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Dimension reduction methods applied to coastline extraction on hyperspectral imagery / Ozan Arslan in Geocarto international, vol 35 n° 4 ([15/03/2020])
[article]
Titre : Dimension reduction methods applied to coastline extraction on hyperspectral imagery Type de document : Article/Communication Auteurs : Ozan Arslan, Auteur ; özer Akyürek, Auteur ; Sinasi Kaya, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 376 - 390 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse en composantes principales
[Termes IGN] Bosphore, détroit du
[Termes IGN] classification par réseau neuronal
[Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] détection de contours
[Termes IGN] extraction
[Termes IGN] image EO1-Hyperion
[Termes IGN] image hyperspectrale
[Termes IGN] Istanbul (Turquie)
[Termes IGN] littoral
[Termes IGN] rapport signal sur bruit
[Termes IGN] réduction
[Termes IGN] télédétection
[Termes IGN] trait de côteRésumé : (auteur) In this study, dimensionality reduction (DR) methods on a hyperspectral dataset to explore the influence on the process of extraction of coastlines were examined and performance of different DR algorithms on the detection of coastline in Bosphorus, Istanbul was investigated. Among these methods, principal component (PC) analysis, maximum noise fraction and independent component (IC) analysis were used in the experiments with the aim of comparing. The study was carried out using these well-known DR techniques on a real hyperspectral image, an Hyperion data set with 161 bands, in the course of the experiments. Three different classifiers (i.e. ML, SVM and neural network) were used for the classification of dimensionally reduced and original images to detect coastline in the region. The DR results were evaluated quantitatively and visually in order to determine the reduced dimensions of the image subsets. Findings show that there is no significant influence of using DR methods on the dataset on the detection of coastline. Numéro de notice : A2020-099 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2018.1520920 Date de publication en ligne : 22/10/2018 En ligne : https://doi.org/10.1080/10106049.2018.1520920 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94690
in Geocarto international > vol 35 n° 4 [15/03/2020] . - pp 376 - 390[article]Low-frequency desert noise intelligent suppression in seismic data based on multiscale geometric analysis convolutional neural network / Yuxing Zhao in IEEE Transactions on geoscience and remote sensing, vol 58 n° 1 (January 2020)
[article]
Titre : Low-frequency desert noise intelligent suppression in seismic data based on multiscale geometric analysis convolutional neural network Type de document : Article/Communication Auteurs : Yuxing Zhao, Auteur ; Yue Li, Auteur ; Baojun Yang, Auteur Année de publication : 2020 Article en page(s) : pp 650 - 665 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement du signal
[Termes IGN] algorithme de filtrage
[Termes IGN] analyse multiéchelle
[Termes IGN] classification par réseau neuronal convolutif
[Termes IGN] désert
[Termes IGN] enregistrement de données
[Termes IGN] filtrage du bruit
[Termes IGN] filtre passe-bande
[Termes IGN] interruption du signal
[Termes IGN] lutte contre le bruit
[Termes IGN] rapport signal sur bruit
[Termes IGN] reconstruction du signal
[Termes IGN] séismeRésumé : (auteur) Existing denoising algorithms often need to meet some premise assumptions and applicable conditions, such as the signal-to-noise ratio (SNR) cannot be too low, and the noise needs to obey a specific distribution (such as Gaussian distribution) and to satisfy some properties (such as stationarity). For the desert noise that shares the same frequency band with the effective signal and has complex characteristics (nonlinear, nonstationary, and non-Gaussian), it is difficult to find a universally applicable method. In response to this problem, a multiscale geometric analysis (MGA) convolutional neural network (CNN) is proposed in this article. One of the most important features of the CNN is that it can extract data-rich intrinsic information from the training set without relying on a priori assumption. By introducing the CNN into the MGA, a new kind of denoising method can be created, which can achieve good results even under a low SNR. This article takes the nonsubsampled contourlet transform as an example to create a denoising network named NC-CNN for high-efficiency and intelligent denoising of desert seismic data. The processing results of synthetic seismic records and field seismic records prove that NC-CNN can effectively suppress the low-frequency noise (random noise and surface wave), and the effective signal almost has no energy loss. In addition, the reconstruction ability of the missing signals is also an advantage of this method. Numéro de notice : A2020-076 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2019.2938836 Date de publication en ligne : 24/09/2019 En ligne : https://doi.org/10.1109/TGRS.2019.2938836 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94608
