• DocumentCode
    2821805
  • Title

    Image Fusion Algorithm Based on Self-Adaptive Fuzzy Clustering Method

  • Author

    Hong Zhang ; XiaoNan Sun ; Yanfeng Sun ; Lei Liu

  • Author_Institution
    Dept. of Comput. Sci. & Technol., Jilin Univ., Changchun
  • Volume
    1
  • fYear
    2008
  • fDate
    2-4 Sept. 2008
  • Firstpage
    446
  • Lastpage
    449
  • Abstract
    This paper explores an image fusion algorithm based on self-adaptive fuzzy clustering algorithm. The clustering method combined nearest neighbor clustering method with k-means clustering method (NNKM) is adopted in pixel classification. The membership of every image pixel to each cluster center is introduced. And the fused image membership obtained by maximum rule is adopted as the weighting coefficient of the weighted mean strategy, which is used to obtain the fusion image. In this experiment, the fusion results of various Radiuses of Gauss function are compared with the results obtained by nearest neighbor clustering method. The experiment results show that the proposed method can achieve better performance of the fused image.
  • Keywords
    fuzzy set theory; image classification; image fusion; pattern clustering; Gauss function; cluster center; image fusion; image membership; k-means clustering; nearest neighbor clustering; pixel classification; self-adaptive fuzzy clustering; weighted mean strategy; weighting coefficient; Clustering algorithms; Clustering methods; Computer networks; Fuzzy sets; Image fusion; Information management; Nearest neighbor searches; Neural networks; Pixel; Sun; Image fusion; K-means; nearest neighbor clustering method;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Networked Computing and Advanced Information Management, 2008. NCM '08. Fourth International Conference on
  • Conference_Location
    Gyeongju
  • Print_ISBN
    978-0-7695-3322-3
  • Type

    conf

  • DOI
    10.1109/NCM.2008.95
  • Filename
    4624049