Super Resolution of Multispectral Images using ?1 Image Models and Interband Correlations |
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Authors: | Miguel Vega Javier Mateos Rafael Molina Aggelos K Katsaggelos |
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Affiliation: | 1.Dept. de Lenguajes y Sistemas Informáticos,Universidad de Granada,Granada,Spain;2.Dept. de Ciencias de la Computación e I. A.,Universidad de Granada,Granada,Spain;3.Dept. of Electrical Engineering and Computer Science,Northwestern University,Evanston,USA |
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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. |
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