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3D browsing of wide-angle fisheye images under view-dependent perspective correction / Mingyi Huang in Photogrammetric record, vol 37 n° 178 (June 2022)  

Public [article]  inPhotogrammetric record > vol 37 n° 178 (June 2022) . - pp 185 - 207 Titre : 3D browsing of wide-angle fisheye images under view-dependent perspective correction Type de document : Article/Communication Auteurs : Mingyi Huang, Auteur ; Jun Wu, Auteur ; Zhiyong Peng, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 185 - 207 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] classification par réseau neuronal convolutif [Termes IGN] correction d'image [Termes IGN] distorsion d'image [Termes IGN] étalonnage d'instrument [Termes IGN] image hémisphérique [Termes IGN] objectif très grand angulaire [Termes IGN] panorama sphérique [Termes IGN] perspective [Termes IGN] processeur graphique [Termes IGN] projection orthogonale [Termes IGN] projection perspective Résumé : (auteur) This paper presents a novel technique for 3D browsing of wide-angle fisheye images using view-dependent perspective correction (VDPC). First, the fisheye imaging model with interior orientation parameters (IOPs) is established. Thereafter, a VDPC model for wide-angle fisheye images is proposed that adaptively selects correction planes for different areas of the image format. Finally, the wide-angle fisheye image is re-projected to obtain the visual effect of browsing in hemispherical space, using the VDPC model and IOPs of the fisheye camera calibrated using the ideal projection ellipse constraint. The proposed technique is tested on several downloaded internet images with unknown IOPs. Results show that the proposed VDPC model achieves a more uniform perspective correction of fisheye images in different areas, and preserves the detailed information with greater flexibility compared with the traditional perspective projection conversion (PPC) technique. The proposed algorithm generates a corrected image of 512 × 512 pixels resolution at a speed of 58 fps when run on a pure central processing unit (CPU) processor. With an ordinary graphics processing unit (GPU) processor, a corrected image of 1024 × 1024 pixels resolution can be generated at 60 fps. Therefore, smooth 3D visualisation of a fisheye image can be realised on a computer using the proposed algorithm, which may benefit applications such as panorama surveillance, robot navigation, etc. Numéro de notice : A2022-518 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1111/phor.12410 Date de publication en ligne : 10/05/2022 En ligne : https://doi.org/10.1111/phor.12410 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101068 [article]

Estimation of uneven-aged forest stand parameters, crown closure and land use/cover using the Landsat 8 OLI satellite image / Sinan Kaptan in Geocarto international, vol 37 n° 5 ([01/05/2022])  

Public [article]  inGeocarto international > vol 37 n° 5 [01/05/2022] . - pp 1408 - 1425 Titre : Estimation of uneven-aged forest stand parameters, crown closure and land use/cover using the Landsat 8 OLI satellite image Type de document : Article/Communication Auteurs : Sinan Kaptan, Auteur ; Hasan Aksoy, Auteur Année de publication : 2022 Article en page(s) : pp 1408 - 1425 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] classification dirigée [Termes IGN] correction géométrique [Termes IGN] forêt inéquienne [Termes IGN] houppier [Termes IGN] image Landsat-OLI [Termes IGN] occupation du sol [Termes IGN] peuplement forestier [Termes IGN] Turquie [Termes IGN] utilisation du sol Résumé : (Auteur) This study used the Landsat 8 OLI satellite image and the supervised classification method to estimate uneven-aged forest stand parameters and land use/cover. The spatial success of classification was also investigated. The overall success rates and Kappa values of the classification were, respectively, 74.7% and 0.75 for actual structural type, 84.6% and 0.80 for crown closure, and 88.35% and 0.81 for land use class, whereas the spatial success of classification on the forest cover type map was 36.91% for actual structural type, 64.74% for crown closure, and 41.78% for land use/cover class. The results revealed that the Landsat 8 OLI image can be used to identify stand parameters and land use/cover class. However, because the spatial success rates were below 50% for the actual structural type and land use/cover class of the stand types, it is not suitable for use in spatial classification determination for these classes. Numéro de notice : A2022-277 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2020.1765888 Date de publication en ligne : 20/05/2020 En ligne : https://doi.org/10.1080/10106049.2020.1765888 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100795 [article]

