Segmentation of networks from VHR remote sensing images using a directed phase field HOAC model

Aymen El Ghoul 1 Ian Jermyn 1 Josiane Zerubia 1
1 ARIANA - Inverse problems in earth monitoring
CRISAM - Inria Sophia Antipolis - Méditerranée , SIS - Signal, Images et Systèmes
Abstract : We propose a new algorithm for network segmentation from very high resolution (VHR) remote sensing images. The algorithm performs this task quasi-automatically, that is, with no human intervention except to fix some parameters. The task is made difficult by the amount of prior knowledge about network region geometry needed to perform the task, knowledge that is usually provided by a human being. To include such prior knowledge, we make use of methodological advances in region modelling: a phase field higher order active contour of directed networks is used as the prior model for region geometry. By adjoining an approximately conserved flow to a phase field model encouraging network shapes (i.e. regions composed of branches meeting at junctions), the model favours network regions in which different branches may have very different widths, but in which width change along a branch is slow; in which branches do not come to an end, hence tending to close gaps in the network; and in which junctions show approximate ‘conservation of width'. We also introduce image models for network and background, which are validated using maximum likelihood segmentation against other possibilities. We then test the full model on VHR optical and multispectral satellite images.
Type de document :
Communication dans un congrès
ISPRS Technical Commission III Symposium on Photogrammetry Computer Vision and Image Analysis (PCV 2010), Sep 2010, Paris, France. 2010
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Dernière modification le : mercredi 4 août 2010 - 16:00:58
Document(s) archivé(s) le : vendredi 17 septembre 2010 - 13:34:02

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Aymen El Ghoul, Ian Jermyn, Josiane Zerubia. Segmentation of networks from VHR remote sensing images using a directed phase field HOAC model. ISPRS Technical Commission III Symposium on Photogrammetry Computer Vision and Image Analysis (PCV 2010), Sep 2010, Paris, France. 2010. <inria-00491017>

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