• DocumentCode
    1796269
  • Title

    Affinity Pansharpening and Image Fusion

  • Author

    Tierney, Stephen ; Junbin Gao ; Yi Guo

  • Author_Institution
    Sch. of Comput. & Math., Charles Sturt Univ., Bathurst, NSW, Australia
  • fYear
    2014
  • fDate
    25-27 Nov. 2014
  • Firstpage
    1
  • Lastpage
    8
  • Abstract
    A novel framework for enhancing the resolution of a low-resolution multispectral or hyperspectral image using a high resolution panchromatic image or multispectral image is proposed in this paper. This framework can be further used to perform more general types of image fusion. To create the enhanced image, a convex objective function is minimised, which preserves both the pixel affinity learnt from the high resolution image and spectral information from the low resolution image. A fast approximation method is discussed. Quantitive and qualitative analysis against existing methods shows that our method is comparable to state of the art with faster running time and greater flexibility. MATLAB code for our proposed method and the compared methods are freely available in the FuseBox package.
  • Keywords
    hyperspectral imaging; image enhancement; image resolution; mathematics computing; sensor fusion; FuseBox package; MATLAB code; affinity pansharpening; convex objective function; fast approximation method; high resolution image; high resolution panchromatic image; hyperspectral image; image enhancement; image fusion; low resolution image; low-resolution multispectral image; pixel affinity; spectral information; Approximation methods; Image fusion; Principal component analysis; Remote sensing; Satellites; Spatial resolution;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Digital lmage Computing: Techniques and Applications (DlCTA), 2014 International Conference on
  • Conference_Location
    Wollongong, NSW
  • Type

    conf

  • DOI
    10.1109/DICTA.2014.7008094
  • Filename
    7008094