Direct photogrammetry with multispectral imagery for UAV-based snow depth estimation / Kathrin Maier in ISPRS Journal of photogrammetry and remote sensing, vol 186 (April 2022)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 186 (April 2022) . - pp 1 - 18 Titre : Direct photogrammetry with multispectral imagery for UAV-based snow depth estimation Type de document : Article/Communication Auteurs : Kathrin Maier, Auteur ; Andrea Nascetti, Auteur ; Ward van Pelt, Auteur ; Gunhild Rosqvist, Auteur Année de publication : 2022 Article en page(s) : pp 1 - 18 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] analyse en composantes principales [Termes IGN] bande infrarouge [Termes IGN] épaisseur [Termes IGN] erreur moyenne quadratique [Termes IGN] géoréférencement direct [Termes IGN] image captée par drone [Termes IGN] image multibande [Termes IGN] manteau neigeux [Termes IGN] modèle numérique de surface [Termes IGN] photogrammétrie aérienne [Termes IGN] positionnement cinématique en temps réel [Termes IGN] qualité du modèle [Termes IGN] reconstruction 3D [Termes IGN] structure-from-motion [Termes IGN] Suède Résumé : (Auteur) More accurate snow quality predictions are needed to economically and socially support communities in a changing Arctic environment. This contrasts with the current availability of affordable and efficient snow monitoring methods. In this study, a novel approach is presented to determine spatial snow depth distribution in challenging alpine terrain that was tested during a field campaign performed in the Tarfala valley, Kebnekaise mountains, northern Sweden, in April 2019. The combination of a multispectral camera and an Unmanned Aerial Vehicle (UAV) was used to derive three-dimensional (3D) snow surface models via Structure from Motion (SfM) with direct georeferencing. The main advantage over conventional photogrammetric surveys is the utilization of accurate Real-Time Kinematic (RTK) positioning which enables direct georeferencing of the images, and therefore eliminates the need for ground control points. The proposed method is capable of producing high-resolution 3D snow-covered surface models (7 cm/pixel) of alpine areas up to eight hectares in a fast, reliable and affordable way. The test sites’ average snow depth was 160 cm with an average standard deviation of 78 cm. The overall Root-Mean-Square Errors (RMSE) of the snow depth range from 11.52 cm for data acquired in ideal surveying conditions to 41.03 cm in aggravated light and wind conditions. Results of this study suggest that the red components in the electromagnetic spectrum, i.e., the red, red edge, and near-infrared (NIR) band, contain the majority of information used in photogrammetric processing. The experiments highlighted a significant influence of the multi-spectral imagery on the quality of the final snow depth estimation as well as a strong potential to reduce processing times and computational resources by limiting the dimensionality of the imagery through the application of a Principal Component Analysis (PCA) before the photogrammetric 3D reconstruction. The proposed method is part of closing the scale gap between discrete point measurements and regional-scale remote sensing and complements large-scale remote sensing data and snow model output with an adequate validation source. Numéro de notice : A2022-066 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2022.01.020 Date de publication en ligne : 09/02/2022 En ligne : https://doi.org/10.1016/j.isprsjprs.2022.01.020 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99783 [article]

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Hybrid georeferencing of images and LiDAR data for UAV-based point cloud collection at millimetre accuracy / Norbert Haala in ISPRS Open Journal of Photogrammetry and Remote Sensing, vol 4 (April 2022)  

Public [article]  inISPRS Open Journal of Photogrammetry and Remote Sensing > vol 4 (April 2022) . - n° 100014 Titre : Hybrid georeferencing of images and LiDAR data for UAV-based point cloud collection at millimetre accuracy Type de document : Article/Communication Auteurs : Norbert Haala, Auteur ; Michael Kölle, Auteur ; Michael Cramer, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 100014 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Photogrammétrie numérique [Termes IGN] aérotriangulation automatisée [Termes IGN] appariement d'images [Termes IGN] collecte de données [Termes IGN] compensation par faisceaux [Termes IGN] données lidar [Termes IGN] géoréférencement direct [Termes IGN] image captée par drone [Termes IGN] orthoimage [Termes IGN] précision millimétrique [Termes IGN] semis de points [Termes IGN] zone d'intérêt Résumé : (auteur) During the last two decades, UAV emerged as standard platform for photogrammetric data collection. Main motivation in that early phase was the cost effective airborne image collection at areas of limited size. This was already feasible by rather simple payloads like an off-the-shelf, compact camera and a navigation-grade GNSS sensor. Meanwhile, dedicated sensor systems enable applications that have not been feasible in the past. One example is the airborne collection of dense 3D point clouds at millimetre accuracies, which will be discussed in our paper. For this purpose, we collect both LiDAR and image data from a joint UAV platform and apply a so-called hybrid georeferencing. This process integrates photogrammetric bundle block adjustment with direct georeferencing of LiDAR point clouds. By these means georeferencing accuracy is improved for the LiDAR point cloud by an order of magnitude. We demonstrate the feasibility of our approach in the context of a project, which aims on monitoring of subsidence of about 10 mm/year. The respective area of interest is defined by a ship lock and its vicinity of mixed use. In that area, multiple UAV flights were captured and evaluated for a period of three years. As our main contribution, we demonstrate that 3D point accuracies at sub-centimetre level can be achieved. This is realized by joint orientation of laser scans and images in a hybrid adjustment framework, which enables accuracies corresponding to the GSD of the captured imagery. Numéro de notice : A2022-236 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1016/j.ophoto.2022.100014Get rights and content Date de publication en ligne : 16/03/2022 En ligne : https://doi.org/10.1016/j.ophoto.2022.100014Get rights and content Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100146 [article]

