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Multispectral Image Pansharpening Based on the Contourlet Transform

  • Israa Amro
  • Javier Mateos
Chapter

Abstract

Pansharpening is a technique that fuses the information of a low-resolution multispectral image and a high-resolution panchromatic image, usually remote sensing images, to provide a high-resolution multispectral image. In the literature, this task has been addressed from different points of view being one of the most popular wavelet-based algorithms. Recently, a new transform, the contourlet transform, has been proposed. This transform combines the advantages of the wavelets transform, with a more efficient directional information representation. The result is a flexible multiscale, multidirection and shift-invariant decomposition that can be efficiently implemented via the a’trous algorithm. In this chapter, we compare the wavelet-based pansharpening with existing contourlet-based approaches and propose a new pansharpening method based on the contourlet transform. The performance of the contourlet in general, and the proposed method in particular, is assessed numerically and visually for Landsat and SPOT images.

Keywords

Multispectral Image Panchromatic Image Directional Filter Bank Universal Image Quality Index Pansharpened Image 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgements

This work has been supported by the Consejería de Innovación, Ciencia y Empresa of the Junta de Andalucía under contract P07-TIC-02698.

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Copyright information

© Springer Science+Business Media, LLC 2010

Authors and Affiliations

  1. 1.Universidad de GranadaGranadaSpain
  2. 2.Al-Quds Open UniversityHepronPalestine

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