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Comparison and analysis of results of 3D modelling of complex cultural and historical objects using different types of terrestrial laser scanner / Admir Mulahusic in Survey review, vol 52 n° 371 (March 2020)  

Public [article]  inSurvey review > vol 52 n° 371 (March 2020) . - pp 107-114 Titre : Comparison and analysis of results of 3D modelling of complex cultural and historical objects using different types of terrestrial laser scanner Type de document : Article/Communication Auteurs : Admir Mulahusic, Auteur ; Nedim Tuno, Auteur ; Dubravko Gajski, Auteur ; Jusuf Topoljak, Auteur Année de publication : 2020 Article en page(s) : pp 107-114 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes descripteurs IGN] balayage laser [Termes descripteurs IGN] Croatie [Termes descripteurs IGN] impulsion laser [Termes descripteurs IGN] logiciel de reconstruction 3D [Termes descripteurs IGN] modélisation 3D [Termes descripteurs IGN] monument historique [Termes descripteurs IGN] patrimoine culturel [Termes descripteurs IGN] précision géométrique (imagerie) [Termes descripteurs IGN] télémétrie laser terrestre [Termes descripteurs IGN] traitement de données Résumé : (auteur) Laser scanning does not provide unlimited geometrical accuracy and integrity when scanning complex objects. Scanning systems have a minimum and maximum range in which they operate, depending on the technical characteristics. Scanning below or above these limits results in gross errors and registering of incorrect data. Laser scanners can have difficulties with certain materials such as marble and reflective surfaces. This paper presents the results of laser scanning of a complex monument of cultural and historical heritage using two different types of terrestrial laser scanners. Afterwards, the comparison and analysis of the results are shown. The scanners used were terrestrial laser scanners Faro Focus 3D (phase mode distance measurements) and STONEX X300 (pulse mode distance measurements). Numéro de notice : A2020-073 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/00396265.2018.1528758 date de publication en ligne : 09/10/2018 En ligne : https://doi.org/10.1080/00396265.2018.1528758 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94638 [article]

Optimising drone flight planning for measuring horticultural tree crop structure / Yu-Hsuan Tu in ISPRS Journal of photogrammetry and remote sensing, vol 160 (February 2020)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 160 (February 2020) . - pp 83 - 96 Titre : Optimising drone flight planning for measuring horticultural tree crop structure Type de document : Article/Communication Auteurs : Yu-Hsuan Tu, Auteur ; Stuart Phinn, Auteur ; Kasper Johansen, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 83 - 96 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Photogrammétrie numérique [Termes descripteurs IGN] correction d'image [Termes descripteurs IGN] détection d'arbres [Termes descripteurs IGN] distorsion d'image [Termes descripteurs IGN] étalonnage de chambre métrique [Termes descripteurs IGN] horticulture [Termes descripteurs IGN] image de drone [Termes descripteurs IGN] MicMac [Termes descripteurs IGN] obturateur [Termes descripteurs IGN] photogrammétrie aérienne [Termes descripteurs IGN] plan de vol [Termes descripteurs IGN] point d'appui [Termes descripteurs IGN] qualité d'image [Termes descripteurs IGN] Queensland (Australie) Résumé : (Auteur) In recent times, multi-spectral drone imagery has proved to be a useful tool for measuring tree crop canopy structure. In this context, establishing the most appropriate flight planning variable settings is an essential consideration due to their controls on the quality of the imagery and derived maps of tree and crop biophysical properties. During flight planning, variables including flight altitude, image overlap, flying direction, flying speed and solar elevation, require careful consideration in order to produce the most suitable drone imagery. Previous studies have assessed the influence of individual variables on image quality, but the interaction of multiple variables has yet to be examined. This study assesses the influence of several flight variables on measures of data quality in each processing step, i.e. photo alignment, point cloud densification, 3D model building, and ortho-mosaicking. The analysis produced a drone flight planning and image processing workflow that delivers accurate measurements of tree crops, including the tie point quality, densified point cloud density, and the measurement accuracy of height and plant projective cover derived from individual trees within a commercial avocado orchard. Results showed that flying along the hedgerow, at high solar elevation and with low image pitch angles improved the data quality. Optimal flying speed needs to be set to achieve the required forward overlap. The impacts of each image acquisition variable are discussed in detail and protocols for flight planning optimisation for three scenarios with different drone settings are suggested. Establishing protocols that deliver optimal image acquisitions for the collection of drone data over horticultural tree crops, will create greater confidence in the accuracy of subsequent algorithms and resultant maps of biophysical properties. Numéro de notice : A2020-044 Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2019.12.006 date de publication en ligne : 18/12/2019 En ligne : https://doi.org/10.1016/j.isprsjprs.2019.12.006 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94524 [article]

