical component and a textured component by applying Rudin-Osher-Fatemi (ROF) model in combination with Chambolle´s projection algorithm. Secondly, the corresponding components are fused separately. For fusing the geometrical components, a weighted average method is adopted. To construct the textured component, a reconstruction algorithm of vector field based on structure tensor analysis is adopted. Finally, the sum of the fused composites is calculated to obtain the fused result. Experiments show that the proposed algorithm works well in multi focus image fusion.
  • Keywords
    image fusion; image reconstruction; image texture; tensors; Chambolle projection algorithm; ROF model; Rudin-Osher-Fatemi model; edge energy; geometrical component; pixel level multifocus image fusion; reconstruction algorithm; structure tensor analysis; textured component; variational decomposition; weighted average method; Eigenvalues and eigenfunctions; Image fusion; Pixel; Projection algorithms; Reconstruction algorithms; Signal processing algorithms; Tensile stress; Image decomposition; Image fusion; Structure tensor; Variational model;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signal Processing (ICSP), 2010 IEEE 10th International Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    978-1-4244-5897-4
  • Type

    conf

  • DOI
    10.1109/ICOSP.2010.5655949
  • Filename
    5655949