• DocumentCode
    1465272
  • Title

    Image fusion technique based on non-subsampled contourlet transform and adaptive unit-fast-linking pulse-coupled neural network

  • Author

    Kong, W.W. ; Lei, Y.J. ; Lei, Yunwen ; Lu, Siyu

  • Author_Institution
    Dept. of Comput. Eng., Air Force Eng. Univ., Xi´an, China
  • Volume
    5
  • Issue
    2
  • fYear
    2011
  • fDate
    3/1/2011 12:00:00 AM
  • Firstpage
    113
  • Lastpage
    121
  • Abstract
    A new image fusion technique based on non-subsampled contourlet transform (NSCT) and adaptive unit-fast-linking pulse-coupled neural network (PCNN) is presented. By using NSCT, multi-scale and multi-direction sparse decompositions of the source images are performed. Then, the basic PCNN model is improved to be an adaptive unit-fast-linking PCNN model, which synthesises the advantages of both unit-linking PCNN and fast-linking PCNN. The novel PCNN model utilises the clarity of each pixel in images as the linking strength β; moreover, the time matrix T of the sub-images can be obtained via the synchronous pulse burst property. Finally, the sub-images are fused by analysing the time matrix T and linking strength β. The experimental results show that the proposed approach is better than some current methods.
  • Keywords
    image fusion; matrix decomposition; neural nets; sparse matrices; transforms; NSCT; PCNN; adaptive unit fast linking; image fusion; non subsampled contourlet transform; pulse coupled neural network; sparse matrix decompositions; synchronous pulse burst property; time matrix;
  • fLanguage
    English
  • Journal_Title
    Image Processing, IET
  • Publisher
    iet
  • ISSN
    1751-9659
  • Type

    jour

  • DOI
    10.1049/iet-ipr.2009.0425
  • Filename
    5724113