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Journal of Signal Processing Systems

, Volume 65, Issue 3, pp 509–523 | Cite as

Super Resolution of Multispectral Images using ℓ1 Image Models and Interband Correlations

  • Miguel Vega
  • Javier Mateos
  • Rafael Molina
  • Aggelos K. Katsaggelos
Article

Abstract

In this paper we propose a novel super-resolution based algorithm for the pansharpening of multispectral images. Within the Bayesian formulation, the proposed methodology incorporates prior knowledge on the expected characteristics of multispectral images; that is, it imposes smoothness within each band by means of the energy associated with the ℓ1 norm of vertical and horizontal first order differences of image pixel values and also takes into account the correlation among the bands of the multispectral image. The observation process is modeled using the sensor characteristics of both panchromatic and multispectral images. The method is tested on real and synthetic images, compared with other pansharpening methods, and the quality of the results assessed both qualitatively and quantitatively.

Keywords

Pansharpening Super-resolution Multispectral images Bayesian approach Variational methods ℓ1 image models Interband correlations 

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Copyright information

© Springer Science+Business Media, LLC 2010

Authors and Affiliations

  • Miguel Vega
    • 1
  • Javier Mateos
    • 2
  • Rafael Molina
    • 2
  • Aggelos K. Katsaggelos
    • 3
  1. 1.Dept. de Lenguajes y Sistemas InformáticosUniversidad de GranadaGranadaSpain
  2. 2.Dept. de Ciencias de la Computación e I. A.Universidad de GranadaGranadaSpain
  3. 3.Dept. of Electrical Engineering and Computer ScienceNorthwestern UniversityEvanstonUSA

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