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Deep learning for multi-modal classification of cloud, shadow and land cover scenes in PlanetScope and Sentinel-2 imagery / Yuri Shendryk in ISPRS Journal of photogrammetry and remote sensing, vol 157 (November 2019)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 157 (November 2019) . - pp 124 - 136 Titre : Deep learning for multi-modal classification of cloud, shadow and land cover scenes in PlanetScope and Sentinel-2 imagery Type de document : Article/Communication Auteurs : Yuri Shendryk, Auteur ; Yannik Rist, Auteur ; Catherine Ticehurst, Auteur ; Peter Thorburn, Auteur Année de publication : 2019 Article en page(s) : pp 124 - 136 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes descripteurs IGN] Amazonie [Termes descripteurs IGN] apprentissage profond [Termes descripteurs IGN] Australie [Termes descripteurs IGN] classification par réseau neuronal convolutif [Termes descripteurs IGN] détection d'ombre [Termes descripteurs IGN] état de l'art [Termes descripteurs IGN] image à haute résolution [Termes descripteurs IGN] image PlanetScope [Termes descripteurs IGN] image Sentinel-MSI [Termes descripteurs IGN] Normalized Difference Vegetation Index [Termes descripteurs IGN] nuage [Termes descripteurs IGN] occupation du sol [Termes descripteurs IGN] zone tropicale humide Résumé : (Auteur) With the increasing availability of high-resolution satellite imagery it is important to improve the efficiency and accuracy of satellite image indexing, retrieval and classification. Furthermore, there is a need for utilizing all available satellite imagery in identifying general land cover types and monitoring their changes through time irrespective of their spatial, spectral, temporal and radiometric resolutions. Therefore, in this study, we developed deep learning models able to efficiently and accurately classify cloud, shadow and land cover scenes in different high-resolution ( Numéro de notice : A2019-494 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2019.08.018 date de publication en ligne : 17/09/2019 En ligne : https://doi.org/10.1016/j.isprsjprs.2019.08.018 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93727 [article]

Diffusion and inpainting of reflectance and height LiDAR orthoimages / Pierre Biasutti in Computer Vision and image understanding, vol 179 (February 2019)    

Public [article]  inComputer Vision and image understanding > vol 179 (February 2019) . - pp 31 - 40 Titre : Diffusion and inpainting of reflectance and height LiDAR orthoimages Type de document : Article/Communication Auteurs : Pierre Biasutti, Auteur ; Jean-François Aujol, Auteur ; Mathieu Brédif , Auteur ; Aurélie Bugeau, Auteur Année de publication : 2019 Projets : SysNum / Article en page(s) : pp 31 - 40 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques [Termes descripteurs IGN] chaîne de traitement [Termes descripteurs IGN] convivialité [Termes descripteurs IGN] densité des points [Termes descripteurs IGN] détection d'ombre [Termes descripteurs IGN] données lidar [Termes descripteurs IGN] données localisées 3D [Termes descripteurs IGN] orthoimage [Termes descripteurs IGN] réflectance [Termes descripteurs IGN] semis de points Résumé : (Auteur) This paper presents a fully automatic framework for the generation of so-called LiDAR orthoimages (i.e. 2D raster maps of the reflectance and height LiDAR samples) from ground-level LiDAR scans. Beyond the Digital Surface Model (DSM or heightmap) provided by the height orthoimage, the proposed method cost-effectively generates a reflectance channel that is easily interpretable by human operators without relying on any optical acquisition, calibration and registration. Moreover, it commonly achieves very high resolutions (1cm per pixel), thanks to the typical sampling density of static or mobile LiDAR scans. Compared to orthoimages generated from aerial datasets, the proposed LiDAR orthoimages are acquired from the ground level and thus do not suffer occlusions from hovering objects (trees, tunnels and bridges), enabling their use in a number of urban applications such as road network monitoring and management, as well as precise mapping of the public space e.g. for accessibility applications or management of underground networks. Its generation and usability however faces two issues : (i) the inhomogeneous sampling density of LiDAR point clouds and (ii) the presence of masked areas (holes) behind occluders, which include, in a urban context, cars, tree trunks, poles or pedestrians (i) is addressed by first projecting the point cloud on a 2D-pixel grid so as to generate sparse and noisy reflectance and height images from which dense images estimated using a joint anisotropic diffusion of the height and reflectance channels. (ii) LiDAR shadow areas are detected by analyzing the diffusion results so that they can be inpainted using an examplar-based method, guided by an alignment prior. Results on real mobile and static acquisition data demonstrate the effectiveness of the proposed pipeline in generating a very high resolution LiDAR orthoimage of reflectance and height while filling holes of various sizes in a visually satisfying way. Numéro de notice : A2019-168 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.cviu.2018.10.011 date de publication en ligne : 24/11/2018 En ligne : https://doi.org/10.1016/j.cviu.2018.10.011 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92610 [article]

