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Fusion of hyperspectral and panchromatic data by spectral unmixing in the reflective domain

Abstract : Earth observation at a local scale requires images having both high spatial and spectral resolutions. As sensors cannot simultaneously provide such characteristics, a solution is combining images jointly acquired by two different optical instruments. Notably, hyperspectral pansharpening methods combine a panchromatic image, providing a high spatial resolution, with a hyperspectral image, providing a high spectral resolution, to generate an image with both high spatial and spectral resolutions. Nevertheless, these methods suffer from some limitations, including managing mixed pixels. This article introduces a new hyperspectral pansharpening method designed to deal with mixed pixels, which is called Spatially Organized Spectral Unmixing (SOSU). The performance of this method is measured on synthetic then real data (simulated from airborne acquisitions), using spatial, spectral and global criteria, to evaluate the contributions of the SOSU algorithm to mixed pixel processing. In particular, this contribution is confirmed in the case of a peri-urban area via a nearly ten percent increase in the rate of mixed pixels improved with SOSU, in comparison with the method used as a reference.
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Preprints, Working Papers, ...
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Contributor : Cécile André Connect in order to contact the contributor
Submitted on : Friday, January 17, 2020 - 11:13:03 AM
Last modification on : Wednesday, November 3, 2021 - 6:02:56 AM


  • HAL Id : hal-02443504, version 1


Yohann Constans, Sophie Fabre, Henry Brunet, Michael Seymour, Vincent Crombez, et al.. Fusion of hyperspectral and panchromatic data by spectral unmixing in the reflective domain. 2020. ⟨hal-02443504⟩



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