Traffic sign three-dimensional reconstruction based on point clouds and panoramic images / Minye Wang in Photogrammetric record, vol 37 n° 177 (March 2022)  

Public [article]  inPhotogrammetric record > vol 37 n° 177 (March 2022) . - pp 87 - 110 Titre : Traffic sign three-dimensional reconstruction based on point clouds and panoramic images Type de document : Article/Communication Auteurs : Minye Wang, Auteur ; Rufei Liu, Auteur ; Jiben Yang, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 87 - 110 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] classification par réseau neuronal convolutif [Termes IGN] correction d'image [Termes IGN] extraction de traits caractéristiques [Termes IGN] image panoramique [Termes IGN] lidar mobile [Termes IGN] reconstruction 3D [Termes IGN] semis de points [Termes IGN] signalisation routière Résumé : (auteur) Traffic signs are a very important source of information for drivers and pilotless automobiles. With the advance of Mobile LiDAR System (MLS), massive point clouds have been applied in three-dimensional digital city modelling. However, traffic signs in MLS point clouds are low density, colourless and incomplete. This paper presents a new method for the reconstruction of vertical rectangle traffic sign point clouds based on panoramic images. In this method, traffic sign point clouds are extracted based on arc feature and spatial semantic features analysis. Traffic signs in images are detected by colour and shape features and a convolutional neural network. Traffic sign point cloud and images are registered based on outline features. Finally, traffic sign points match traffic sign pixels to reconstruct the traffic sign point cloud. Experimental results have demonstrated that this proposed method can effectively obtain colourful and complete traffic sign point clouds with high resolution. Numéro de notice : A2022-254 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1111/phor.12398 Date de publication en ligne : 05/03/2022 En ligne : https://doi.org/10.1111/phor.12398 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100217 [article]

Improving local adaptive filtering method employed in radiometric correction of analogue airborne campaigns / Lâmân Lelégard (2022)  

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Semi-automatic reconstruction of object lines using a smartphone’s dual camera / Mohammed Aldelgawy in Photogrammetric record, Vol 36 n° 176 (December 2021)  

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Accuracy assessment of RTK-GNSS equipped UAV conducted as-built surveys for construction site modelling / Sander Varbla in Survey review, Vol 53 n° 381 (November 2021)  

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Multi-objective CNN-based algorithm for SAR despeckling / Sergio Vitale in IEEE Transactions on geoscience and remote sensing, vol 59 n° 11 (November 2021)  

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Robust registration of aerial images and LiDAR data using spatial constraints and Gabor structural features / Bai Zhu in ISPRS Journal of photogrammetry and remote sensing, Vol 181 (November 2021)  

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The polar epipolar rectification / François Darmon in IPOL Journal, Image Processing On Line, vol 11 (2021)  

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Spectral reflectance estimation of UAS multispectral imagery using satellite cross-calibration method / Saket Gowravaram in Photogrammetric Engineering & Remote Sensing, PERS, vol 87 n° 10 (October 2021)  

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Hyperspectral image fusion and multitemporal image fusion by joint sparsity / Han Pan in IEEE Transactions on geoscience and remote sensing, Vol 59 n° 9 (September 2021)  

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Les journées de la Recherche IGN 2021 / Anonyme in Géomatique expert, n° 135 (septembre 2021)

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Evaluation du potentiel des series d’images multi-temporelles optique et radar des satellites Sentinel 1 & 2 pour le suivi d’une zone côtière en contexte tropical: cas de l’estuaire du Cameroun pour la période 2015-2020 / Nourdi Njutapvoui in Revue Française de Photogrammétrie et de Télédétection, n° 223 (mars - décembre 2021)  

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