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Automatic satellite image georeferencing using a contour-matching approach / Francisco Eugenio in IEEE Transactions on geoscience and remote sensing, vol 41 n° 12 (December 2003)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 41 n° 12 (December 2003) . - pp 2869 - 2880 Titre : Automatic satellite image georeferencing using a contour-matching approach Type de document : Article/Communication Auteurs : Francisco Eugenio, Auteur ; F. Marques-, Auteur Année de publication : 2003 Article en page(s) : pp 2869 - 2880 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques [Termes IGN] contour [Termes IGN] correction géométrique [Termes IGN] détection de contours [Termes IGN] extraction automatique [Termes IGN] géoréférencement [Termes IGN] image multicapteur [Termes IGN] image multitemporelle [Termes IGN] image NOAA-AVHRR [Termes IGN] image Seawifs Résumé : (Auteur) Multitemporal and multisatellite studies or comparisons between satellite data and local ground measurements require nowadays precise and automatic geometric correction of satellite images. This paper presents a fully automatic geometric correction system capable of georeferencing satellite images with high accuracy. An orbital prediction model, which provides initial earth locations, is combined with the proposed automatic contour-matching technique. This combination allows correcting the low-frequency error component, mainly due to timing and orbital model errors, as well as the high-frequency error component, due to variations in the spacecraft's attitude. The approach aims at exploiting the maximum reliable information in the image to guide the matching algorithm. The contour-matching process has three main steps: 1) estimation of the gradient energy map (edges) and detection of the cloudless (reliable) areas; 2) initialization of the contours positions; 3) estimation of the transformation parameters (affine model) using a contour optimization approach. Three different robust and automatic algorithms are proposed for optimization, and their main features are discussed. Finally, the performance of the three proposed algorithms is assessed using a new error estimation technique applied to Advanced Very High Resolution Radiometer (AVHRR), Sea-viewing Wide Field of view Sensor (SeaWiFS), and multisensor AVHRR-SeaWiFS imagery. Numéro de notice : A2003-382 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2003.817226 En ligne : https://ieeexplore.ieee.org/document/1260624 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=26462 [article]

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