in IEEE Transactions on geoscience and remote sensing > vol 58 n° 1 (January 2020) . - pp 650 - 665[article]Introducing spatial regularization in SAR tomography reconstruction / Clément Rambour in IEEE Transactions on geoscience and remote sensing, vol 57 n° 11 (November 2019)
[article]
Titre : Introducing spatial regularization in SAR tomography reconstruction Type de document : Article/Communication Auteurs : Clément Rambour, Auteur ; Loïc Denis, Auteur ; Florence Tupin, Auteur ; Hélène Oriot, Auteur Année de publication : 2019 Article en page(s) : pp 8600 - 8617 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] acquisition comprimée
[Termes IGN] analyse spectrale
[Termes IGN] écho radar
[Termes IGN] fractionnement
[Termes IGN] image à très haute résolution
[Termes IGN] image radar moirée
[Termes IGN] image TerraSAR-X
[Termes IGN] mécanique de Lagrange
[Termes IGN] reconstruction 3D du bâti
[Termes IGN] scène urbaine
[Termes IGN] TerraSAR-X
[Termes IGN] tomographie radarRésumé : (auteur) The resolution achieved by current synthetic aperture radar (SAR) sensors provides a detailed visualization of urban areas. Spaceborne sensors such as TerraSAR-X can be used to analyze large areas at a very high resolution. In addition, repeated passes of the satellite give access to temporal and interferometric information on the scene. Because of the complex 3-D structure of urban surfaces, scatterers located at different heights (ground, building facade, and roof) produce radar echoes that often get mixed within the same radar cells. These echoes must be numerically unmixed in order to get a fine understanding of the radar images. This unmixing is at the core of SAR tomography. SAR tomography reconstruction is generally performed in two steps: 1) reconstruction of the so-called tomogram by vertical focusing, at each radar resolution cell, to extract the complex amplitudes (a 1-D processing) and 2) transformation from radar geometry to ground geometry and extraction of significant scatterers. We propose to perform the tomographic inversion directly in ground geometry in order to enforce spatial regularity in 3-D space. This inversion requires solving a large-scale nonconvex optimization problem. We describe an iterative method based on variable splitting and the augmented Lagrangian technique. Spatial regularizations can easily be included in this generic scheme. We illustrate, on simulated data and a TerraSAR-X tomographic data set, the potential of this approach to produce 3-D reconstructions of urban surfaces. Numéro de notice : A2019-596 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2019.2921756 Date de publication en ligne : 04/07/2019 En ligne : https://doi.org/10.1109/TGRS.2019.2921756 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94588
in IEEE Transactions on geoscience and remote sensing > vol 57 n° 11 (November 2019) . - pp 8600 - 8617[article]Measuring phase scintillation at different frequencies with conventional GNSS receivers operating at 1 Hz / Viet Khoi Nguyen in Journal of geodesy, vol 93 n°10 (October 2019)
[article]
Titre : Measuring phase scintillation at different frequencies with conventional GNSS receivers operating at 1 Hz Type de document : Article/Communication Auteurs : Viet Khoi Nguyen, Auteur ; Adria Rovira-Garcia, Auteur ; José Miguel Juan, Auteur ; et al., Auteur Année de publication : 2019 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie spatiale
[Termes IGN] artefact
[Termes IGN] filtre passe-haut
[Termes IGN] glissement de cycle
[Termes IGN] horloge du récepteur
[Termes IGN] ionosphère
[Termes IGN] mesurage de phase
[Termes IGN] oscillateur
[Termes IGN] phase GNSS
[Termes IGN] récepteur GNSS
[Termes IGN] retard ionosphèrique
[Termes IGN] scintillation
[Termes IGN] teneur totale en électrons
