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Ultra short-term prediction of pole coordinates via combination of empirical mode decomposition and neural networks / Yu Lei in Artificial satellites, vol 51 n° 4 (December 2016)
[article]
Titre : Ultra short-term prediction of pole coordinates via combination of empirical mode decomposition and neural networks Type de document : Article/Communication Auteurs : Yu Lei, Auteur ; Danning Zhao, Auteur ; Hongbing Cai, Auteur Année de publication : 2016 Article en page(s) : pp 149 – 161 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie physique
[Termes IGN] filtre passe-bas
[Termes IGN] fonction de base radiale
[Termes IGN] mouvement du pôle
[Termes IGN] oscillation
[Termes IGN] prévision à court terme
[Termes IGN] réseau neuronal artificiel
[Termes IGN] terme de ChandlerRésumé : (auteur) It was shown in the previous study that the increase of pole coordinates prediction error for about 100 days in the future is mostly caused by irregular short period oscillations. In this paper, the ultra short-term prediction of pole coordinates is studied for 10 days in the future by means of combination of empirical mode decomposition (EMD) and neural networks (NN), denoted EMD-NN. In the algorithm, EMD is employed as a low pass filter for eliminating high frequency signals from observed pole coordinates data. Then the annual and Chandler wobbles are removed a priori from pole coordinates data with high frequency signals eliminated. Finally, the radial basis function (RBF) networks are used to model and predict the residuals. The prediction performance of the EMD-NN approach is compared with that of the NN-only solution and the prediction methods and techniques involved in the Earth orientation parameters prediction comparison campaign (EOP PCC). The results show that the prediction accuracy of the EMD-NN algorithm is better than that of the NN-only solution and is also comparable with that of the other existing prediction method and techniques. Numéro de notice : A2016-977 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article DOI : 10.1515/arsa-2016-0013 En ligne : https://doi.org/10.1515/arsa-2016-0013 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=83688
in Artificial satellites > vol 51 n° 4 (December 2016) . - pp 149 – 161[article]Satellite images analysis for shadow detection and building height estimation / Gregoris Liasis in ISPRS Journal of photogrammetry and remote sensing, vol 119 (September 2016)
[article]
Titre : Satellite images analysis for shadow detection and building height estimation Type de document : Article/Communication Auteurs : Gregoris Liasis, Auteur ; Stavros Stavrou, Auteur Année de publication : 2016 Article en page(s) : pp 437 - 450 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] contour
[Termes IGN] délimitation
[Termes IGN] détection d'ombre
[Termes IGN] filtre spectral
[Termes IGN] hauteur du bâti
[Termes IGN] image satellite
[Termes IGN] intensité lumineuse
[Termes IGN] ombre
[Termes IGN] scène urbaine
[Termes IGN] valeur radiométriqueRésumé : (Auteur) Satellite images can provide valuable information about the presented urban landscape scenes to remote sensing and telecommunication applications. Obtaining information from satellite images is difficult since all the objects and their surroundings are presented with feature complexity. The shadows cast by buildings in urban scenes can be processed and used for estimating building heights. Thus, a robust and accurate building shadow detection process is important. Region-based active contour models can be used for satellite image segmentation. However, spectral heterogeneity that usually exists in satellite images and the feature similarity representing the shadow and several non-shadow regions makes building shadow detection challenging. In this work, a new automated method for delineating building shadows is proposed. Initially, spectral and spatial features of the satellite image are utilized for designing a custom filter to enhance shadows and reduce intensity heterogeneity. An effective iterative procedure using intensity differences is developed for tuning and subsequently selecting the most appropriate filter settings, able to highlight the building shadows. The response of the filter is then used for automatically estimating the radiometric property of the shadows. The customized filter and the radiometric feature are utilized to form an optimized active contour model where the contours are biased to delineate shadow regions. Post-processing morphological operations are also developed and applied for removing misleading artefacts. Finally, building heights are approximated using shadow length and the predefined or estimated solar elevation angle. Qualitative and quantitative measures are used for evaluating the performance of the proposed method for both shadow detection and building height estimation. Numéro de notice : A2016-792 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2016.07.006 En ligne : http://dx.doi.org/10.1016/j.isprsjprs.2016.07.006 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=82509
in ISPRS Journal of photogrammetry and remote sensing > vol 119 (September 2016) . - pp 437 - 450[article]Projective texturing uncertain geometry: silhouette-aware box-filtered blending using integral radial images / Mathieu Brédif (2016)
Titre : Projective texturing uncertain geometry: silhouette-aware box-filtered blending using integral radial images Type de document : Article/Communication Auteurs : Mathieu Brédif , Auteur Editeur : Saint-Mandé : Institut national de l'information géographique et forestière - IGN (2012-) Année de publication : 2016 Projets : iSpace&Time / Brédif, Mathieu Conférence : JFIG 2016, 29èmes Journées Française d’Informatique Graphique de l'AFIG, du GdR IG-RV du CNRS et du Chapitre Français d’EG 30/11/2016 02/12/2016 Grenoble France Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] filtre passe-bas
[Termes IGN] géométrie de l'image
[Termes IGN] incertitude géométrique
[Termes IGN] modèle géométrique de prise de vue
