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Article

Variational Bayesian Pansharpening with Super-Gaussian Sparse Image Priors

1
Departamento de Ciencias de la Computación e Inteligencia Artificial, Universidad de Granada, 18071 Granada, Spain
2
Departamento de Lenguajes y Sistemas Informáticos, Universidad de Granada, 18071 Granada, Spain
3
Department of Electrical Engineering and Computer Science, Northwestern University, Evanston, IL 60208-3118, USA
*
Author to whom correspondence should be addressed.
Sensors 2020, 20(18), 5308; https://doi.org/10.3390/s20185308
Received: 21 July 2020 / Revised: 8 September 2020 / Accepted: 11 September 2020 / Published: 16 September 2020
(This article belongs to the Special Issue Digital Imaging with Multispectral Filter Array (MSFA) Sensors)
Pansharpening is a technique that fuses a low spatial resolution multispectral image and a high spatial resolution panchromatic one to obtain a multispectral image with the spatial resolution of the latter while preserving the spectral information of the multispectral image. In this paper we propose a variational Bayesian methodology for pansharpening. The proposed methodology uses the sensor characteristics to model the observation process and Super-Gaussian sparse image priors on the expected characteristics of the pansharpened image. The pansharpened image, as well as all model and variational parameters, are estimated within the proposed methodology. Using real and synthetic data, the quality of the pansharpened images is assessed both visually and quantitatively and compared with other pansharpening methods. Theoretical and experimental results demonstrate the effectiveness, efficiency, and flexibility of the proposed formulation. View Full-Text
Keywords: pansharpening; variational Bayesian; image fusion; super-Gaussians pansharpening; variational Bayesian; image fusion; super-Gaussians
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MDPI and ACS Style

Pérez-Bueno, F.; Vega, M.; Mateos, J.; Molina, R.; Katsaggelos, A.K. Variational Bayesian Pansharpening with Super-Gaussian Sparse Image Priors. Sensors 2020, 20, 5308. https://doi.org/10.3390/s20185308

AMA Style

Pérez-Bueno F, Vega M, Mateos J, Molina R, Katsaggelos AK. Variational Bayesian Pansharpening with Super-Gaussian Sparse Image Priors. Sensors. 2020; 20(18):5308. https://doi.org/10.3390/s20185308

Chicago/Turabian Style

Pérez-Bueno, Fernando, Miguel Vega, Javier Mateos, Rafael Molina, and Aggelos K. Katsaggelos. 2020. "Variational Bayesian Pansharpening with Super-Gaussian Sparse Image Priors" Sensors 20, no. 18: 5308. https://doi.org/10.3390/s20185308

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