Détail de l'auteur
Auteur Meng Xu |
Documents disponibles écrits par cet auteur (1)
Ajouter le résultat dans votre panier Affiner la recherche Interroger des sources externes
Thin cloud removal based on signal transmission principles and spectral mixture analysis / Meng Xu in IEEE Transactions on geoscience and remote sensing, vol 54 n° 3 (March 2016)
[article]
Titre : Thin cloud removal based on signal transmission principles and spectral mixture analysis Type de document : Article/Communication Auteurs : Meng Xu, Auteur ; Mark Pickering, Auteur ; Antonio J. Plaza, Auteur ; Xiuping Jia, Auteur Année de publication : 2016 Article en page(s) : pp 1659 - 1669 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse des mélanges spectraux
[Termes IGN] classification pixellaire
[Termes IGN] correction d'image
[Termes IGN] épaisseur de nuage
[Termes IGN] nuage
[Termes IGN] rayonnement solaire
[Termes IGN] reconstruction d'imageRésumé : (Auteur) Cloud removal is an important goal for enhancing the utilization of optical remote sensing satellite images. Clouds dynamically affect the signal transmission due to their different shapes, heights, and distribution. In the case of thick opaque clouds, pixel replacement has been commonly adopted. For thin clouds, pixel correction techniques allow the effects of thin clouds to be removed while retaining the remaining information in the contaminated pixels. In this paper, we develop a new method based on signal transmission and spectral mixture analysis for pixel correction which makes use of a cloud removal model that considers not only the additive reflectance from the clouds but also the energy absorption when solar radiation passes through them. Data correction is achieved by subtracting the product of the cloud endmember signature and the cloud abundance and rescaling according to the cloud thickness. The proposed method has no requirement for meteorological data and does not rely on reference images. Our experimental results indicate that the proposed approach is able to perform effective removal of thin clouds in different scenarios. Numéro de notice : A2016-125 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2015.2486780 En ligne : http://dx.doi.org/10.1109/TGRS.2015.2486780 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=80006
in IEEE Transactions on geoscience and remote sensing > vol 54 n° 3 (March 2016) . - pp 1659 - 1669[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 065-2016031 SL Revue Centre de documentation Revues en salle Disponible