• DocumentCode
    231654
  • Title

    A novel multi-focus image fusion algorithm based on NSST-FRFT

  • Author

    Sun Yuchao ; Hu Shaohai ; Liu Shuaiqi ; Sun Wei

  • Author_Institution
    Inst. of Inf. Sci., Beijing Jiaotong Univ., Beijing, China
  • fYear
    2014
  • fDate
    19-23 Oct. 2014
  • Firstpage
    780
  • Lastpage
    783
  • Abstract
    Non-subsampled Shearlet transform (NSST) has good properties such as multi-scale, multi-direction and shift invariance, but limits the signal analysis to the time frequency domain. Fractional Fourier transform (FRFT) extend the signal analysis to fractional domain, but it is unable to analysis the partial characteristic of signal. Combine the advantages of NSST and FRFT, a novel image fusion algorithm is proposed. Firstly, NSST is applied to the two source images. Secondly, the FRFT is applied to the low-frequency sub-bands coefficients of NSST to acquire image description in fractional domain. Thirdly, fusion rule selecting maximizes of sum-modified-Laplacian is applied to fuse high-frequency sub-bands coefficients and fusion rule of the simple averaging operation is applied to fuse low-frequency coefficients. Finally, the fused image is obtained by the inverse FRFT and inverse NSST. Experimental results show that the proposed method can not only obtain good visual effect, but also improve its objective evaluation criteria.
  • Keywords
    Fourier transforms; image fusion; time-frequency analysis; fractional Fourier transform; image description; inverse FRFT; inverse NSST; low-frequency sub-bands coefficients; nonsubsampled Shearlet transform; novel multifocus image fusion algorithm; signal analysis; sum-modified-Laplacian; time frequency domain; Discrete wavelet transforms; Educational institutions; Fourier transforms; Image fusion; Signal processing algorithms; FRFT; Image fusion; NSST; SML;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signal Processing (ICSP), 2014 12th International Conference on
  • Conference_Location
    Hangzhou
  • ISSN
    2164-5221
  • Print_ISBN
    978-1-4799-2188-1
  • Type

    conf

  • DOI
    10.1109/ICOSP.2014.7015110
  • Filename
    7015110