The sharpening of hyperspectral (HS) images introduces novel questions that have never been faced by classical pansharpening, which deals with the fusion of multispectral and panchromatic images. In this paper, we focus on the fusion of high resolution MultiSpectral (MS) and low resolution HS data, namely tackling the problem of assigning the optimal MS channel for each HS band through the minimization of the Spectral Angle Mapper (SAM) metric. The performance is assessed on two datasets, both composed by a HS and a MS image acquired by the Hyperion and the ALI sensors, respectively. Several MultiResolution Analysis pansharpening approaches are used for evaluating the performance improvements with respect to existing methods.

Multispectral and hyperspectral data fusion based on SAM minimization band assignment approach

Picone, D.;Restaino, R.;Vivone, G.;Addesso, P.;Dalla Mura, M.;
2016-01-01

Abstract

The sharpening of hyperspectral (HS) images introduces novel questions that have never been faced by classical pansharpening, which deals with the fusion of multispectral and panchromatic images. In this paper, we focus on the fusion of high resolution MultiSpectral (MS) and low resolution HS data, namely tackling the problem of assigning the optimal MS channel for each HS band through the minimization of the Spectral Angle Mapper (SAM) metric. The performance is assessed on two datasets, both composed by a HS and a MS image acquired by the Hyperion and the ALI sensors, respectively. Several MultiResolution Analysis pansharpening approaches are used for evaluating the performance improvements with respect to existing methods.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11386/4707390
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