Centre de documentation
scientifique

Dépouillements

Digital camera calibration for cultural heritage documentation: the case study of a mass digitization project of religious monuments in Cyprus / Evagoras Evagorou in European journal of remote sensing, vol 54 sup 1 (2021)  

Public [article]  inEuropean journal of remote sensing > vol 54 sup 1 (2021) . - pp 6 - 17 Titre : Digital camera calibration for cultural heritage documentation: the case study of a mass digitization project of religious monuments in Cyprus Type de document : Article/Communication Auteurs : Evagoras Evagorou, Auteur ; Christodoulos Mettas, Auteur ; Athos Agapiou, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 6 - 17 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Acquisition d'image(s) et de donnée(s) [Termes IGN] Agisoft Photoscan [Termes IGN] auto-étalonnage [Termes IGN] Chypre [Termes IGN] distorsion d'image [Termes IGN] données massives [Termes IGN] édifice religieux [Termes IGN] étalonnage d'instrument [Termes IGN] patrimoine culturel [Termes IGN] point d'appui [Termes IGN] texture d'image [Termes IGN] vision par ordinateur [Termes IGN] visualisation 3D Résumé : (auteur) The paper summarizes the methodology followed, to evaluate the accuracy of different digitization methods of ecclesiastical monuments in 3D computer vision form and stresses the importance of photographic equipment calibration. In this study, a set of images were taken using the CANON EOS M5 digital camera, while the internal calibration parameters – horizontal and vertical focal length (fx, fy), principal point coordinates (x0, y0), radial distortion coefficients (K1, K2, K3), tangential distortion coefficients (P1, P2) and the affinity and the shear terms (b1, b2) were estimated. These parameters were calculated using different software applications and then analyzed. For the calibration procedure, 3D texture models were built with the Agisoft commercial software based on: (a) the aforementioned calibration parameters and (b) the self-calibration process. The overall accuracy (Root Mean Square – RMS) between these models, by comparing known geo-referenced ground-control-points (GCP) is presented through the Cloud Compare software. The results indicate that the internal calibration parameters of the digital camera used for documentation purposes are essential and should be systematically implemented for documentation purposes. Numéro de notice : A2021-816 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Atlas DOI : 10.1080/22797254.2020.1810131 Date de publication en ligne : 02/09/2020 En ligne : https://doi.org/10.1080/22797254.2020.1810131 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98902 [article]

Fluvial gravel bar mapping with spectral signal mixture analysis / Liza Stančič in European journal of remote sensing, vol 54 sup 1 (2021)  

Public [article]  inEuropean journal of remote sensing > vol 54 sup 1 (2021) . - pp 31 - 46 Titre : Fluvial gravel bar mapping with spectral signal mixture analysis Type de document : Article/Communication Auteurs : Liza Stančič, Auteur ; Krištof Oštir, Auteur ; Žiga Kokalj, Auteur Année de publication : 2021 Article en page(s) : pp 31 - 46 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] analyse des mélanges spectraux [Termes IGN] bassin hydrographique [Termes IGN] carte thématique [Termes IGN] gravier [Termes IGN] image Landsat [Termes IGN] image Sentinel-MSI [Termes IGN] précision infrapixellaire [Termes IGN] réflectance spectrale [Termes IGN] rivière [Termes IGN] signature spectrale [Termes IGN] Slovénie Résumé : (auteur) The paper presents a method for mapping fluvial gravel bars based on Sentinel-2 and Landsat imagery. The proposed method therefore uses spectral signal mixture analysis (SSMA) because its results allow the development of land cover fraction maps for surface water, gravel, and vegetation. The method is validated on a spatially heterogeneous mountainous area in the upper Soča river basin in north-west Slovenia, Central Europe. Unmixing results in highly accurate fraction maps with MAE of around 0.1. Gravel fractions are mapped the most accurately, indicating that the approach can be used successfully for fluvial gravel bar mapping. Endmember sets selected automatically perform slightly worse (MAE higher by at most 0.05) than sets selected manually based on high resolution reference data. Both Sentinel-2 and Landsat imagery can be used for accurate mapping with differences between the two remote sensing systems within 0.05 MAE. For the study area, the SSMA-based soft classification method is more accurate for land cover mapping than a Spectral Angle Mapping-based hard classification. The method is promising for an effective use in other cases where highly accurate subpixel information is needed, because it is able to detect small-scale changes that could go unnoticed with hard classification mapping. Numéro de notice : A2021-817 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1080/22797254.2020.1811776 Date de publication en ligne : 30/08/2020 En ligne : https://doi.org/10.1080/22797254.2020.1811776 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98906 [article]