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Semi-automated extraction of rivers from digital imagery / C.R. Dillabaugh in Geoinformatica, vol 6 n° 3 (September - November 2002)  

Public [article]  inGeoinformatica > vol 6 n° 3 (September - November 2002) . - pp 263 - 284 Titre : Semi-automated extraction of rivers from digital imagery Type de document : Article/Communication Auteurs : C.R. Dillabaugh, Auteur ; K.O. Niemann, Auteur ; D.E. Richardson, Auteur Année de publication : 2002 Article en page(s) : pp 263 - 284 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] détection de contours [Termes IGN] extraction semi-automatique [Termes IGN] image à haute résolution [Termes IGN] image numérique [Termes IGN] image panchromatique [Termes IGN] image SPOT [Termes IGN] réseau hydrographique [Termes IGN] rivière Résumé : (Auteur) The manual production of vector maps from digital imagery can be a time consuming and costly process. Developing tools to automate this task for specific features, such as roads, has become an important research topic. The purpose of this paper was to present a technique for the semi-automatic extraction of multiple pixel width river features appearing in high resolution satellite imagery. This was accomplished using a two stage, multi resolution procedure. Initial river extraction was performed on low resolution (SPOT multispectral 20 m) imagery. The results from this low resolution extraction were then refined on higher resolution (KFA 1000. panchromatic. 5m) imagery to produce a detailed outline of the channel banks. To perform low resolution extraction a cost surface was generated to represent the combined local evidence of the presence of a river feature. The local evidence of a river was evaluated based on the results of a number of simple operators. Then, with user specified start and end points for the network, rivers were extracted by performing a least cost path search across this surface using the A* algorithm. The low resolution results were transferred to the high resolution imagery as closed contours which provided an estimate of the channel banks. These contours were then fit to the channel banks using the dynamic contours (or snakes) technique. Numéro de notice : A2002-205 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1023/A:1019718019825 En ligne : https://doi.org/10.1023/A:1019718019825 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=22120 [article]

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