Super resolution of multispectral images using ℓ1 image models and interband correlations

Miguel Vega*, Javier Mateos, Rafael Molina, Aggelos K Katsaggelos

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations

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, imposes smoothness within each band by means of the energy associated to the ℓ1 norm of vertical and horizontal first order differences of image pixel values and also takes into account the correlation between 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 its quality is assessed both qualitatively and quantitatively.

Original languageEnglish (US)
Title of host publicationMachine Learning for Signal Processing XIX - Proceedings of the 2009 IEEE Signal Processing Society Workshop, MLSP 2009
DOIs
StatePublished - Dec 1 2009
EventMachine Learning for Signal Processing XIX - 2009 IEEE Signal Processing Society Workshop, MLSP 2009 - Grenoble, France
Duration: Sep 2 2009Sep 4 2009

Publication series

NameMachine Learning for Signal Processing XIX - Proceedings of the 2009 IEEE Signal Processing Society Workshop, MLSP 2009

Other

OtherMachine Learning for Signal Processing XIX - 2009 IEEE Signal Processing Society Workshop, MLSP 2009
CountryFrance
CityGrenoble
Period9/2/099/4/09

ASJC Scopus subject areas

  • Human-Computer Interaction
  • Signal Processing
  • Education

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    Vega, M., Mateos, J., Molina, R., & Katsaggelos, A. K. (2009). Super resolution of multispectral images using ℓ1 image models and interband correlations. In Machine Learning for Signal Processing XIX - Proceedings of the 2009 IEEE Signal Processing Society Workshop, MLSP 2009 [5306217] (Machine Learning for Signal Processing XIX - Proceedings of the 2009 IEEE Signal Processing Society Workshop, MLSP 2009). https://doi.org/10.1109/MLSP.2009.5306217