Descripteur
Termes IGN > sciences naturelles > physique > traitement d'image > superposition d'images
superposition d'images |
Documents disponibles dans cette catégorie (101)
Ajouter le résultat dans votre panier
Visionner les documents numériques
Affiner la recherche Interroger des sources externes
Etendre la recherche sur niveau(x) vers le bas
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)
[article]
Titre : Improving sensor fusion : a parametric method for the geometric coalignment of airborne hyperspectral and lidar data Type de document : Article/Communication Auteurs : Maximilian Brell, Auteur ; Christian Rogass, Auteur ; Karl Segl, Auteur ; et al., Auteur Année de publication : 2016 Article en page(s) : pp 3460 - 3474 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image mixte
[Termes IGN] alignement semi-dirigé
[Termes IGN] appariement géométrique
[Termes IGN] données lidar
[Termes IGN] image aérienne
[Termes IGN] image hyperspectrale
[Termes IGN] image multicapteur
[Termes IGN] points homologues
[Termes IGN] superposition d'images
[Termes IGN] télémétrie laser aéroportéRésumé : (Auteur) Synergistic applications based on integrated hyperspectral and lidar data are receiving a growing interest from the remote-sensing community. A prerequisite for the optimum sensor fusion of hyperspectral and lidar data is an accurate geometric coalignment. The simple unadjusted integration of lidar elevation and hyperspectral reflectance causes a substantial loss of information and does not exploit the full potential of both sensors. This paper presents a novel approach for the geometric coalignment of hyperspectral and lidar airborne data, based on their respective adopted return intensity information. The complete approach incorporates ray tracing and subpixel procedures in order to overcome grid inherent discretization. It aims at the correction of extrinsic and intrinsic (camera resectioning) parameters of the hyperspectral sensor. In additional to a tie-point-based coregistration, we introduce a ray-tracing-based back projection of the lidar intensities for area-based cost aggregation. The approach consists of three processing steps. First is a coarse automatic tie-point-based boresight alignment. The second step coregisters the hyperspectral data to the lidar intensities. Third is a parametric coalignment refinement with an area-based cost aggregation. This hybrid approach of combining tie-point features and area-based cost aggregation methods for the parametric coregistration of hyperspectral intensity values to their corresponding lidar intensities results in a root-mean-square error of 1/3 pixel. It indicates that a highly integrated and stringent combination of different coalignment methods leads to an improvement of the multisensor coregistration. Numéro de notice : A2016-855 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2016.2518930 En ligne : https://doi.org/10.1109/TGRS.2016.2518930 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=82994
in IEEE Transactions on geoscience and remote sensing > vol 54 n° 6 (June 2016) . - pp 3460 - 3474[article]An approach to fine coregistration between very high resolution multispectral images based on registration noise distribution / Youkyung Han in IEEE Transactions on geoscience and remote sensing, vol 53 n° 12 (December 2015)
[article]
Titre : An approach to fine coregistration between very high resolution multispectral images based on registration noise distribution Type de document : Article/Communication Auteurs : Youkyung Han, Auteur ; Francesca Bovolo, Auteur ; Lorenzo Bruzzone, Auteur Année de publication : 2015 Article en page(s) : pp 6650 - 6662 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] appariement de points
[Termes IGN] bruit (théorie du signal)
[Termes IGN] filtrage du bruit
[Termes IGN] image à très haute résolution
[Termes IGN] image multibande
[Termes IGN] point d'appui
[Termes IGN] raccord d'images
[Termes IGN] superposition d'imagesRésumé : (auteur) Even after applying effective coregistration methods, multitemporal images are likely to show a residual misalignment, which is referred to as registration noise (RN). This is because coregistration methods from the literature cannot fully handle the local dissimilarities induced by differences in the acquisition conditions (e.g., the stability of the acquisition platform, the off-nadir angle of the sensor, the structure of the considered scene, etc.). This paper addresses the problem of reducing such a residual misalignment by proposing a fine automatic coregistration approach for very high resolution (VHR) multispectral images. The proposed method takes advantage of the properties of the residual misalignment itself. To this end, RN is first extracted in the change vector analysis (CVA) polar domain according to the behaviors of the specific multitemporal images considered. Then, a local analysis of RN pixels (i.e., those showing residual misalignment) is conducted for automatically extracting control points (CPs) and matching them according to their estimated displacement. Matched CPs are used for generating a deformation map by interpolation. Finally, one VHR image is warped to the coordinates of the other through a deformation map. Experiments carried out on simulated and real multitemporal VHR images confirm the effectiveness of the proposed approach. Numéro de notice : A2015-846 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2015.2445632 Date de publication en ligne : 07/07/2015 En ligne : https://doi.org/10.1109/TGRS.2015.2445632 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=79196
