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On the determination of transformation parameters between different ITRS realizations using procrustes approach in Turkey / Mevlut Yetkin in Journal of applied geodesy, vol 11 n° 3 (September 2017)  

Public [article]  inJournal of applied geodesy > vol 11 n° 3 (September 2017) . - pp 123 - 130 Titre : On the determination of transformation parameters between different ITRS realizations using procrustes approach in Turkey Type de document : Article/Communication Auteurs : Mevlut Yetkin, Auteur ; Kutubuddin Ansari, Auteur Année de publication : 2017 Article en page(s) : pp 123 - 130 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Systèmes de référence et réseaux [Termes IGN] analyse procustéenne [Termes IGN] International Terrestrial Reference Frame [Termes IGN] réseau géodésique permanent [Termes IGN] transformation de coordonnées [Termes IGN] transformation de Helmert [Termes IGN] Turquie Résumé : (Auteur) The International Terrestrial Reference Frame (ITRF) solutions that are published by the International Earth Rotation and Reference Systems Service (IERS) are annual realizations of the ITRS (International Terrestrial Reference System). The results expressed in two different ITRS realizations can be compared using the transformation parameters that provide a link between different ITRF solutions. Generally, the 7-parameter (the three translation parameters, three rotation parameters and one scale factor) Helmert transformation is employed to compute the transformation parameters. However, the number of transformation parameters can be increased for better understanding. For example, 3 different scale factors may be computed instead of one scale factor. In this paper, the 9-parameter (the three translation parameters, three rotation parameters and three scale factors) transformation model and its solution by Procrustes approach is considered. Transformation parameters between ITRF 05 and ITRF 08 for Turkey have been computed in both 7-parameter model and 9-parameter model and a numerical example has been given to understand the difference between two models in a better way. An explanation about the proposed methodology as a flow chart also has been shown in appendix. Numéro de notice : A2017-567 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article DOI : 10.1515/jag-2016-0048 En ligne : https://doi.org/10.1515/jag-2016-0048 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=86687 [article]

Shadow detection and removal in RGB VHR images for land use unsupervised classification / A. Movia in ISPRS Journal of photogrammetry and remote sensing, vol 119 (September 2016)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 119 (September 2016) . - pp 485 - 495 Titre : Shadow detection and removal in RGB VHR images for land use unsupervised classification Type de document : Article/Communication Auteurs : A. Movia, Auteur ; A. Beina, Auteur ; F. Crosilla, Auteur Année de publication : 2016 Article en page(s) : pp 485 - 495 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] analyse comparative [Termes IGN] analyse d'image numérique [Termes IGN] analyse procustéenne [Termes IGN] anisotropie [Termes IGN] classification non dirigée [Termes IGN] détection d'ombre [Termes IGN] détection de changement [Termes IGN] factorisation de Cholesky [Termes IGN] image à très haute résolution [Termes IGN] image RVB Résumé : (Auteur) Nowadays, high resolution aerial images are widely available thanks to the diffusion of advanced technologies such as UAVs (Unmanned Aerial Vehicles) and new satellite missions. Although these developments offer new opportunities for accurate land use analysis and change detection, cloud and terrain shadows actually limit benefits and possibilities of modern sensors. Focusing on the problem of shadow detection and removal in VHR color images, the paper proposes new solutions and analyses how they can enhance common unsupervised classification procedures for identifying land use classes related to the CO2 absorption. To this aim, an improved fully automatic procedure has been developed for detecting image shadows using exclusively RGB color information, and avoiding user interaction. Results show a significant accuracy enhancement with respect to similar methods using RGB based indexes. Furthermore, novel solutions derived from Procrustes analysis have been applied to remove shadows and restore brightness in the images. In particular, two methods implementing the so called “anisotropic Procrustes” and the “not-centered oblique Procrustes” algorithms have been developed and compared with the linear correlation correction method based on the Cholesky decomposition. To assess how shadow removal can enhance unsupervised classifications, results obtained with classical methods such as k-means, maximum likelihood, and self-organizing maps, have been compared to each other and with a supervised clustering procedure. Numéro de notice : A2016-793 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2016.05.004 En ligne : https://doi.org/10.1016/j.isprsjprs.2016.05.004 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=82510 [article]