This paper presents a solution to the problem of enhancing the spatial resolution of multispectral images with highresolution panchromatic observations. The proposed method exploits a Weighted Least Squares estimator to calculate injection parameters in the fusion model. For each pixel of the image a weight is calculated by a classification map. The classifier used in the experiments is a Support Vector Machine in order to obtain high accuracy on each land-cover type. Results are presented and discussed on very-high resolution images acquired by Quickbird and Ikonos satellite systems. Fusion simulations on spatially degraded data and fusion tests at full scale reveal that an accurate and reliable PAN-sharpening is achieved by the proposed method.

Nencini, F., Capobianco, L., & Garzelli, A. (2008). Weighted Least Squares Pan-Sharpening of Very High Resolution Multispectral Images. In Proc. IEEE IGARSS'08 (pp.65-68). IEEE [10.1109/IGARSS.2008.4780028].

Weighted Least Squares Pan-Sharpening of Very High Resolution Multispectral Images

GARZELLI, ANDREA
2008

Abstract

This paper presents a solution to the problem of enhancing the spatial resolution of multispectral images with highresolution panchromatic observations. The proposed method exploits a Weighted Least Squares estimator to calculate injection parameters in the fusion model. For each pixel of the image a weight is calculated by a classification map. The classifier used in the experiments is a Support Vector Machine in order to obtain high accuracy on each land-cover type. Results are presented and discussed on very-high resolution images acquired by Quickbird and Ikonos satellite systems. Fusion simulations on spatially degraded data and fusion tests at full scale reveal that an accurate and reliable PAN-sharpening is achieved by the proposed method.
9781424428083
Nencini, F., Capobianco, L., & Garzelli, A. (2008). Weighted Least Squares Pan-Sharpening of Very High Resolution Multispectral Images. In Proc. IEEE IGARSS'08 (pp.65-68). IEEE [10.1109/IGARSS.2008.4780028].
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11365/5488
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