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Matching of TerraSAR-X derived ground control points to optical image patches using deep learning / Tatjana Bürgmann in ISPRS Journal of photogrammetry and remote sensing, Vol 158 (December 2019)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > Vol 158 (December 2019) . - pp 241 - 248 Titre : Matching of TerraSAR-X derived ground control points to optical image patches using deep learning Type de document : Article/Communication Auteurs : Tatjana Bürgmann, Auteur ; Wolfgang Koppe, Auteur ; Michael Schmitt, Auteur Année de publication : 2019 Article en page(s) : pp 241 - 248 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image mixte [Termes IGN] appariement d'images [Termes IGN] apprentissage profond [Termes IGN] classification par réseau neuronal convolutif [Termes IGN] géolocalisation [Termes IGN] image multicapteur [Termes IGN] image optique [Termes IGN] image Pléiades [Termes IGN] image radar moirée [Termes IGN] image Sentinel-MSI [Termes IGN] image Sentinel-SAR [Termes IGN] image TerraSAR-X [Termes IGN] point d'appui Résumé : (auteur) High resolution synthetic aperture radar (SAR) satellites like TerraSAR-X are capable of acquiring images exhibiting an absolute geolocation accuracy within a few centimeters, mainly because of the availability of precise orbit information and by compensating range delay errors due to atmospheric conditions. In contrast, satellite images from optical missions generally exhibit comparably low geolocation accuracies because of the propagation of errors in angular measurements over large distances. However, a variety of remote sensing applications, such as change detection, surface movement monitoring or ice flow measurements, require precisely geo-referenced and co-registered satellite images. By using Ground Control Points (GCPs) derived from TerraSAR-X, the absolute geolocation accuracy of optical satellite images can be improved. For this purpose, the corresponding matching points in the optical images need to be localized. In this paper, a deep learning based approach is investigated for an automated matching of SAR-derived GCPs to optical image elements. Therefore, a convolutional neural network is pretrained with medium resolution Sentinel-1 and Sentinel-2 imagery and fine-tuned on precisely co-registered TerraSAR-X and Pléiades training image pairs to learn a common descriptor representation. By using these descriptors, the similarity of SAR and optical image patches can be calculated. This similarity metric is then used in a sliding window approach to identify the matching points in the optical reference image. Subsequently, the derived points can be utilized for co-registration of the underlying images. The network is evaluated over nine study areas showing airports and their rural surroundings from several different countries around the world. The results show that based on TerraSAR-X-derived GCPs, corresponding points in the optical image can automatically and reliably be identified with a pixel-level localization accuracy. Numéro de notice : A2019-548 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2019.09.010 Date de publication en ligne : 05/11/2019 En ligne : https://doi.org/10.1016/j.isprsjprs.2019.09.010 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94194 [article]

Exemplaires(3)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
081-2019121	RAB	Revue	Centre de documentation	En réserve L003	Disponible
081-2019123	DEP-RECP	Revue	LASTIG	Dépôt en unité	Exclu du prêt
081-2019122	DEP-RECF	Revue	Nancy	Dépôt en unité	Exclu du prêt

Synergie des données Sentinel optiques et radar pour l’observation et l’analyse de la végétation du littoral du Pays de Brest / Antoine Billey (2018)  

Public Titre : Synergie des données Sentinel optiques et radar pour l’observation et l’analyse de la végétation du littoral du Pays de Brest Type de document : Mémoire Auteurs : Antoine Billey, Auteur Editeur : Le Mans : Ecole Supérieure des Géomètres et Topographes ESGT Année de publication : 2018 Importance : 62 p. Format : 21 x 30 cm Note générale : bibliographie Mémoire présenté en vue d'obtenir le diplôme d'Ingénieur CNAM spécialité : Géomètre et Topographe Langues : Français (fre) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] Brest [Termes IGN] carte d'occupation du sol [Termes IGN] carte de la végétation [Termes IGN] classification dirigée [Termes IGN] classification par forêts d'arbres décisionnels [Termes IGN] fusion de données [Termes IGN] image multicapteur [Termes IGN] image Sentinel-MSI [Termes IGN] image Sentinel-SAR [Termes IGN] image SPOT 6 [Termes IGN] littoral [Termes IGN] Normalized Difference Vegetation Index [Termes IGN] Normalized Difference Water Index [Termes IGN] série temporelle [Termes IGN] surveillance de la végétation [Termes IGN] télédétection spatiale [Termes IGN] traitement de données Résumé : (auteur) Cartographier la végétation d’un territoire est nécessaire pour le suivi et la gestion des espaces naturels. La cartographie de la végétation intéresse notamment les gestionnaires et les décideurs dans la gestion de territoire et l’aménagement du territoire. Le pays de Brest est un territoire possédant un patrimoine naturel riche et diversifié, lié au climat littoral qui subsiste. De nombreuses méthodes d’élaboration de cartes d’occupations des sols existent, et la télédétection spatiale représente un moyen efficace pour y parvenir.L’objectif de cette étude est de mettre au point une méthode de cartographie pour effectuer le suivi de la végétation du littoral du Pays de Brest à partir des nouvelles données satellites européennes. Note de contenu : Introduction 1- Contexte de l’étude 2- Méthodologie 3- Résultats et discussions Conclusion Numéro de notice : 25724 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Mémoire ingénieur CNAM En ligne : https://dumas.ccsd.cnrs.fr/MEMOIRES-CNAM/dumas-02092722 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94879

