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Technical Program
Paper Detail
| Paper: | TP-L4.8 |
| Session: | Super-Resolution |
| Time: | Tuesday, October 10, 17:00 - 17:20 |
| Presentation: |
Lecture
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| 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. |
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