Paper Info
Title
Fusion of multitemporal and multiresolution remote sensing data and application to natural disasters
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 data1.
Year
DOI
Venue
2014
10.1109/IGARSS.2014.6946393
Geoscience and Remote Sensing Symposium
Keywords
Field
DocType
disasters,geophysical image processing,graph theory,image classification,image registration,image resolution,quadtrees,remote sensing,sensor fusion,time series,explicit hierarchical graph-based model,image collection,multiple cascade quadtree,multiresolution Pléiades data,multiresolution remote sensing data fusion,multiresolution remote sensing imagery,multisource coregistered time series,multitemporal Pléiades data,multitemporal classification purpose,multitemporal remote sensing data fusion,natural disaster,spatial resolution,Natural disasters,hierarchical Markov random fields,maximizer of posterior marginals,multiresolution data,supervised classification
Computer vision,Graph,Computer science,Remote sensing,Fusion,Artificial intelligence,Cascade,Fuse (electrical)
Conference
ISSN
Citations 
PageRank 
2153-6996
1
0.36
References 
Authors
9
4
Name
Order
Citations
PageRank
Ihsen Hedhli110.36
Gabriele Moser291976.92
Josiane Zerubia340.99
Serpico, S.B.456048.52