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imagerie
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Terme regroupant photographies et images issues de différents capteurs.
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A novel sharpening approach for superresolving multiresolution optical images / Claudia Paris in IEEE Transactions on geoscience and remote sensing, vol 57 n° 3 (March 2019)
[article]
Titre : A novel sharpening approach for superresolving multiresolution optical images Type de document : Article/Communication Auteurs : Claudia Paris, Auteur ; José Bioucas-Dias, Auteur ; Lorenzo Bruzzone, Auteur Année de publication : 2019 Article en page(s) : pp 1545 - 1560 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] filtrage du bruit
[Termes IGN] image multibande
[Termes IGN] image Sentinel-MSI
[Termes IGN] problème inverseRésumé : (Auteur) This paper aims to provide a compact superresolution formulation specific for multispectral (MS) multiresolution optical data, i.e., images characterized by different scales across different spectral bands. The proposed method, named multiresolution sharpening approach (MuSA), relies on the solution of an optimization problem tailored to the properties of those images. The superresolution problem is formulated as the minimization of an objective function containing a data-fitting term that models the blurs and downsamplings of the different bands and a patch-based regularizer that promotes image self-similarity guided by the geometric details provided by the high-resolution bands. By exploiting the approximately low-rank property of the MS data, the ill-posedness of the inverse problem in hand is strongly reduced, thus sharply improving its conditioning. The state-of-the-art color block-matching and 3D filtering (C-BM3D) image denoiser is used as a patch-based regularizer by leveraging the “plug-and-play” framework: the denoiser is plugged into the iterations of the alternating direction method of multipliers. The main novelties of the proposed method are: 1) the introduction of an observation model tailored to the specific properties of (MS) multiresolution images and 2) the exploitation of the high-spatial-resolution bands to guide the grouping step in the color block-matching and 3D filtering (C-BM3D) denoiser, which constitutes a form of regularization learned from the high-resolution channels. The results obtained on the real and synthetic Sentinel 2 data sets give an evidence of the effectiveness of the proposed approach. Numéro de notice : A2019-129 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2018.2867284 Date de publication en ligne : 26/09/2018 En ligne : https://doi.org/10.1109/TGRS.2018.2867284 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92458
in IEEE Transactions on geoscience and remote sensing > vol 57 n° 3 (March 2019) . - pp 1545 - 1560[article]Semantic understanding of scenes through the ADE20K dataset / Bolei Zhou in International journal of computer vision, vol 127 n° 3 (March 2019)
[article]
Titre : Semantic understanding of scenes through the ADE20K dataset Type de document : Article/Communication Auteurs : Bolei Zhou, Auteur ; Hang Zhao, Auteur ; Xavier Puig, Auteur ; Tete Xiao, Auteur ; Sanja Fidler, Auteur ; et al., Auteur Année de publication : 2019 Article en page(s) : pp 302 - 321 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] apprentissage profond
[Termes IGN] compréhension de l'image
[Termes IGN] détection d'objet
[Termes IGN] jeu de données localisées
[Termes IGN] réseau neuronal artificiel
[Termes IGN] scène
[Termes IGN] segmentation sémantiqueRésumé : (Auteur) Semantic understanding of visual scenes is one of the holy grails of computer vision. Despite efforts of the community in data collection, there are still few image datasets covering a wide range of scenes and object categories with pixel-wise annotations for scene understanding. In this work, we present a densely annotated dataset ADE20K, which spans diverse annotations of scenes, objects, parts of objects, and in some cases even parts of parts. Totally there are 25k images of the complex everyday scenes containing a variety of objects in their natural spatial context. On average there are 19.5 instances and 10.5 object classes per image. Based on ADE20K, we construct benchmarks for scene parsing and instance segmentation. We provide baseline performances on both of the benchmarks and re-implement state-of-the-art models for open source. We further evaluate the effect of synchronized batch normalization and find that a reasonably large batch size is crucial for the semantic segmentation performance. We show that the networks trained on ADE20K are able to segment a wide variety of scenes and objects. Numéro de notice : A2018-602 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s11263-018-1140-0 Date de publication en ligne : 07/12/2018 En ligne : https://doi.org/10.1007/s11263-018-1140-0 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92529
