Multi-band semiblind deconvolution for pansharpening applications

Abstract : Pansharpening consists of fusing a multispectral (MS) image together with a panchromatic (PAN) image with the aim of jointly preserving the spectral diversity of the former and the geometric richness of the latter. A crucial step in pansharpening algorithms is the detail extraction. This problem is usually addressed by the means of 2D Gaussian filters matched with the MS sensor's modulation transfer function (MTF). Nevertheless, several issues can affect this characterization (e.g. the MTF's gains at the Nyquist frequency could be not available or unreliable). Thus, in this paper we propose a technique based on blind image deblurring in order to estimate band-dependent spatial detail extraction filters by taking into consideration the possible variability of the MS spatial features along bands. The validation is carried out exploiting two real datasets acquired by the IKONOS and the QuickBird sensors.
Type de document :
Communication dans un congrès
IEEE International Geoscience and Remote Sensing Symposium (IGARSS 2015), Jul 2015, Milan, Italy. 〈10.1109/IGARSS.2015.7325692〉
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http://hal.univ-grenoble-alpes.fr/hal-01246596
Contributeur : Vincent Couturier-Doux <>
Soumis le : vendredi 18 décembre 2015 - 17:23:47
Dernière modification le : jeudi 11 janvier 2018 - 06:26:25

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Gemine Vivone, R. Restaino, Mauro Dalla Mura, Jocelyn Chanussot. Multi-band semiblind deconvolution for pansharpening applications. IEEE International Geoscience and Remote Sensing Symposium (IGARSS 2015), Jul 2015, Milan, Italy. 〈10.1109/IGARSS.2015.7325692〉. 〈hal-01246596〉

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