Intersensor statistical matching for pansharpening : theoretical issues and practical solutions / Luciano Alparone in IEEE Transactions on geoscience and remote sensing, vol 55 n° 8 (August 2017)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 55 n° 8 (August 2017) . - pp 4682 - 4695 Titre : Intersensor statistical matching for pansharpening : theoretical issues and practical solutions Type de document : Article/Communication Auteurs : Luciano Alparone, Auteur ; Andrea Garzelli, Auteur ; Gemine Vivone, Auteur Année de publication : 2017 Article en page(s) : pp 4682 - 4695 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image mixte [Termes IGN] appariement d'histogramme [Termes IGN] appariement d'images [Termes IGN] image Ikonos [Termes IGN] image multibande [Termes IGN] image multicapteur [Termes IGN] image panchromatique [Termes IGN] image Worldview [Termes IGN] pansharpening (fusion d'images) [Termes IGN] résolution multiple Résumé : (Auteur) In this paper, the authors investigate the statistical matching of the panchromatic (Pan) image to the multispectral (MS) bands, also known as the histogram matching, for the two main classes of pansharpening methods, i.e., those based on component substitution (CS) or spectral methods and those based on multiresolution analysis (MRA) or spatial methods. Also, hybrid methods combining CS with MRA, like the widespread additive wavelet luminance proportional (AWLP), are investigated. It is shown that all spectral, spatial, and hybrid methods must perform a dynamics matching of the enhancing Pan to the individual MS bands for MRA or a combination of them (the component that shall be substituted) for CS. For hybrid methods, the problem is more complex and both types of histogram matching may be suitable. Such an intersensor balance may be either explicit or implicitly performed by the detail-injection model, e.g., the popular projective and multiplicative injection models. An experimental setup exploiting IKONOS and WorldView-2 data sets demonstrates that a correct histogram matching is the key to attain extra performance from established methods. As a first result of this paper, the AWLP method has been revisited and its performance significantly improved by simply performing the histogram matching of Pan to the individual MS bands, rather than to the intensity component, thereby losing the original proportionality feature. Numéro de notice : A2017-502 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2017.2697943 En ligne : http://dx.doi.org/10.1109/TGRS.2017.2697943 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=86447 [article]

Image-based mobile mapping for 3D Urban data capture / Stefan Cavegn in Photogrammetric Engineering & Remote Sensing, PERS, vol 82 n° 12 (December 2016)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 82 n° 12 (December 2016) . - pp 925 - 933 Titre : Image-based mobile mapping for 3D Urban data capture Type de document : Article/Communication Auteurs : Stefan Cavegn, Auteur ; Norbert Haala, Auteur Année de publication : 2016 Article en page(s) : pp 925 - 933 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Photogrammétrie terrestre [Termes IGN] acquisition de données [Termes IGN] appariement d'images [Termes IGN] géoréférencement direct [Termes IGN] image multicapteur [Termes IGN] image terrestre [Termes IGN] lever mobile [Termes IGN] milieu urbain [Termes IGN] reconstruction 3D [Termes IGN] semis de points [Termes IGN] système de numérisation mobile [Termes IGN] télémétrie laser terrestre [Termes IGN] traitement d'image Résumé : (auteur) Ongoing innovations in dense multi-view stereo image matching meanwhile allow for 3D data collection using image sequences captured from mobile mapping platforms even in complex and densely built-up areas. However, the extraction of dense and precise 3D point clouds from such street-level imagery presumes high quality georeferencing as a first processing step. While standard direct georeferencing solves this task in open areas, poor GNSS coverage in densely built-up areas and urban canyons frequently prevents sufficient accuracy and reliability. Thus, we use bundle block adjustment, which additionally integrates tie and control point information for precise georeferencing of our multi-camera mobile mapping system. Subsequently, this allows the adaption of a state-of-the-art dense image matching pipeline to provide a suitable 3D representation of the captured urban structures. In addition to the presentation of different processing steps, this paper also provides an evaluation of the achieved image-based 3D capture in a dense urban environment. Numéro de notice : A2016-981 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.82.12.925 En ligne : https://doi.org/10.14358/PERS.82.12.925 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=83693 [article]

