Super-Resolution of Multispectral Images

Authors: Vega, M.; Mateos, J.; Molina, R.; Katsaggelos, A.K.

Source: Computer Journal, Volume 52, Number 1, 11 January 2009 , pp. 153-167(15)

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Abstract:

In this paper we propose and analyze a globally and locally adaptive super-resolution Bayesian methodology for pansharpening of multispectral images. The methodology incorporates prior knowledge on the expected characteristics of the multispectral images uses the sensor characteristics to model the observation process of both panchromatic and multispectral images and includes information on the unknown parameters in the model in the form of hyperprior distributions. 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.

Keywords: super-resolution; Bayesian models; hyperspectral images

Document Type: Research article

DOI: http://dx.doi.org/10.1093/comjnl/bxn031

Publication date: 2009-01-11

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