[Termes IGN] zone équatorialeRésumé : (auteur) Ionospheric scintillation causes rapid fluctuations of measurements from Global Navigation Satellite Systems (GNSSs), thus threatening space-based communication and geolocation services. The phenomenon is most intense in equatorial regions, around the equinoxes and in maximum solar cycle conditions. Currently, ionospheric scintillation monitoring receivers (ISMRs) measure scintillation with high-pass filter algorithms involving high sampling rates, e.g. 50 Hz, and highly stable clocks, e.g. an ultra-low-noise Oven-Controlled Crystal Oscillator. The present paper evolves phase scintillation indices implemented in conventional geodetic receivers with sampling rates of 1 Hz and rapidly fluctuating clocks. The method is capable to mitigate ISMR artefacts that contaminate the readings of the state-of-the-art phase scintillation index. Our results agree in more than 99.9% within ± 0.05 rad (2 mm) of the ISMRs, with a data set of 8 days which include periods of moderate and strong scintillation. The discrepancies are clearly identified, being associated with data gaps and to cycle-slips in the carrier-phase tracking of ISMR that occur simultaneously with ionospheric scintillation. The technique opens the door to use huge databases available from the International GNSS Service and other centres for scintillation studies. This involves GNSS measurements from hundreds of worldwide-distributed geodetic receivers over more than one Solar Cycle. This overcomes the current limitations of scintillation studies using ISMRs, as only a few tens of ISMRs are available and their data are provided just for short periods of time. Numéro de notice : A2019-609 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s00190-019-01297-z Date de publication en ligne : 01/10/2019 En ligne : https://doi.org/10.1007/s00190-019-01297-z Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94792
in Journal of geodesy > vol 93 n°10 (October 2019)[article]An analytic expression for the phase noise of the goldstein–werner filter / Scott Hensley in IEEE Transactions on geoscience and remote sensing, vol 57 n° 9 (September 2019)
[article]
Titre : An analytic expression for the phase noise of the goldstein–werner filter Type de document : Article/Communication Auteurs : Scott Hensley, Auteur Année de publication : 2019 Article en page(s) : pp 6499 - 6516 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] bruit thermique
[Termes IGN] corrélation temporelle
[Termes IGN] densité spectrale de puissance
[Termes IGN] filtrage du bruit
[Termes IGN] filtre de Goldstein
[Termes IGN] image radar moirée
[Termes IGN] interféromètrie par radar à antenne synthétique
[Termes IGN] phase
[Termes IGN] pouvoir de résolution spectrale
[Termes IGN] rapport signal sur bruit
[Termes IGN] transformation de FourierRésumé : (auteur) Interferogram filtering for noise reduction is a key to many radar interferometric applications. Repeat pass radar interferometry often uses data with less than ideal correlation levels resulting from either long spatial or temporal baselines or changes between observations leading to high levels of temporal correlation. To maximize the utility of such pairs filtering the interferogram to get maximal noise reduction is often needed. One technique that has proved quite useful in the geophysical community is power spectral or Goldstein–Werner filtering of the interferogram whereby a power-weighted version of the Fourier transform is used to enhance fringe visibility. Although this paper defining the filter briefly touched upon the spatial resolution and noise reduction induced by the filter, it did not provide a useful formula for predicting the phase noise after filtering. This paper derives a formula for the phase noise obtained from power spectral filtering albeit under the restriction of several simplifying assumptions to make the problem analytically tractable. In particular, it is assumed that the interferometric phase is locally well approximated by a linear phase ramp with nonlinear phase perturbations small in a spectral energy sense compared to the linear term. Numéro de notice : A2019-343 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2019.2906549 Date de publication en ligne : 25/04/2019 En ligne : http://doi.org/10.1109/TGRS.2019.2906549 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93378
in IEEE Transactions on geoscience and remote sensing > vol 57 n° 9 (September 2019) . - pp 6499 - 6516[article]Discovery of new code interference phenomenon in GPS observables / Connor D. Flynn in GPS solutions, vol 23 n° 3 (July 2019)PermalinkReal-time sea-level monitoring using Kalman filtering of GNSS-R data / Joakim Strandberg in GPS solutions, vol 23 n° 3 (July 2019)PermalinkApport des mesures du radar à synthèse d'ouverture de Sentinel-1 pour l'étude des propriétés du manteau neigeux / Gaëlle Veyssière (2019)PermalinkPermalinkCaractérisation des déplacements liés aux coulées de lave au Piton de la Fournaise à partir de données InSAR / Alexis Hrysiewicz (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)PermalinkGlobal observations of ocean surface winds and waves using spaceborne synthetic aperture radar measurements / Huimin Li (2019)PermalinkSea level estimation from SNR data of geodetic receivers using wavelet analysis / Xiaolei Wang in GPS solutions, vol 23 n° 1 (January 2019)PermalinkPermalinkEstimation of surface roughness over bare agricultural soil from Sentinel-1 data / Mohammad Choker (2018)Permalink