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Refining high spatial resolution remote sensing image segmentation for man-made objects through acollinear and ipsilateral neighborhood model / Min Wang in Photogrammetric Engineering & Remote Sensing, PERS, vol 81 n° 5 (May 2015)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 81 n° 5 (May 2015) . - pp 397 - 406 Titre : Refining high spatial resolution remote sensing image segmentation for man-made objects through acollinear and ipsilateral neighborhood model Type de document : Article/Communication Auteurs : Min Wang, Auteur ; Yanxia Sun, Auteur ; Guanyi Chen, Auteur Année de publication : 2015 Article en page(s) : pp 397 - 406 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] analyse d'image orientée objet [Termes IGN] détail topographique artificiel [Termes IGN] détection d'objet [Termes IGN] planimétrie [Termes IGN] pouvoir de résolution géométrique [Termes IGN] segmentation d'image Résumé : (auteur) Man-made objects, such as buildings and roads, which are important targets for information extraction from high spatial resolution (HSR) remote sensing images, often feature straight boundaries. This study employs this knowledge on HSR image segmentation by embedding a straight-line constraint in regionbased image segmentation. A new concept called collinear and ipsilateral neighborhood is proposed and applied to hardboundary constraint-based image segmentation for accuracy improvement. In the experimental areas, the method accuracy measured by recall ratio r increases from 0.036 to 0.048 (on the average) after the refinement, with significantly smaller decreases in precision p that are all less than 0.006. In sum, the proposed technique effectively reduces over-segmentation errors and maintains the same level of under-segmentation error ratio, particularly in man-made areas. It facilitates subsequent objectbased image analyses, including feature extraction, object recognition, and classification. Numéro de notice : A2015-974 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : doi.org/10.14358/PERS.81.5.397 En ligne : https://doi.org/10.14358/PERS.81.5.397 Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=80044 [article]