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Geometric accuracy improvement of WorldView‐2 imagery using freely available DEM data / Mateo Gašparović in Photogrammetric record, vol 34 n° 167 (September 2019)  

Public [article]  inPhotogrammetric record > vol 34 n° 167 (September 2019) . - pp 266 - 281 Titre : Geometric accuracy improvement of WorldView‐2 imagery using freely available DEM data Type de document : Article/Communication Auteurs : Mateo Gašparović, Auteur ; Dino Dobrinić, Auteur ; Damir Medak, Auteur Année de publication : 2019 Article en page(s) : pp 266 - 281 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques [Termes descripteurs IGN] image à très haute résolution [Termes descripteurs IGN] image ALOS [Termes descripteurs IGN] image panchromatique [Termes descripteurs IGN] image Worldview [Termes descripteurs IGN] modèle numérique de surface [Termes descripteurs IGN] orientation du capteur [Termes descripteurs IGN] orthorectification [Termes descripteurs IGN] point d'appui [Termes descripteurs IGN] précision géométrique (imagerie) Résumé : (auteur) This paper provides geometric accuracy improvements for very highresolution WorldView-2 (WV2) Ortho Ready Standard Level-2A (ORS2A) satelliteimages in the panchromatic (PAN) band. The entire process can be divided intotwo steps: (1) sensor orientation, which was conducted on 40 ground controlpoints (GCPs) to determine which sensor model was best depending on variousnumbers of GCPs; and (2) orthorectification, whose main objective was tocompare the accuracy of the process when using different freely available globaldigital elevation models (DEMs). The research showed that a sensor model basedon rational polynomial coefficients (RPCs) with a shift or zero-order biascorrection attained the best geopositioning accuracy during the orientation stepwith the use of seven GCPs. The highest accuracy was achieved for imagesorthorectified with the ALOS World 3D-30 m DEM (AW3D30). Numéro de notice : A2019-432 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/phor.12292 date de publication en ligne : 10/10/2019 En ligne : https://doi.org/10.1111/phor.12292 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93759 [article]

Vehicle detection in aerial images / Michael Ying Yang in Photogrammetric Engineering & Remote Sensing, PERS, vol 85 n° 4 (avril 2019)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 85 n° 4 (avril 2019) . - pp 297 - 304 Titre : Vehicle detection in aerial images Type de document : Article/Communication Auteurs : Michael Ying Yang, Auteur ; Wentong Liao, Auteur ; Xinbo Li, Auteur ; et al., Auteur Année de publication : 2019 Article en page(s) : pp 297 - 304 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes descripteurs IGN] apprentissage profond [Termes descripteurs IGN] compréhension de l'image [Termes descripteurs IGN] détection d'objet [Termes descripteurs IGN] entropie [Termes descripteurs IGN] image aérienne [Termes descripteurs IGN] orthoimage [Termes descripteurs IGN] précision de la classification [Termes descripteurs IGN] qualité d'image [Termes descripteurs IGN] réseau neuronal convolutif [Termes descripteurs IGN] véhicule automobile Résumé : (Auteur) The detection of vehicles in aerial images is widely applied in many applications. Comparing with object detection in the ground view images, vehicle detection in aerial images remains a challenging problem because of small vehicle size and the complex background. In this paper, we propose a novel double focal loss convolutional neural network (DFL-CNN) framework. In the proposed framework, the skip connection is used in the CNN structure to enhance the feature learning. Also, the focal loss function is used to substitute for conventional cross entropy loss function in both of the region proposal network (RPN) and the final classifier. We further introduce the first large-scale vehicle detection dataset ITCVD with ground truth annotations for all the vehicles in the scene. We demonstrate the performance of our model on the existing benchmark German Aerospace Center (DLR) 3K dataset as well as the ITCVD dataset. The experimental results show that our DFL-CNN outperforms the baselines on vehicle detection. Numéro de notice : A2019-163 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.85.4.297 date de publication en ligne : 01/04/2019 En ligne : https://doi.org/10.14358/PERS.85.4.297 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92568 [article]

