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Simultaneous intensity bias estimation and stripe noise removal in infrared images using the global and local sparsity constraints / Li Liu in IEEE Transactions on geoscience and remote sensing, vol 58 n° 3 (March 2020)
[article]
Titre : Simultaneous intensity bias estimation and stripe noise removal in infrared images using the global and local sparsity constraints Type de document : Article/Communication Auteurs : Li Liu, Auteur ; Luping Xu, Auteur ; Houzhang Fang, Auteur Année de publication : 2020 Article en page(s) : pp 1777 - 1789 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] analyse bivariée
[Termes IGN] analyse comparative
[Termes IGN] filtrage du bruit
[Termes IGN] image infrarouge
[Termes IGN] intensité lumineuse
[Termes IGN] interpolation polynomiale
[Termes IGN] itération
[Termes IGN] optimisation (mathématiques)
[Termes IGN] programmation par contraintes
[Termes IGN] texture d'imageRésumé : (Auteur) Infrared (IR) images are often contaminated by obvious intensity bias and stripes, which severely affect the visual quality and subsequent applications. It is challenging to eliminate simultaneously the mixed nonuniformity noise without blurring the fine-image details in low-textured IR images. In this article, we present a new model for simultaneous intensity bias correction and destriping through introducing two sparsity constraints. One is that model fit on the intensity bias should be as accurate as possible. A bivariate polynomial model is built to characterize the global smoothness of the intensity bias. The other constraint is that the unidirectional variational sparse model can concisely represent the direction characteristic of stripe noise. A computationally efficient numerical algorithm based on split Bregman iteration is used to solve the complex optimization problem. The proposed method is fundamentally different from the existing denoising techniques and simultaneously estimates the sharp image, intensity bias, and stripe components. Significant improvement on image quality is achieved on both simulated and real studies. Both qualitative and quantitative comparisons with the state-of-the-art correction methods demonstrate its superiority. Numéro de notice : A2020-089 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2019.2948601 Date de publication en ligne : 18/11/2019 En ligne : https://doi.org/10.1109/TGRS.2019.2948601 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94663
in IEEE Transactions on geoscience and remote sensing > vol 58 n° 3 (March 2020) . - pp 1777 - 1789[article]Combinatorial optimization applied to VLBI scheduling / A. Corbin in Journal of geodesy, vol 94 n°2 (February 2020)
[article]
Titre : Combinatorial optimization applied to VLBI scheduling Type de document : Article/Communication Auteurs : A. Corbin, Auteur ; B. Niedermann, Auteur ; Axel Nothnagel, Auteur ; et al., Auteur Année de publication : 2020 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie spatiale
[Termes IGN] analyse combinatoire (maths)
[Termes IGN] données VGOS
[Termes IGN] interférométrie à très grande base
[Termes IGN] positionnement par ITGB
[Termes IGN] programmation linéaire
[Termes IGN] retard troposphérique zénithal
[Termes IGN] station VLBI
[Termes IGN] téléscope
[Termes IGN] temps universel coordonnéRésumé : (auteur) Due to the advent of powerful solvers, today linear programming has seen many applications in production and routing. In this publication, we present mixed-integer linear programming as applied to scheduling geodetic very-long-baseline interferometry (VLBI) observations. The approach uses combinatorial optimization and formulates the scheduling task as a mixed-integer linear program. Within this new method, the schedule is considered as an entity containing all possible observations of an observing session at the same time, leading to a global optimum. In our example, the optimum is found by maximizing the sky coverage score. The sky coverage score is computed by a hierarchical partitioning of the local sky above each telescope into a number of cells. Each cell including at least one observation adds a certain gain to the score. The method is computationally expensive and this publication may be ahead of its time for large networks and large numbers of VLBI observations. However, considering that developments of solvers for combinatorial optimization are progressing rapidly and that computers increase in performance, the usefulness of this approach may come up again in some distant future. Nevertheless, readers