ICIP 2006, Atlanta, GA
 

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Paper:TP-L4.8
Session:Super-Resolution
Time:Tuesday, October 10, 17:00 - 17:20
Presentation: Lecture
Title: PARAMETER ESTIMATION IN BAYESIAN RECONSTRUCTION OF MULTISPECTRAL IMAGES USING SUPER RESOLUTION TECHNIQUES
Authors: Rafael Molina; University of Granada 
 Miguel Vega; University of Granada 
 Javier Mateos; University of Granada 
 Aggelos K. Katsaggelos; Northwestern University 
Abstract: In this paper we present a new super resolution Bayesian method for pansharpening of multispectral images which: a) incorporates prior knowledge on the expected characteristics of the multispectral images, b) uses the sensor characteristics to model the observation process of both panchromatic and multispectral images, and c) performs the estimation of all the unknown parameters in the model. Using real data, the pansharpened multispectral images are compared with the images obtained by other parsharpening methods and their quality is assessed both qualitatively and quantitatively.