• DocumentCode
    3126160
  • Title

    Adaptive Fusion Algorithm of Multisensor Image in Nonsubsampled Contourlet Domain

  • Author

    Yang, Xiaohui

  • Author_Institution
    Sch. of Math. & Inf. Sci., Henan Univ., Kaifeng, China
  • fYear
    2009
  • fDate
    28-29 Dec. 2009
  • Firstpage
    334
  • Lastpage
    337
  • Abstract
    Considering of the characteristics of low visible light images and infrared images and combining with the human visual system, a novel image fusion technique is presented in this paper. The fusion technique is based on immune clonal selection (ICS) in natural immune selection and nonsubsampled contourlet transform (NSCT). NSCT can give the asymptotic optimal representation of the edges and contours in image by virtue of the characteristics of good multiresolution, shift-invariance and multi-directionality. And then ICS is introduced into NSCT domain to optimize the fusing weights adaptively. Numerical tests show that this algorithm provides improvements both in visual effects and quantitative analysis. And the fusion images hold edge and texture information well and have ideal contrast and definition.
  • Keywords
    edge detection; image fusion; image representation; image resolution; image texture; optimisation; adaptive fusion algorithm; contour representation; edge representation; human visual system; image edge; image texture; immune clonal selection; infrared images; low visible light images; multidirectionality; multiresolution; multisensor image; nonsubsampled contourlet domain; optimization; shift-invariance; Anisotropic magnetoresistance; Humans; Image edge detection; Image fusion; Image sensors; Immune system; Infrared imaging; Layout; Pixel; Wavelet transforms; image fusion; immune clone selection; multisensor images; nonsubsampled contourlet;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Wireless Networks and Information Systems, 2009. WNIS '09. International Conference on
  • Conference_Location
    Shanghai
  • Print_ISBN
    978-0-7695-3901-0
  • Electronic_ISBN
    978-1-4244-5400-6
  • Type

    conf

  • DOI
    10.1109/WNIS.2009.37
  • Filename
    5381961