in International journal of computer vision > vol 127 n° 3 (March 2019) . - pp 302 - 321[article]Tree species classification in tropical forests using visible to shortwave infrared WorldView-3 images and texture analysis / Matheus Pinheiro Ferreira in ISPRS Journal of photogrammetry and remote sensing, vol 149 (March 2019)
[article]
Titre : Tree species classification in tropical forests using visible to shortwave infrared WorldView-3 images and texture analysis Type de document : Article/Communication Auteurs : Matheus Pinheiro Ferreira, Auteur ; Fabien Hubert Wagner, Auteur ; Luiz E.O.C. Aragão, Auteur Année de publication : 2019 Article en page(s) : pp 119 - 131 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse texturale
[Termes IGN] arbre (flore)
[Termes IGN] Brésil
[Termes IGN] canopée
[Termes IGN] classification dirigée
[Termes IGN] espèce végétale
[Termes IGN] forêt tropicale
[Termes IGN] houppier
[Termes IGN] image à très haute résolution
[Termes IGN] image infrarouge
[Termes IGN] image Worldview
[Termes IGN] inventaire forestier (techniques et méthodes)
[Termes IGN] matrice de co-occurrence
[Termes IGN] pansharpening (fusion d'images)
[Termes IGN] variation saisonnièreRésumé : (Auteur) Tropical forest conservation and management can significantly benefit from information about the spatial distribution of tree species. Very-high resolution (VHR) spaceborne platforms have been hailed as a promising technology for mapping tree species over broad spatial extents. WorldView-3, the most advanced VHR sensor, provides spectral data in 16 bands covering the visible to near-infrared (VNIR, 400–1040 nm) and shortwave-infrared (SWIR, 1210–2365 nm) wavelength ranges. It also collects images at unprecedented levels of details using a panchromatic band with 0.3-m of spatial resolution. However, the potential of WorldView-3 at its full spectral and spatial resolution for tropical tree species classification remains unknown. In this study, we performed a comprehensive assessment of WorldView-3 images acquired in the dry and wet seasons for tree species discrimination in tropical semi-deciduous forests. Classification experiments were performed using VNIR individually and combined with SWIR channels. To take advantage of the sub-metric resolution of the panchromatic band for classification, we applied an individual tree crown (ITC)-based approach that employed pan-sharpened VNIR bands and gray level co-occurrence matrix texture features. We determined whether the combination of images from the two annual seasons improves the classification accuracy. Finally, we investigated which plant traits influenced species detection. The new SWIR sensing capabilities of WorldView-3 increased the average producer’s accuracy up to 7.8%, by enabling the detection of non-photosynthetic vegetation within ITCs. The combination of VNIR bands from the two annual seasons did not improve the classification results when compared to the results obtained using images from each season individually. The use of VNIR bands at their original 1.2-m spatial resolution yielded average producer’s accuracies of 43.1 ± 3.1% and 38.8 ± 3% in the wet and dry seasons, respectively. The ITC-based approach improved the accuracy to 70 ± 8% in the wet and 68.4 ± 7.4% in the dry season. Texture analysis of the panchromatic band enabled the detection of species-specific differences in crown structure, which improved species detection. The use of texture analysis, pan-sharpening, and ITC delineation is a potential approach to perform tree species classification in tropical forests with WorldView-3 satellite images. Numéro de notice : A2019-117 Affiliation des auteurs : non IGN Thématique : BIODIVERSITE/FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2019.01.019 Date de publication en ligne : 28/01/2019 En ligne : https://doi.org/10.1016/j.isprsjprs.2019.01.019 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92444
in ISPRS Journal of photogrammetry and remote sensing > vol 149 (March 2019) . - pp 119 - 131[article]Exemplaires(3)
Code-barres Cote Support Localisation Section Disponibilité 081-2019031 RAB Revue Centre de documentation En réserve L003 Disponible 081-2019033 DEP-RECP Revue LASTIG Dépôt en unité Exclu du prêt 081-2019032 DEP-RECF Revue Nancy Dépôt en unité Exclu du prêt Complete 3D scene parsing from an RGBD image / Chuhang Zou in International journal of computer vision, vol 127 n° 2 (February 2019)
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Titre : Complete 3D scene parsing from an RGBD image Type de document : Article/Communication Auteurs : Chuhang Zou, Auteur ; Ruiqi Guo, Auteur ; Zhizhong Li, Auteur ; Derek Hoiem, Auteur Année de publication : 2019 Article en page(s) : pp 143 - 162 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] classification par réseau neuronal convolutif
[Termes IGN] cohérence géométrique
[Termes IGN] compréhension de l'image
[Termes IGN] image isolée
