• DocumentCode
    2604450
  • Title

    Remote Sensing Image Fusion on Gradient Field

  • Author

    Wen, Jianting ; Li, Yan ; Gong, Haifeng

  • Author_Institution
    Sch. of Comput., South China Normal Univ.
  • Volume
    3
  • fYear
    0
  • fDate
    0-0 0
  • Firstpage
    643
  • Lastpage
    646
  • Abstract
    This paper presents two methods to fuse a low spatial resolution multispectral image and a high spatial resolution panchromatic one to produce a new multispectral image with high spatial resolution. First, the Poisson fusion method is developed based on minimizing the gradient difference between the synthesized image and the panchromatic image with boundary conditions sampled from the multispectral image. The fusion result can therefore be achieved by solving the Poisson equation with Dirichlet boundary conditions. Secondly, an optimal fusion technique, which minimizes the gradient difference and the color difference with respect to the panchromatic and multispectral images respectively is given and the result is induced by an iterative optimization algorithm. Both of them can be applied to color composites and individual bands. Their advantages of the fidelity to spectral property and the spatial resolution improvement over the HSI, Brovey, PCA and wavelet transform are convincingly demonstrated in the experiments from visual evaluation and statistical analysis
  • Keywords
    Poisson equation; boundary-value problems; geophysics computing; gradient methods; image colour analysis; image resolution; optimisation; remote sensing; stochastic processes; Dirichlet boundary conditions; Poisson fusion; gradient field; high spatial resolution panchromatic image; iterative optimization; low spatial resolution multispectral image; remote sensing image fusion; Boundary conditions; Fuses; Image fusion; Iterative algorithms; Multispectral imaging; Poisson equations; Principal component analysis; Remote sensing; Spatial resolution; Wavelet analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Pattern Recognition, 2006. ICPR 2006. 18th International Conference on
  • Conference_Location
    Hong Kong
  • ISSN
    1051-4651
  • Print_ISBN
    0-7695-2521-0
  • Type

    conf

  • DOI
    10.1109/ICPR.2006.995
  • Filename
    1699608