• DocumentCode
    2397007
  • Title

    Multisensor image fusion by using discrete multiwavelet transform

  • Author

    Wang, Hai-Wi

  • Author_Institution
    Sch. of Comput. Sci. & Eng., Wuhan Inst. of Chem. Technol., China
  • Volume
    7
  • fYear
    2004
  • fDate
    26-29 Aug. 2004
  • Firstpage
    4331
  • Abstract
    We discuss the application of the discrete multiwavelet transform (DMWT) to multisensor image fusion processing. Multiwavelets are extension from scalar wavelets, and have several advantages in comparison with scalar wavelets. Multiwavelet analysis can offer a more precise image analysis than wavelet multiresolution analysis. A novel fusion algorithm is presented for multisensor images based on discrete multiwavelet transform that can be performed at pixel level. After the registering of source images, a pyramid for each source image can be obtained by applying decomposition with multiwavelet in each level. The multiwavelet decomposition coefficients of the input images are appropriately merged and a new fused image is obtained by reconstructing the fused multiwavelet coefficients. This image fusion algorithm may be used to combine images from multisensors to obtain a single composite with extended information content. The results of the experiment indicate that this image fusion algorithm can gain a more satisfactory fusion outcome.
  • Keywords
    discrete wavelet transforms; image reconstruction; image registration; image resolution; sensor fusion; discrete multiwavelet transform; image fusion algorithm; image pixel; image reconstruction; multisensor image fusion processing; multiwavelet decomposition coefficients; multiwavelet image analysis; scalar wavelets; source image registration; wavelet multiresolution analysis; Computer science; Data analysis; Discrete transforms; Discrete wavelet transforms; Image analysis; Image fusion; Image reconstruction; Pixel; Time frequency analysis; Wavelet transforms;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Learning and Cybernetics, 2004. Proceedings of 2004 International Conference on
  • Print_ISBN
    0-7803-8403-2
  • Type

    conf

  • DOI
    10.1109/ICMLC.2004.1384598
  • Filename
    1384598