[Termes IGN] image RVB
[Termes IGN] reconstruction d'objet
[Termes IGN] scène 3DRésumé : (Auteur) One major goal of vision is to infer physical models of objects, surfaces, and their layout from sensors. In this paper, we aim to interpret indoor scenes from one RGBD image. Our representation encodes the layout of orthogonal walls and the extent of objects, modeled with CAD-like 3D shapes. We parse both the visible and occluded portions of the scene and all observable objects, producing a complete 3D parse. Such a scene interpretation is useful for robotics and visual reasoning, but difficult to produce due to the well-known challenge of segmentation, the high degree of occlusion, and the diversity of objects in indoor scenes. We take a data-driven approach, generating sets of potential object regions, matching to regions in training images, and transferring and aligning associated 3D models while encouraging fit to observations and spatial consistency. We use support inference to aid interpretation and propose a retrieval scheme that uses convolutional neural networks to classify regions and retrieve objects with similar shapes. We demonstrate the performance of our method on our newly annotated NYUd v2 dataset (Silberman et al., in: Computer vision-ECCV, 2012, pp 746–760, 2012) with detailed 3D shapes. Numéro de notice : A2018-598 Affiliation des auteurs : non IGN Thématique : IMAGERIE/INFORMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s11263-018-1133-z Date de publication en ligne : 21/11/2018 En ligne : https://doi.org/10.1007/s11263-018-1133-z Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92525
in International journal of computer vision > vol 127 n° 2 (February 2019) . - pp 143 - 162[article]Developing an optimized texture mapping for photorealistic 3D buildings / Jungil Lee in Transactions in GIS, vol 23 n° 1 (February 2019)
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Titre : Developing an optimized texture mapping for photorealistic 3D buildings Type de document : Article/Communication Auteurs : Jungil Lee, Auteur ; Byungyun Yang, Auteur Année de publication : 2019 Article en page(s) : pp 1 - 21 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] bâtiment
[Termes IGN] C++
[Termes IGN] façade
[Termes IGN] image aérienne
[Termes IGN] modèle 3D de l'espace urbain
[Termes IGN] rendu réaliste
[Termes IGN] texturageRésumé : (auteur) Texture mapping generates photorealistic representations of three‐dimensional (3D) geometric objects and enhances the spatial perception of areas of interest. Over the past two decades, even though various approaches for 3D urban models have been investigated, their use has been limited because of the lack of spatial accuracy, details, and the complex processes. It is difficult to maintain highly detailed texture information without using a hybrid of aerial image and ground‐based imaging techniques, which are costly. Furthermore, it is hard to develop a fully automated process for 3D urban mapping that achieves high spatial accuracy. With regard to the issues, this research aims to develop a semi‐automated process for 3D building models that would help image‐based approaches. It helps acquire qualified texture information and improve the appearance of building façades in a large city. In particular, this research first investigates an optimal overlap of consecutive aerial images that generates sufficient information to texture each façade, thus making this process more cost‐effective. Second, this research develops an application to semi‐automatically build 3D buildings and textured 3D buildings. The application is developed in C++. The textured 3D building models are quantitatively and qualitatively assessed to determine the usability of the semi‐automated process. Numéro de notice : A2019-088 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/tgis.12494 Date de publication en ligne : 19/11/2018 En ligne : https://doi.org/10.1111/tgis.12494 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92235
in Transactions in GIS > vol 23 n° 1 (February 2019) . - pp 1 - 21[article]Efficiently annotating object images with absolute size information using mobile devices / Martin Hofmann in International journal of computer vision, vol 127 n° 2 (February 2019)PermalinkGeneration of large-scale moderate-resolution forest height mosaic with spaceborne repeat-pass SAR interferometry and lidar / Yang Lei in IEEE Transactions on geoscience and remote sensing, vol 57 n° 2 (February 2019)PermalinkImprovement of photogrammetric accuracy by modeling and correcting the thermal effect on camera calibration / Mehdi Daakir in ISPRS Journal of photogrammetry and remote sensing, vol 148 (February 2019)PermalinkImproving LiDAR classification accuracy by contextual label smoothing in post-processing / Nan Li in ISPRS Journal of photogrammetry and remote sensing, vol 148 (February 2019)PermalinkLearning spectral-spatial-temporal features via a recurrent convolutional