[Termes IGN] texturageRésumé : (auteur) Projective texturing is a commonly used image based rendering technique that enables the synthesis of novel views from the blended reprojection of nearby views on a coarse geometry proxy approximating the scene. When scene geometry is inexact, aliasing artefacts occur. This introduces disturbing artefacts in applications such as street-level immersive navigation in mobile mapping imagery, since a pixel-accurate modelling of the scene geometry and all its details is most of the time out of question. The filtered blending approach applies the necessary 1D low-pass filtering on the projective texture to trade out the aliasing artefacts at the cost of some radial blurring. This paper proposes extensions of the filtered blending approach. Firstly, we introduce Integral Radial Images that enable constant time radial box filtering and show how they can be used to apply box-filtered blending in constant time independently of the amount of depth uncertainty. Secondly, we show a very efficient application of filtered blending where the scene geometry is only given by a loose depth interval prior rather than an actual geometry proxy. Thirdly, we propose a silhouette-aware extension of the box-filtered blending that not only account for uncertain depth along the viewing ray but also for uncertain silhouettes that have to be blurred as well Numéro de notice : C2016-063 Affiliation des auteurs : LASTIG MATIS (2012-2019) Thématique : IMAGERIE/INFORMATIQUE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésNat DOI : sans En ligne : https://hal.science/hal-02551490 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96340 Evaluation of Lidar-derived DEMs through terrain analysis and field / Cody P. Gillin in Photogrammetric Engineering & Remote Sensing, PERS, vol 81 n° 5 (May 2015)
[article]
Titre : Evaluation of Lidar-derived DEMs through terrain analysis and field Type de document : Article/Communication Auteurs : Cody P. Gillin, Auteur ; Scott W. Bailey, Auteur ; Kevin J. McGuire, Auteur ; Stephen P. Prisley, Auteur Année de publication : 2015 Article en page(s) : pp 387 - 396 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] bassin hydrographique
[Termes IGN] crète (ligne)
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] filtre passe-bas
[Termes IGN] modèle numérique de surface
[Termes IGN] pas d'échantillonnage au sol
[Termes IGN] penteRésumé : (auteur) Topographic analysis of watershed-scale soil and hydrological processes using digital elevation models (DEMs) is commonplace, but most studies have used DEMs of 10 m resolution or coarser. Availability of higher-resolution DEMs created from light detection and ranging (lidar) data is increasing but their suitability for such applications has received little critical evaluation. Two different 1 m DEMs were re-sampled to 3, 5, and 10 m resolutions and used with and without a low-pass smoothing filter to delineate catchment boundaries and calculate topographic metrics. Accuracy was assessed through comparison with field slope measurements and total station surveys. DEMs provided a good estimate of slope values when grid resolution reflected the field measurement scale. Intermediate scale DEMs were most consistent with land survey techniques in delineating catchment boundaries. Upslope accumulated area was most sensitive to grid resolution, with intermediate resolutions producing a range of UAA values useful in soil and groundwater analysis. Numéro de notice : A2015-973 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.81.5.387 En ligne : https://doi.org/10.14358/PERS.81.5.387 Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=80043
in Photogrammetric Engineering & Remote Sensing, PERS > vol 81 n° 5 (May 2015) . - pp 387 - 396[article]Hyperspectral-based adaptive matched filter detector error as a function of atmospheric water vapor estimation / Allan W. Yarbrough in IEEE Transactions on geoscience and remote sensing, vol 52 n° 4 (April 2014)
[article]
Titre : Hyperspectral-based adaptive matched filter detector error as a function of atmospheric water vapor estimation Type de document : Article/Communication Auteurs : Allan W. Yarbrough, Auteur ; Michael J. Mendenhall, Auteur ; Richard K. Martin, Auteur ; Steven T. Fiorino, Auteur Année de publication : 2014 Article en page(s) : pp 2029 - 2039 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] détection d'erreur
[Termes IGN] données météorologiques
[Termes IGN] erreur de classification
[Termes IGN] estimation statistique
[Termes IGN] filtrage numérique d'image
[Termes IGN] filtre spectral
[Termes IGN] humidité de l'air
[Termes IGN] image hyperspectrale
[Termes IGN] transfert radiatif
[Termes IGN] vapeur d'eauRésumé : (Auteur) Accurate target detection and classification in hyperspectral imagery require that the spectral measurements by the imager match as closely as possible the known “true” target as collected under controlled conditions and stored in a target database. Therefore, the effect of the radiation source and the atmosphere must be factored out of the result before detection is attempted. Our objective is to evaluate detection error due to the error in estimating the atmospherics. We apply a range of atmospheric water vapor profiles, corresponding to different relative humidities, to a model-based prediction of the radiative transfer to examine the effect of water vapor on simulated hyperspectral imagery. These profiles are taken from known distribution percentiles as obtained from historic meteorological measurements close to the sites being simulated. We quantify the expected detection error for the adaptive matched filter, as measured by the receiver operating characteristic (ROC) and the area under the ROC curve, given the range of atmospheric conditions in the historic profile. We discover that, depending on the target, and given the uncertainty as to the true atmospheric conditions, detection rates improve on average across the historic range when we assume the atmospheric profile is at the 35th percentile of atmospheric relative humidity instead of the 50th percentile. Numéro de notice : A2014-269 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2013.2257797 En ligne : https://doi.org/10.1109/TGRS.2013.2257797 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=33172
in IEEE Transactions on geoscience and remote sensing > vol 52 n° 4 (April 2014) . - pp 2029 - 2039[article]Réservation
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