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3-D deep learning approach for remote sensing image classification / Amina Ben Hamida in IEEE Transactions on geoscience and remote sensing, vol 56 n° 8 (August 2018)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 56 n° 8 (August 2018) . - pp 4420 - 4434 Titre : 3-D deep learning approach for remote sensing image classification Type de document : Article/Communication Auteurs : Amina Ben Hamida, Auteur ; Alexandre Benoit, Auteur ; Patrick Lambert, Auteur ; Chokri Ben Amar, Auteur Année de publication : 2018 Article en page(s) : pp 4420 - 4434 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes descripteurs IGN] apprentissage profond [Termes descripteurs IGN] image hyperspectrale [Termes descripteurs IGN] qualité géométrique (image) [Termes descripteurs IGN] valeur radiométrique Résumé : (Auteur) Recently, a variety of approaches have been enriching the field of remote sensing (RS) image processing and analysis. Unfortunately, existing methods remain limited to the rich spatiospectral content of today's large data sets. It would seem intriguing to resort to deep learning (DL)-based approaches at this stage with regard to their ability to offer accurate semantic interpretation of the data. However, the specificity introduced by the coexistence of spectral and spatial content in the RS data sets widens the scope of the challenges presented to adapt DL methods to these contexts. Therefore, the aim of this paper is first to explore the performance of DL architectures for the RS hyperspectral data set classification and second to introduce a new 3-D DL approach that enables a joint spectral and spatial information process. A set of 3-D schemes is proposed and evaluated. Experimental results based on well-known hyperspectral data sets demonstrate that the proposed method is able to achieve a better classification rate than state-of-the-art methods with lower computational costs. Numéro de notice : A2018-470 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2018.2818945 date de publication en ligne : 20/04/2018 En ligne : https://doi.org/10.1109/TGRS.2018.2818945 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91252 [article]

Toward automatic georeferencing of archival aerial photogrammetric surveys / Sébastien Giordano in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, IV-2 ([28/05/2018])  

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No-reference image quality assessment for image auto-denoising / Xiangfei Kong in International journal of computer vision, vol 126 n° 5 (May 2018)  

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Des exigences techniques de qualité pour l'exploitation des images / Laurent Polidori in Géomètre, n° 2156 (mars 2018)

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Foveon VS Bayer: Comparison of 3D reconstruction performances / Pierre Bodin (2018) 

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GNSS-assisted accurate corridor mapping with small UAV / Yilin Zhou (2018)    

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Large-scale block adjustment without use of ground control points based on the compensation of geometric calibration for ZY-3 images / Yang Bo in ISPRS Journal of photogrammetry and remote sensing, vol 134 (December 2017)  

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Estudio de precision en la aerotriangulacion de bloques de imagenes obtenidas con UAV / Miguel Angel Lopez Gonzalez in Mapping : Teledetección, medio ambiante, cartografía, sistemas de información geográfica, vol 26 n° 185 (septembrie - octubre 2017)    

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Using landsat surface reflectance data as a reference target for multiswath hyperspectral data collected over mixed agricultural rangeland areas / Cooper McCann in IEEE Transactions on geoscience and remote sensing, vol 55 n° 9 (September 2017)  

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Evaluation of pan-sharpening methods for spatial and spectral quality / Jagalingam Pushparaj in Applied geomatics, vol 9 n° 1 (March 2017)  

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Geometric accuracy evaluation of YG-18 satellite imagery based on RFM / Ruishan Zhao in Photogrammetric record, vol 32 n° 157 (March - May 2017)  

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