in IEEE Transactions on geoscience and remote sensing > vol 53 n° 12 (December 2015) . - pp 6650 - 6662[article]Réservation
Réserver ce documentExemplaires (1)
Code-barres Cote Support Localisation Section Disponibilité 065-2015121 SL Revue Centre de documentation Revues en salle Disponible Forest cover maps of China in 2010 from multiple approaches and data sources: PALSAR, Landsat, MODIS, FRA, and NFI / Yuanwei Qin in ISPRS Journal of photogrammetry and remote sensing, vol 109 (November 2015)
[article]
Titre : Forest cover maps of China in 2010 from multiple approaches and data sources: PALSAR, Landsat, MODIS, FRA, and NFI Type de document : Article/Communication Auteurs : Yuanwei Qin, Auteur ; Xiangming Xiao, Auteur ; Jinwei Dong, Auteur ; et al., Auteur Année de publication : 2015 Article en page(s) : pp 1 - 16 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] base de données d'occupation du sol
[Termes IGN] carte de la végétation
[Termes IGN] carte thématique
[Termes IGN] Chine
[Termes IGN] classification par arbre de décision
[Termes IGN] forêt
[Termes IGN] image ALOS-PALSAR
[Termes IGN] image Terra-MODIS
[Termes IGN] inventaire forestier étranger (données)
[Termes IGN] superposition d'images
[Termes IGN] teneur en carboneRésumé : (auteur) Forests and their changes are important to the regional and global carbon cycle, biodiversity and ecosystem services. Some uncertainty about forest cover area in China calls for an accurate and updated forest cover map. In this study, we combined ALOS PALSAR orthorectified 50-m mosaic images (FBD mode with HH and HV polarization) and MODIS time series data in 2010 to map forests in China. We used MODIS-based NDVI dataset (MOD13Q1, 250-m spatial resolution) to generate a map of annual maximum NDVI and used it to mask out built-up lands, barren lands, and sparsely vegetated lands. We developed a decision tree classification algorithm to identify forest and non-forest land cover, based on the signature analysis of PALSAR backscatter coefficient data. The PALSAR-based algorithm was then applied to produce a forest cover map in China in 2010. The resulting forest/non-forest classification map has an overall accuracy of 96.2% and a Kappa Coefficient of 0.91. The resultant 50-m PALSAR-based forest cover map was compared to five forest cover databases. The total forest area (2.02 × 106 km2) in China from the PALSAR-based forest map is close to the forest area estimates from China National Forestry Inventory (1.95 × 106 km2), JAXA (2.00 × 106 km2), and FAO FRA (2.07 × 106 km2). There are good linear relationships between the PALSAR-based forest map and the forest maps from the JAXA, MCD12Q1, and NLCD-China datasets at the province and county scales. All the forest maps have similar spatial distributions of forest/non-forest at pixel scale. Our PALSAR-based forest map recognizes well the agro-forests in China. The results of this study demonstrate the potential of integrating PALSAR and MODIS images to map forests in large areas. The resultant map of forest cover in China in 2010 can be used for many studies such as forest carbon cycle and ecological restoration. Numéro de notice : A2015-854 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2015.08.010 En ligne : https://doi.org/10.1016/j.isprsjprs.2015.08.010 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=79234
in ISPRS Journal of photogrammetry and remote sensing > vol 109 (November 2015) . - pp 1 - 16[article]Fusion of waveform LiDAR data and hyperspectral imagery for land cover classification / Hongzhou Wang in ISPRS Journal of photogrammetry and remote sensing, vol 108 (October 2015)
[article]
Titre : Fusion of waveform LiDAR data and hyperspectral imagery for land cover classification Type de document : Article/Communication Auteurs : Hongzhou Wang, Auteur ; Craig L. Glennie, Auteur Année de publication : 2015 Article en page(s) : pp 1 - 11 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] classification par maximum de vraisemblance
[Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] données lidar
[Termes IGN] extraction de traits caractéristiques
[Termes IGN] forme d'onde pleine
[Termes IGN] fusion d'images
[Termes IGN] fusion de données
[Termes IGN] image hyperspectrale
[Termes IGN] occupation du sol
[Termes IGN] onde lidar
[Termes IGN] semis de points
[Termes IGN] superposition d'images
[Termes IGN] voxelRésumé : (auteur) Current research into the fusion of hyperspectral imagery (HI) and full waveform LiDAR (Light Detection And Ranging) has relied on first processing the full waveform LiDAR (FWL) data to a set of discrete returns before merging because the data structure and sampling interval of HI and FWL are distinctly different. However, additional information about target properties can potentially be recovered if the waveform shape is preserved in the fusion process. This paper proposes a “voxelization” method to register FWL data to HI by dividing the waveform data into voxels, and then synthesizing all waveforms which intersect a voxel column into one three-dimensional superposition waveform: the synthesized waveform (SWF). A vertical energy distribution coefficients (VEDC) feature is proposed for extracting features from SWF, and then the SWF and HI are fused to form a complete feature space for classification. A pairwise classifier was adapted and completed using both Maximum Likelihood and Support Vector Machine classifiers for the combined SWF/HI features. Results show that this method of generating SWF from FWL data can effectively preserve information from the original waveforms, and the fusion of SWF and HI enhanced land cover classification compared to both using either data set alone or the merging of HI with a discrete LiDAR return point cloud. Numéro de notice : A2015-848 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2015.05.012 Date de publication en ligne : 23/06/2015 En ligne : http://dx.doi.org/10.1016/j.isprsjprs.2015.05.012 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=79218
