Fusion of multitemporal and multiresolution remote sensing data and application to natural disasters

Ihsen Hedhli 1, * Gabriele Moser 2 Josiane Zerubia 1 Sebastiano B. Serpico 2
* Auteur correspondant
1 AYIN - Models of spatio-temporal structure for high-resolution image processing
CRISAM - Inria Sophia Antipolis - Méditerranée
2 DIBE - Department of Biophysical and Electronic Engineering [Genoa]
Abstract : In this paper, we propose a novel method to fuse multidate, multiresolution, and multiband remote sensing imagery for multitemporal classification purposes. The proposed method is based on an explicit hierarchical graph-based model that is sufficiently flexible to deal with multisource coregistered time series of images collected at different spatial resolutions. An especially novel element of the proposed approach is the use of multiple quad-trees in cascade, each associated with an image acquired at a different date, with the aim to characterize the temporal correlations associated with distinct images in an input time series. Experimental results are shown with multitemporal and multiresolution Pléiades data.
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Communication dans un congrès
IEEE IGARSS - International Geoscience and Remote Sensing Symposium, Jul 2014, Québec, Canada. 2014
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Dernière modification le : samedi 27 janvier 2018 - 01:31:39
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Ihsen Hedhli, Gabriele Moser, Josiane Zerubia, Sebastiano B. Serpico. Fusion of multitemporal and multiresolution remote sensing data and application to natural disasters. IEEE IGARSS - International Geoscience and Remote Sensing Symposium, Jul 2014, Québec, Canada. 2014. 〈hal-01022380〉

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