Super Resolution of Multispectral Images Using TV Image Models

Authors:
Miguel Vega;Javier Mateos;Rafael Molina;Aggelos K. Katsaggelos
Affiliations:
Dpto. de Lenguajes y Sistemas Informáticos, Universidad de Granada, Granada, Spain 18071;Dpto. de Ciencias de la Computación e Inteligencia Artificial, Universidad de Granada, Granada, Spain 18071;Dpto. de Ciencias de la Computación e Inteligencia Artificial, Universidad de Granada, Granada, Spain 18071;Department of Electrical Engineering and Computer Science, Northwestern University, Evanston, USA 60208
Venue:
KES '08 Proceedings of the 12th international conference on Knowledge-Based Intelligent Information and Engineering Systems, Part III
Year:
2008

Citing 2
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Abstract

In this paper we propose a novel algorithm for the pansharpening of multispectral images based on the use of a Total Variation (TV) image prior. Within the Bayesian formulation, the proposed methodology incorporates prior knowledge on the expected characteristics of multispectral images, and uses the sensor characteristics to model the observation process of both panchromatic and multispectral images. Using real and synthetic data, the pansharpened multispectral images are compared with the images obtained by other pansharpening methods and their quality is assessed both qualitatively and quantitatively.