A global study of NDVI difference among moderate-resolution satellite sensors / Xingwang Fan in ISPRS Journal of photogrammetry and remote sensing, vol 121 (November 2016)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 121 (November 2016) . - pp 177 – 191 Titre : A global study of NDVI difference among moderate-resolution satellite sensors Type de document : Article/Communication Auteurs : Xingwang Fan, Auteur ; Yuanbo Liu, Auteur Année de publication : 2016 Article en page(s) : pp 177 – 191 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] analyse comparative [Termes IGN] effet atmosphérique [Termes IGN] image Aqua-MODIS [Termes IGN] image multicapteur [Termes IGN] image NPP-VIIRS [Termes IGN] image Terra-MODIS [Termes IGN] image TIROS-AVHRR [Termes IGN] Normalized Difference Vegetation Index [Termes IGN] occupation du sol [Termes IGN] variation saisonnière Résumé : (Auteur) Moderate-resolution sensors, including AVHRR (Advanced Very High Resolution Radiometer), MODIS (MODerate-resolution Imaging Spectroradiometer) and VIIRS (Visible-Infrared Imager-Radiometer Suite), have provided over forty years of global scientific data. In the form of NDVI (Normalized Difference Vegetation Index), these data greatly benefit environmental studies. However, their usefulness is compromised by sensor differences. This study investigates the global NDVI difference and its spatio-temporal patterns among typical moderate-resolution sensors, as supported by state-of-the-art remote sensing derived products. Our study demonstrates that the atmosphere plays a secondary role to LULC (Land Use/Land Cover) in inter-sensor NDVI differences. With reference to AVHRR/3, AVHRR/1 and 2 exhibit negative NDVI biases for vegetated land cover types. In summer (July), the area of negative bias shifts northward, and the magnitude increases in the Northern Hemisphere. For most LULC types, the bias generally shifts in the negative direction from winter (January) to summer. A linear regression of the NDVI difference versus NDVI shows a close correlation between the slope value and vegetation phenology. Overall, NDVI differences are controlled by LULC type and vegetation phenology. Our study can be used to generate a long-term, consistent NDVI data set from composite MODIS and AVHRR NDVI data. LULC-dependent and temporally variable correction equations are recommended to reduce inter-sensor NDVI differences. Numéro de notice : A2016--017 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2016.09.008 En ligne : http://dx.doi.org/10.1016/j.isprsjprs.2016.09.008 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=83879 [article]

Development of a large-format UAS imaging system with the construction of a one sensor geometry from a multicamera array / Jiann-Yeou Rau in IEEE Transactions on geoscience and remote sensing, vol 54 n° 10 (October 2016)  

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Vegetation effects modeling in soil moisture retrieval using MSVI / Mina Moradizadeh in Photogrammetric Engineering & Remote Sensing, PERS, vol 82 n° 10 (October 2016)  

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Improving sensor fusion : a parametric method for the geometric coalignment of airborne hyperspectral and lidar data / Maximilian Brell in IEEE Transactions on geoscience and remote sensing, vol 54 n° 6 (June 2016)  

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Toward a generalizable image representation for large-scale change detection : application to generic damage analysis / Lionel Gueguen in IEEE Transactions on geoscience and remote sensing, vol 54 n° 6 (June 2016)  

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Surface-based matching of 3D point clouds with variable coordinates in source and target system / Xuming Ge in ISPRS Journal of photogrammetry and remote sensing, vol 111 (January 2016)  

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Distinctive order based self-similarity descriptor for multi-sensor remote sensing image matching / Amin Sedaghat in ISPRS Journal of photogrammetry and remote sensing, vol 108 (October 2015)  

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Photogrammetric techniques for voxel-based flow velocity field measurement / Patrick Westfeld in Photogrammetric record, vol 26 n° 136 (December 2011 - February 2012)  

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vol 46 n° 5 - May 2008 - Special issue on data fusion (Bulletin de IEEE Transactions on geoscience and remote sensing) / Geoscience and remote sensing society  

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Multi-sensor model-data fusion for estimation of hydrologic and energy flux parameters / L. Renzullo in Remote sensing of environment, vol 112 n° 4 (15/04/2008)  

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Fusion of support vector machines for classification of multisensor data / Björn Waske in IEEE Transactions on geoscience and remote sensing, vol 45 n° 12 Tome 1 (December 2007)  

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