may be prompted to look into these optimization methods already today seeing that they are available also in the geodetic literature. The validity of the concept and the applicability of the logic are demonstrated by evaluating test schedules for five 1-h, single-baseline Intensive VLBI sessions. Compared to schedules that were produced with the scheduling software sked, the number of observations per session is increased on average by three observations and the simulated precision of UT1-UTC is improved in four out of five cases (6 μs average improvement in quadrature). Moreover, a simplified and thus much faster version of the mixed-integer linear program has been developed for modern VLBI Global Observing System telescopes. Numéro de notice : A2020-153 Affiliation des auteurs : non IGN Thématique : MATHEMATIQUE/POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s00190-020-01348-w Date de publication en ligne : 29/01/2020 En ligne : https://doi.org/10.1007/s00190-020-01348-w Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94786
in Journal of geodesy > vol 94 n°2 (February 2020)[article]Mapping precipitable water vapor time series from Sentinel-1 interferometric SAR / Pedro Mateus in IEEE Transactions on geoscience and remote sensing, vol 58 n° 2 (February 2020)
[article]
Titre : Mapping precipitable water vapor time series from Sentinel-1 interferometric SAR Type de document : Article/Communication Auteurs : Pedro Mateus, Auteur ; João Catalão, Auteur ; Giovanni Nico, Auteur ; Pedro Benevides, Auteur Année de publication : 2020 Article en page(s) : pp 1373 - 1379 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] Appalaches
[Termes IGN] cartographie
[Termes IGN] données GNSS
[Termes IGN] image Sentinel-SAR
[Termes IGN] interferométrie différentielle
[Termes IGN] itération
[Termes IGN] méthode des moindres carrés
[Termes IGN] modèle atmosphérique
[Termes IGN] optimisation (mathématiques)
[Termes IGN] phase GNSS
[Termes IGN] prévision météorologique
[Termes IGN] série temporelle
[Termes IGN] vapeur d'eauRésumé : (auteur) In this article, a methodology to retrieve the precipitable water vapor (PWV) from a differential interferometric time series is presented. We used external data provided by atmospheric weather models (e.g., ERA-Interim reanalysis) to constrain the initial state and by Global Navigation Satellite System (GNSS) to phase ambiguities elimination introduced by phase unwrapping algorithm. An iterative least-square is then used to solve the optimization problem. We applied the presented methodology to two time series of differential PWV maps estimated from synthetic aperture radar (SAR) images acquired by the Sentinel-1A, over the southwest part of the Appalachian Mountains (USA). The results were validated using an independent GNSS data set and also compared with atmospheric weather prediction data. The GNSS PWV observations show a strong correlation with the estimated PWV maps with a root-mean-square error less than 1 mm. These results are very encouraging, particularly for the meteorology community, providing crucial information to assimilate into numerical weather models and potentially improve the forecasts. Numéro de notice : A2020-098 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2019.2946077 Date de publication en ligne : 28/10/2019 En ligne : https://doi.org/10.1109/TGRS.2019.2946077 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94672
in IEEE Transactions on geoscience and remote sensing > vol 58 n° 2 (February 2020) . - pp 1373 - 1379[article]A restrictive polymorphic ant colony algorithm for the optimal band selection of hyperspectral remote sensing images / Xiaohui Ding in International Journal of Remote Sensing IJRS, vol 41 n° 3 (15 - 22 janvier 2020)
[article]
Titre : A restrictive polymorphic ant colony algorithm for the optimal band selection of hyperspectral remote sensing images Type de document : Article/Communication Auteurs : Xiaohui Ding, Auteur ; Shuqing Zhang, Auteur ; Huapeng Li, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 1093 - 1117 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] bande spectrale
[Termes IGN] image hyperspectrale
[Termes IGN] jeu de données
[Termes IGN] optimisation par colonie de fourmis
[Termes IGN] précision de la classification
