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A Geometric and Radiometric Simultaneous Correction Model (GRSCM) framework for high-accuracy remotely sensed image preprocessing / Chang Li in Photogrammetric Engineering & Remote Sensing, PERS, vol 83 n° 9 (September 2017)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 83 n° 9 (September 2017) . - pp 621 - 632 Titre : A Geometric and Radiometric Simultaneous Correction Model (GRSCM) framework for high-accuracy remotely sensed image preprocessing Type de document : Article/Communication Auteurs : Chang Li, Auteur ; Hao Xiong, Auteur Année de publication : 2017 Article en page(s) : pp 621 - 632 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] correction d'image [Termes IGN] correction géométrique [Termes IGN] correction radiométrique [Termes IGN] Ransac (algorithme) [Termes IGN] restauration d'image Résumé : (Auteur) The grey value g (x, y) of pixel on radiometric spectrum is regarded as a function of the geometric coordinates (x, y). Hence, there is a unity of opposite relationships between the geometric and radiometric information, such that, these two types of information cannot be separated. Therefore, this paper proposes a novel geometric and radiometric simultaneous correction model (GRSCM) framework inspired and developed from least squares matching (LSM). Based on the Gauss-Markov model, geometric and radiometric correction coefficients are integrated and solved by an iterative method with variable weights in the proposed model. Moreover, many state-of-theart models and methods can be integrated into the proposed general GRSCM framework. In the GRSCM of this paper, RANdom SAmple Consensus (RANSAC), stepwise regression and significance testing are integrated and used. The experimental results demonstrate that the accuracy of the GRSCM is significantly improved compared with that of geometric correction and radiometric correction separately. Numéro de notice : A2017-608 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.83.9.621 En ligne : https://doi.org/10.14358/PERS.83.9.621 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=86886 [article]