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Shadow detection and correction using a combined 3D GIS and image processing approach / Safa Ridene in Revue internationale de géomatique, vol 29 n° 3 - 4 (juillet - décembre 2019)  

Public [article]  inRevue internationale de géomatique > vol 29 n° 3 - 4 (juillet - décembre 2019) . - pp 241 - 253 Titre : Shadow detection and correction using a combined 3D GIS and image processing approach Type de document : Article/Communication Auteurs : Safa Ridene, Auteur ; Reda Yaagoubi, Auteur ; Imane Sebari, Auteur ; Audrey Alajouanine, Auteur Année de publication : 2019 Article en page(s) : pp 241 - 253 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] détection d'ombre [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] Matlab [Termes IGN] ModelBuilder [Termes IGN] orthophotographie [Termes IGN] SIG 3D [Termes IGN] Toulouse Résumé : (Auteur) While shadow can give useful information about size and shape of objects, it can pose problems in feature detection and object detection, thereby, it represents one of the major perturbator phenomenons frequently occurring on images and unfortunately, it is inevitable. “Shadows may lead to the failure of image analysis processes and also cause a poor quality of information which in turn leads to problems in implementation of algorithms.” (Mahajan and Bajpayee, 2015). It also affects multiple image analysis applications, whereby shadow cast by buildings deteriorate the spectral values of the surfaces. Therefore, its presence causes a deterioration in the visual image's quality and limits the information that the former could give. Ignoring the existence of shadows in images may cause serious problems in various visual processing applications such as false objects detection. In this context, many researches have been conducted through years. However, it is still a challenge for analysts all over the world to find a fully automated and efficient method for shadow removal from images. Numéro de notice : A2019-640 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3166/rig.2019.00091 Date de publication en ligne : 03/08/2020 En ligne : https://doi.org/10.3166/rig.2019.00091 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95649 [article]

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