in ISPRS Journal of photogrammetry and remote sensing > vol 108 (October 2015) . - pp 1 - 11[article]Automatic registration of optical aerial imagery to a LiDAR point cloud for generation of city models / Bernard O. Abayowa in ISPRS Journal of photogrammetry and remote sensing, vol 106 (August 2015)
[article]
Titre : Automatic registration of optical aerial imagery to a LiDAR point cloud for generation of city models Type de document : Article/Communication Auteurs : Bernard O. Abayowa, Auteur ; Alper Yilmaz, Auteur ; Russell C. Hardie, Auteur Année de publication : 2015 Article en page(s) : pp 68 - 81 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] algorithme ICP
[Termes IGN] corrélation croisée normalisée
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] image aérienne
[Termes IGN] image optique
[Termes IGN] méthode robuste
[Termes IGN] milieu urbain
[Termes IGN] modèle 3D de l'espace urbain
[Termes IGN] modèle numérique de surface
[Termes IGN] reconstruction 3D
[Termes IGN] scène
[Termes IGN] semis de points
[Termes IGN] superposition d'imagesRésumé : (auteur) This paper presents a framework for automatic registration of both the optical and 3D structural information extracted from oblique aerial imagery to a Light Detection and Ranging (LiDAR) point cloud without prior knowledge of an initial alignment. The framework employs a coarse to fine strategy in the estimation of the registration parameters. First, a dense 3D point cloud and the associated relative camera parameters are extracted from the optical aerial imagery using a state-of-the-art 3D reconstruction algorithm. Next, a digital surface model (DSM) is generated from both the LiDAR and the optical imagery-derived point clouds. Coarse registration parameters are then computed from salient features extracted from the LiDAR and optical imagery-derived DSMs. The registration parameters are further refined using the iterative closest point (ICP) algorithm to minimize global error between the registered point clouds. The novelty of the proposed approach is in the computation of salient features from the DSMs, and the selection of matching salient features using geometric invariants coupled with Normalized Cross Correlation (NCC) match validation. The feature extraction and matching process enables the automatic estimation of the coarse registration parameters required for initializing the fine registration process. The registration framework is tested on a simulated scene and aerial datasets acquired in real urban environments. Results demonstrates the robustness of the framework for registering optical and 3D structural information extracted from aerial imagery to a LiDAR point cloud, when co-existing initial registration parameters are unavailable. Numéro de notice : A2015-722 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2015.05.006 En ligne : https://doi.org/10.1016/j.isprsjprs.2015.05.006 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=78369
in ISPRS Journal of photogrammetry and remote sensing > vol 106 (August 2015) . - pp 68 - 81[article]Apport du LiDAR dans le géoréférencement d'images hyperspectrales en vue d'un couplage LiDAR/hyperspectral / Antoine Ba in Revue Française de Photogrammétrie et de Télédétection, n° 210 (Avril 2015)PermalinkCoregistration refinement of hyperspectral images and DSM: An object-based approach using spectral information / Janja Avbelj in ISPRS Journal of photogrammetry and remote sensing, vol 100 (February 2015)PermalinkPléiades satellites image quality commissioning / Laurent Lebègue in Revue Française de Photogrammétrie et de Télédétection, n° 209 (Janvier 2015)PermalinkEvaluation of feature-based 3-d registration of probabilistic volumetric scenes / Maria I. Restrepo in ISPRS Journal of photogrammetry and remote sensing, vol 98 (December 2014)PermalinkCross-correlation of diameter measures for the co-registration of forest inventory plots with airborne laser scanning data / Jean-Matthieu Monnet in Forests, vol 5 n° 9 (September 2014)PermalinkSemi-automated registration of close-range hyperspectral scans using oriented digital camera imagery and a 3D model / Alessandra A. Sima in Photogrammetric record, vol 29 n° 145 (March - May 2014)PermalinkAutomatic registration of optical imagery with 3D LiDAR data using statistical similarity / Ebadat Ghanbari Parmehr in ISPRS Journal of photogrammetry and remote sensing, vol 88 (February 2014)PermalinkRadargrammetric registration of airborne multi-aspect SAR data of urban areas / Michael Schmitt in ISPRS Journal of photogrammetry and remote sensing, vol 86 (December 2013)PermalinkRegistration of optical images with lidar data and its accuracy assessment / Shunyl Zheng in Photogrammetric Engineering & Remote Sensing, PERS, vol 79 n° 8 (August 2013)PermalinkImproved nonsubsampled contourlet transform for multi-sensor image registration / R. Wang in Photogrammetric Engineering & Remote Sensing, PERS, vol 79 n° 1 (January 2013)Permalink