[Termes IGN] test de performanceRésumé : (auteur) With hundreds of spectral bands, the rise of the issue of dimensionality in the classification of hyperspectral images is usually inevitable. In this paper, a restrictive polymorphic ant colony algorithm (RPACA) based band selection algorithm (RPACA-BS) was proposed to reduce the dimensionality of hyperspectral images. In the proposed algorithm, both local and global searches were conducted considering band similarity. Moreover, the problem of falling into local optima, due to the selection of similar band subsets although travelling different paths, was solved by varying the pheromone matrix between ants moving in opposite directions. The performance of the proposed RPACA-BS algorithm was evaluated using three public datasets (the Indian Pines, Pavia University and Botswana datasets) based on average overall classification accuracy (OA) and CPU processing time. The experimental results showed that average OA of RPACA-BS was up to 89.80%, 94.96% and 92.17% for the Indian Pines, Pavia University and Botswana dataset, respectively, which was higher than that of the benchmarks, including the ant colony algorithm-based band selection algorithm (ACA-BS), polymorphic ant colony algorithm-based band selection algorithm (PACA-BS) and other band selection methods (e.g. the ant lion optimizer-based band selection algorithm). Meanwhile, the time consumed by RPACA-BS and PACA-BS were slightly lower than that of ACA-BS but obviously lower than that of other benchmarks. The proposed RPACA-BS method is thus able to effectively enhance the search abilities and efficiencies of the ACA-BS and PACA-BS algorithms to handle the complex band selection issue for hyperspectral remotely sensed images. Numéro de notice : A2020-214 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1080/01431161.2019.1655810 Date de publication en ligne : 20/08/2019 En ligne : https://doi.org/10.1080/01431161.2019.1655810 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94899
in International Journal of Remote Sensing IJRS > vol 41 n° 3 (15 - 22 janvier 2020) . - pp 1093 - 1117[article]
Titre : Advances and applications in deep learning Type de document : Monographie Auteurs : Marco Antonio Aceves-Fernandez, Éditeur scientifique Editeur : London [UK] : IntechOpen Année de publication : 2020 Importance : 122 p. Format : 21 x 30 cm ISBN/ISSN/EAN : 978-1-83962-879-5 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Intelligence artificielle
[Termes IGN] apprentissage automatique
[Termes IGN] apprentissage profond
[Termes IGN] classification par réseau neuronal convolutif
[Termes IGN] constante diélectrique
[Termes IGN] méthode fondée sur le noyau
[Termes IGN] programmation stochastique
[Termes IGN] temps réel
[Termes IGN] vision par ordinateurRésumé : (auteur) Artificial Intelligence (AI) has attracted the attention of researchers and users alike and is taking an increasingly crucial role in our modern society. From cars, smartphones, and airplanes to medical equipment, consumer applications, and industrial machines, the impact of AI is notoriously changing the world we live in. In this context, Deep Learning (DL) is one of the techniques that has taken the lead for cognitive processes, pattern recognition, object detection, and machine learning, all of which have played a crucial role in the growth of AI. As such, this book examines DL applications and future trends in the field. It is a useful resource for researchers and students alike. Note de contenu : 1- Advancements in deep learning theory and applications: Perspective in 2020 and beyond
2- Advances in convolutional neural networks
3- Transfer learning and deep domain adaptation
4- Deep learning enabled nanophotonics
5- Explainable artificial intelligence (xAI) approaches and deep meta-learning models
6- Dynamic decision-making for stabilized deep learning software platformsNuméro de notice : 28565 Affiliation des auteurs : non IGN Thématique : INFORMATIQUE Nature : Recueil / ouvrage collectif DOI : 10.5772/intechopen.87786 En ligne : https://doi.org/10.5772/intechopen.87786 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97647 PermalinkAsymptotically exact data augmentation : models and Monte Carlo sampling with applications to Bayesian inference / Maxime Vono (2020)PermalinkDevelopment of new homogenisation methods for GNSS atmospheric data. Application to the analysis of climate trends and variability / Annarosa Quarello (2020)PermalinkPermalinkPermalinkPermalinkPermalinkA new segmentation method for the homogenisation of GNSS-derived IWV time-series / Annarosa Quarello (2020)PermalinkOn the adjustment, calibration and orientation of drone photogrammetry and laser-scanning / Emmanuel Clédat (2020)PermalinkSimplicial complexes reconstruction and generalisation of 3d lidar data in urban scenes / Stéphane Guinard (2020)PermalinkPermalinkPermalinkIntroducing spatial regularization in SAR tomography reconstruction / Clément Rambour in IEEE Transactions on geoscience and remote sensing, vol 57 n° 11 (November 2019)PermalinkSimulation of urban expansion via integrating artificial neural network with Markov chain – cellular automata / Tingting Xu in International journal of geographical information science IJGIS, vol 33 n° 10 (October 2019)PermalinkDecomposition of geodetic time series: A combined simulated annealing algorithm and Kalman filter approach / Feng Ming in Advances in space research, vol 64 n°5 (1 September 2019)PermalinkA factor model approach for the joint segmentation with between‐series correlation / Xavier Collilieux in Scandinavian Journal of Statistics, vol 46 n° 3 (September 2019)PermalinkFree and open-source GIS technologies for the management of woody biomass / Michele Mangiameli in Applied geomatics, vol 11 n° 3 (September 2019)PermalinkAn artificial bee colony-based algorithm to automatically create colour schemes for geovisualizations / Mingguang Wu in Cartographic journal (the), Vol 56 n° 2 (May 2019)PermalinkAutomatic reconstruction of fully volumetric 3D building models from oriented point clouds / Sebastian Ochmann in ISPRS Journal of photogrammetry and remote sensing, vol 151 (May 2019)PermalinkMise en place de procédures automatisées pour les reports topographiques en milieu ferroviaire à partir de données photogrammétriques et LiDAR acquises par drones / Marion Hinaux in XYZ, n° 158 (mars 2019)PermalinkA derivative-free optimization-based approach for detecting architectural symmetries from 3D point clouds / Fan Xue in ISPRS Journal of photogrammetry and remote sensing, vol 148 (February 2019)PermalinkSeamline network generation based on foreground segmentation for orthoimage mosaicking / Li Li in ISPRS Journal of photogrammetry and remote sensing, vol 148 (February 2019)PermalinkAssessment of along-normal uncertainties for application to terrestrial laser scanning surveys of engineering structures / Tarvo Mill in Survey review, vol 51 n° 364 (January 2019)PermalinkPermalinkPermalinkDetecting arbitrarily shaped clusters in origin-destination flows using ant colony optimization / Si Song in International journal of geographical information science IJGIS, Vol 33 n° 1-2 (January - February 2019)PermalinkPermalinkPermalinkPermalinkPermalinkGeographic Information Systems in Geospatial Intelligence, ch. 5. Spectral optimization of airborne multispectral camera for land cover classification: automatic feature selection and spectral band clustering / Arnaud Le Bris (2019)PermalinkHyperparameter optimization of neural network-driven spatial models accelerated using cyber-enabled high-performance computing / Minrui Zheng in International journal of geographical information science IJGIS, Vol 33 n° 1-2 (January - February 2019)PermalinkOptimisation of GNSS networks, considering baseline correlations / M. Amin Alizadeh-Khameneh in Survey review, vol 51 n° 364 (January 2019)PermalinkPermalinkOptimization of optical clock network for the geopotential determination / Guillaume Lion (2019)PermalinkPermalinkPermalinkQuery rewriting for semantic query optimization in spatial databases / Eduardo Mella in Geoinformatica, vol 23 n° 1 (January 2019)PermalinkRetour d'expérience de l'école OpenMOLE "ExModelo", organisée en partenariat avec le méso-centre du CRIANN / Mathieu Leclaire (2019)PermalinkVariational learning of mixture wishart model for PolSAR image classification / Qian Wu in IEEE Transactions on geoscience and remote sensing, vol 57 n° 1 (January 2019)PermalinkUn algorithme pour battre le record du SwissTrainChallenge : poser le pied dans chacun des 26 cantons le plus rapidement possible en utilisant uniquement des transports publics / Emmanuel Clédat in XYZ, n° 157 (décembre 2018 - février 2019)PermalinkEtude de faisabilité et choix optimal d'une station RIMS d'EGNOS en Algérie / Tabti Lahouaria in XYZ, n° 157 (décembre 2018 - février 2019)Permalink3D WebGIS : from visualization to analysis. An efficient browser-based 3D line-of-sight analysis / Michael Auer in ISPRS International journal of geo-information, vol 7 n° 7 (July 2018)PermalinkA context-based geoprocessing framework for optimizing meetup location of multiple moving objects along road networks / Shaohua Wang in International journal of geographical information science IJGIS, vol 32 n° 7-8 (July - August 2018)PermalinkHuman mobility semantics analysis : a probabilistic and scalable approach / Xiaohui Guo in Geoinformatica, vol 22 n° 3 (July 2018)Permalink