neural network for change detection in multispectral imagery / Lichao Mou in IEEE Transactions on geoscience and remote sensing, vol 57 n° 2 (February 2019)PermalinkMonitoring suspended particle matter using GOCI satellite data after the Tohoku (Japan) tsunami in 2011 / Audrey Minghelli in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol 12 n° 2 (February 2019)PermalinkNear real-time deforestation detection in Malaysia and Indonesia using change vector analysis with three sensors / Pauline Perbet in International Journal of Remote Sensing IJRS, vol 40 n°19 (February 2019)PermalinkSmart cartographic background symbolization for map mashups in geoportals : A proof of concept by example of landuse representation / Nadia H. Panchaud in Cartographic journal (the), Vol 56 n° 1 (February 2019)PermalinkSynergetic efficiency of Lidar and WorldView-2 for 3D urban cartography in Northeast Mexico / Fabiola D. Yepez-Rincon in Geocarto international, vol 34 n° 2 ([01/02/2019])PermalinkTree cover mapping using hybrid fuzzy C-means method and multispectral satellite images / Linda Gulbe in Baltic forestry, vol 25 n° 1 ([01/02/2019])Permalink100% automatic metrology with UAV photogrammetry and embedded GPS, and its application in dike monitoring / Yilin Zhou (2019)PermalinkPermalink3D radiative transfer modeling over complex vegetation canopies and forest reconstruction from LIDAR measurements / Jianbo Qi (2019)PermalinkPermalinkAdvanced Remote Sensing Technology for Synthetic Aperture Radar Applications, Tsunami Disasters, and Infrastructure / Maged Marghany (2019)PermalinkPermalinkAilanthus altissima mapping from multi-temporal very high resolution satellite images / Cristina Tarantino in ISPRS Journal of photogrammetry and remote sensing, vol 147 (January 2019)PermalinkAnalyse de la déformation récente dans le Grand Tunis par interférométrie radar SAR / Anis Chaabani (2019)PermalinkAnalysis and modelling of remote sensing reflectance during anoxic crisis in the Thau lagoon using satellite images / Manchun Lei (2019)PermalinkPermalinkApport des mesures du radar à synthèse d'ouverture de Sentinel-1 pour l'étude des propriétés du manteau neigeux / Gaëlle Veyssière (2019)PermalinkApports de l'imagerie satellitaire pour caractériser les évolutions morphologiques de l'embouchure du Tage / Anne Jaouen (2019)PermalinkApports des techniques photogrammétriques à l'étude du dynamisme des structures volcaniques du piton de la Fournaise / Allan Derrien (2019)PermalinkArchival aerial photogrammetric surveys, a data source to study land use/cover evolution over the last century : opportunities and issues / Arnaud Le Bris (2019)PermalinkPermalinkAssessment of different vegetation parameters for parameterizing the coupled water cloud model and advanced integral equation model for soil moisture retrieval using time series Sentinel-1A data / Long Wang in Photogrammetric Engineering & Remote Sensing, PERS, vol 85 n° 1 (January 2019)PermalinkPermalinkBridging the gap: toward a French MS-NFI for territories / Jean-Pierre Renaud (2019)PermalinkCaractérisation des déplacements liés aux coulées de lave au Piton de la Fournaise à partir de données InSAR / Alexis Hrysiewicz (2019)PermalinkCartographie des déformations sur le site de colocalisation de Grasse par méthode INSAR / Isabelle Delprat (2019)PermalinkChallenges in grassland mowing event detection with multimodal Sentinel images / Anatol Garioud (2019)PermalinkClassification du type et de la concentration de la banquise, à partir d’images Sentinel-1 SAR, grâce à des réseaux de neurones convolutifs / Hugo Boulze (2019)PermalinkClimate variability and climate change impacts on land surface, hydrological processes and water management / Yongqiang Zhang (2019)PermalinkConstruction of bulk temperature/salinity from surface temperature and atlas profiles for monitoring water volume variations in the Caspian Sea / Ayoub Moradi (2019)PermalinkPermalinkPermalinkDétection et localisation d'objets 3D par apprentissage profond en topologie capteur / Pierre Biasutti (2019)PermalinkPermalinkDiscriminating ship from radio frequency interference based on noncircularity and non-gaussianity in sentinel-1 SAR imagery / Xiangguang Leng in IEEE Transactions on geoscience and remote sensing, vol 57 n° 1 (January 2019)PermalinkPermalinkEarth observation, remote sensing and geoscientific ground investigations for archaeological and heritage research / Deodato Tapete (2019)PermalinkPermalinkEstimation de profondeur à partir d'images monoculaires par apprentissage profond / Michel Moukari (2019)PermalinkEvaluating SAR-optical sensor fusion for aboveground biomass estimation in a Brazilian tropical forest / Aline Bernarda Debastiani in Annals of forest research, vol 62 n° 1 (January - June 2019)PermalinkEvaluating the capability of the Sentinel 2 data for soil organic carbon prediction in croplands / Fabio Castaldi in ISPRS Journal of photogrammetry and remote sensing, vol 147 (January 2019)Permalink