Documents numériques

en open access Diffusion and inpainting - version HAL URL

ICARE-VEG: A 3D physics-based atmospheric correction method for tree shadows in urban areas / Karine R.M. Adeline in ISPRS Journal of photogrammetry and remote sensing, vol 142 (August 2018)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 142 (August 2018) . - pp 311 - 327 Titre : ICARE-VEG: A 3D physics-based atmospheric correction method for tree shadows in urban areas Type de document : Article/Communication Auteurs : Karine R.M. Adeline, Auteur ; Xavier Briottet , Auteur ; X. Ceamanos, Auteur ; T. Dartigalongue, Auteur ; Jean-Philippe Gastellu-Etchegorry, Auteur Année de publication : 2018 Article en page(s) : pp 311 - 327 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image [Termes descripteurs IGN] arbre (flore) [Termes descripteurs IGN] correction atmosphérique [Termes descripteurs IGN] détection d'ombre [Termes descripteurs IGN] houppier [Termes descripteurs IGN] image à très haute résolution [Termes descripteurs IGN] image hyperspectrale [Termes descripteurs IGN] Leaf Area Index [Termes descripteurs IGN] logiciel de traitement d'image [Termes descripteurs IGN] modèle de transfert radiatif [Termes descripteurs IGN] modélisation 3D [Termes descripteurs IGN] réflectance végétale [Termes descripteurs IGN] zone urbaine Résumé : (Auteur) Many applications dedicated to urban areas (e.g. land cover mapping and biophysical properties estimation) using high spatial resolution remote sensing images require the use of 3D atmospheric correction methods, able to model complex light interactions within urban topography such as buildings and trees. Currently, one major drawback of these methods is their lack in modeling the radiative signature of trees (e.g. the light transmitted through the tree crown), which leads to an over-estimation of ground reflectance at tree shadows. No study has been carried out to take into account both optical and structural properties of trees in the correction provided by these methods. The aim of this work is to improve an existing 3D atmospheric correction method, ICARE (Inversion Code for urban Areas Reflectance Extraction), to account for trees in its new version, ICARE-VEG (ICARE with VEGetation). After the execution of ICARE, the methodology of ICARE-VEG consists in tree crown delineation and tree shadow detection, and then the application of a physics-based correction factor in order to perform a tree-specific local correction for each pixel in tree shadow. A sensitivity analysis with a design of experiments performed with a 3D canopy radiative transfer code, DART (Discrete Anisotropic Radiative Transfer), results in fixing the two most critical variables contributing to the impact of an isolated tree crown on the radiative energy budget at tree shadow: the solar zenith angle and the tree leaf area index (LAI). Thus, the approach to determine the correction factor relies on an empirical statistical regression and the addition of a geometric scaling factor to account for the tree crown occultation from ground. ICARE-VEG and ICARE performance were compared and validated in the Visible-Near Infrared Region (V-NIR: 0.4–1.0 µm) with hyperspectral airborne data at 0.8 m resolution on three ground materials types, grass, asphalt and water. Results show that (i) ICARE-VEG improves the mean absolute error in retrieved reflectances compared to ICARE in tree shadows by a multiplicative factor ranging between 4.2 and 18.8, and (ii) reduces the spectral bias in reflectance from visible to NIR (due to light transmission through the tree crown) by a multiplicative factor between 1.0 and 1.4 in terms of spectral angle mapper performance. ICARE-VEG opens the way to a complete interpretation of remote sensing images (sunlit, shade cast by both buildings and trees) and the derivation of scientific value-added products over all the entire image without the preliminary step of shadow masking. Numéro de notice : A2018-296 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2018.05.015 date de publication en ligne : 01/08/2018 En ligne : https://doi.org/10.1016/j.isprsjprs.2018.05.015 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90415 [article]

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Self-shadowing of a spacecraft in the computation of surface forces : An example in planetary geodesy / Georges Balmino in Artificial satellites, vol 53 n° 1 (March 2018)  

Public [article]  inArtificial satellites > vol 53 n° 1 (March 2018) . - pp 1 - 27 Titre : Self-shadowing of a spacecraft in the computation of surface forces : An example in planetary geodesy Type de document : Article/Communication Auteurs : Georges Balmino, Auteur ; J.C. Marty, Auteur Année de publication : 2018 Article en page(s) : pp 1 - 27 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Techniques orbitales [Termes descripteurs IGN] décomposition [Termes descripteurs IGN] détection d'ombre [Termes descripteurs IGN] engin spatial [Termes descripteurs IGN] Mars (planète) [Termes descripteurs IGN] problème inverse [Termes descripteurs IGN] surface (géométrie) Résumé : (auteur) We describe in details the algorithms used in modelling the self-shadowing between spacecraft components, which appears when computing the surface forces as precisely as possible and especially when moving parts are involved. This becomes necessary in planetary geodesy inverse problems using more and more precise orbital information to derive fundamental parameters of geophysical interest. Examples are given with two Mars orbiters, which show significant improvement on drag and solar radiation pressure model multiplying factors, a prerequisite for improving in turn the determination of other global models. Numéro de notice : A2018-173 Thématique : POSITIONNEMENT Nature : Article DOI : 10.2478/arsa-2018-0002 date de publication en ligne : 24/03/2018 En ligne : https://doi.org/10.2478/arsa-2018-0002 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89813 [article]

Automatic shadow detection in aerial and terrestrial images / Vander Luis de Souza Freitas in Boletim de Ciências Geodésicas, vol 23 n° 4 (oct - dec 2017)    

Public [article]  inBoletim de Ciências Geodésicas > vol 23 n° 4 (oct - dec 2017) . - pp 578 - 590 Titre : Automatic shadow detection in aerial and terrestrial images Type de document : Article/Communication Auteurs : Vander Luis de Souza Freitas, Auteur ; Barbara Maximino da Fonseca Reis, Auteur ; Antonio Maria Garcia Tommaselli, Auteur Année de publication : 2017 Article en page(s) : pp 578 - 590 Note générale : bibliographie Langues : Portugais (por) Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes descripteurs IGN] détection d'ombre [Termes descripteurs IGN] image aérienne [Termes descripteurs IGN] image terrestre Résumé : (auteur) Shadows exist in almost all aerial and outdoor images, and they can be useful for estimating Sun position estimation or measuring object size. On the other hand, they represent a problem in processes such as object detection/recognition, image matching, etc., because they may be confused with dark objects and change the image radiometric properties. We address this problem on aerial and outdoor color images in this work. We use a filter to find low intensities as a first step. For outdoor color images, we analyze spectrum ratio properties to refine the detection, and the results are assessed with a dataset containing ground truth. For the aerial case we validate the detections depending of the hue component of pixels. This stage takes into account that, in deep shadows, most pixels have blue or violet wavelengths because of an atmospheric scattering effect. Numéro de notice : A2017-757 Thématique : IMAGERIE Nature : Article DOI : 10.1590/S1982-21702017000400038 En ligne : http://dx.doi.org/10.1590/S1982-21702017000400038 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89112 [article]

Documents numériques

en open access Automatic shadow detection ... - pdf éditeur Adobe Acrobat PDF

An inquiry on contrast enhancement methods for satellite images / Jose-Luis Lisani in IEEE Transactions on geoscience and remote sensing, vol 54 n° 12 (December 2016)  

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Satellite images analysis for shadow detection and building height estimation / Gregoris Liasis in ISPRS Journal of photogrammetry and remote sensing, vol 119 (September 2016)  

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Shadow detection and removal in RGB VHR images for land use unsupervised classification / A. Movia in ISPRS Journal of photogrammetry and remote sensing, vol 119 (September 2016)  

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Automatic detection of clouds and shadows using high resolution satellite image time series / Nicolas Champion (2016)    

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Recovering quantitative remote sensing products contaminated by thick clouds and shadows using multitemporal dictionary learning / X. Li in IEEE Transactions on geoscience and remote sensing, vol 52 n° 11 tome 1 (November 2014)

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Shadow detection of man-made buildings in high-resolution panchromatic satellite images / Mohamed I. Elbakary in IEEE Transactions on geoscience and remote sensing, vol 52 n° 9 Tome 1 (September 2014)

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Shadow detection in very high spatial resolution aerial images: A comparative study / Karine R.M. Adeline in ISPRS Journal of photogrammetry and remote sensing, vol 80 (June 2013)  

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Use of shadows for detection of earthquake-induced collapsed buildings in high-resolution satellite imagery / Xiaohua Tong in ISPRS Journal of photogrammetry and remote sensing, vol 79 (May 2013)

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A complete processing chain for shadow detection and reconstruction in VHR images / L. Lorenzi in IEEE Transactions on geoscience and remote sensing, vol 50 n° 9 (October 2012)

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Efficient shadow detection of color aerial images based on successive thresholding scheme / K.L. Chung in IEEE Transactions on geoscience and remote sensing, vol 47 n° 2 (February 2009)

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