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Band-limited signal reconstruction from irregular samples with variable apertures / David G. Long in IEEE Transactions on geoscience and remote sensing, vol 54 n° 4 (April 2016)
Titre : Band-limited signal reconstruction from irregular samples with variable apertures Type de document : Article/Communication Auteurs : David G. Long, Auteur ; Reinhard O. W. Franz, Auteur Année de publication : 2016 Article en page(s) : pp 2424 - 2436 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement du signal
[Termes descripteurs IGN] échantillonnage de signal
[Termes descripteurs IGN] largeur de bande
[Termes descripteurs IGN] reconstruction d'image
[Termes descripteurs IGN] reconstruction du signal
[Termes descripteurs IGN] télédétectionRésumé : (Auteur) Sampling plays a critical role in remote sensing and signal analysis. In conventional sampling theory, the signal is sampled at a uniform rate at a minimum of twice the signal bandwidth. Sampling with an aperture function requires a fixed-aperture function, which can be removed by deconvolution after signal reconstruction. However, in some cases, the signal samples are available only at irregular positions, and different samples use different aperture functions. In this paper, the theory of finite-length signal reconstruction with irregular samples and variable apertures in one and two dimensions is considered. In the 1-D case, a band-limited discrete signal can be exactly reconstructed from a finite number of arbitrarily spaced samples with few restrictions on the aperture functions. Exact reconstruction in the 2-D case requires the sampling matrix be invertable, and is not always possible. Variable aperture functions, while complicating the process, can enable reconstruction for a broader range of sample locations. Practical issues are discussed, and numerical examples are provided. Variable aperture reconstruction has application in a variety of remote sensing problems. In this paper, reconstruction from 2-D irregular sampling with variable apertures is illustrated using Special Sensor Microwave/Imager radiometer observations. Numéro de notice : A2016-842 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern En ligne : http://dx.doi.org/10.1109/TGRS.2015.2501366 Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=82886
in IEEE Transactions on geoscience and remote sensing > vol 54 n° 4 (April 2016) . - pp 2424 - 2436[article]
Titre : Retrieval of phase history parameters from distributed scatterers in urban areas using very high resolution SAR data Type de document : Article/Communication Auteurs : Y. Wang, Auteur ; X. Zhu, Auteur ; R. Balmer, Auteur Année de publication : 2012 Article en page(s) : pp 89 - 99 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes descripteurs IGN] coin réflecteur
[Termes descripteurs IGN] image radar moirée
[Termes descripteurs IGN] image TerraSAR-X
[Termes descripteurs IGN] interféromètrie par radar à antenne synthétique
[Termes descripteurs IGN] matrice de covariance
[Termes descripteurs IGN] milieu urbain
[Termes descripteurs IGN] phase
[Termes descripteurs IGN] rapport signal sur bruit
[Termes descripteurs IGN] reconstruction du signalRésumé : (Auteur) In a recent contribution Ferretti and co-workers (Ferretti, A., Fumagalli, A., Novali, F., Prati, C., Rocca, F., Rucci, A., 2011. A new algorithm for processing interferometric data-stacks: SqueeSAR IEEE Transactions on Geoscience and Remote Sensing 49(9), pp. 3460–3470) have proposed the SqueeSAR method, a way to exploit temporally coherent distributed scatterers in coherent SAR data stacks. Elevation and deformation or subsidence estimates are obtained with accuracy similar as in the well known persistent scatterer interferometry (PSI). In this paper, we propose an alternative approach and provide a first demonstration of the optimal estimation of distributed scatterers’ phase histories in urban areas. Different to SqueeSAR, we derive phase histories for each distributed scatterer pixel rather than for groups of pixels. We use the Anderson–Darling statistical test to identify neighboring samples of the same distribution. Prior to covariance matrix estimation required for maximum likelihood estimation we apply a multi-resolution defringe technique. By using TerraSAR-X high resolution spotlight data, it is demonstrated that we are able to retrieve reliable phase histories and motion parameter estimates from distributed scatterers with signal-to-noise-ratio far below the common range. Numéro de notice : A2012-547 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31993
in ISPRS Journal of photogrammetry and remote sensing > vol 73 (September 2012) . - pp 89 - 99[article]Réservation
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Titre : A stochastic approach for modelling airborne lidar waveforms Type de document : Article/Communication Auteurs : Clément Mallet Congrès : ISPRS Workshop Laser Scanning 2009 (1 - 2 septembre 2009; Paris, France), Auteur Année de publication : 01/12/2009 Importance : pp 201 - 206 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement du signal
[Termes descripteurs IGN] chaîne de Markov
[Termes descripteurs IGN] données lidar
[Termes descripteurs IGN] forme d'onde pleine
[Termes descripteurs IGN] méthode de Monte-Carlo
[Termes descripteurs IGN] milieu urbain
[Termes descripteurs IGN] modèle stochastique
[Termes descripteurs IGN] reconstruction du signal
[Termes descripteurs IGN] signal laser
[Termes descripteurs IGN] signal lidarRésumé : (Auteur) In contrast to conventional airborne multi-echo laser scanner systems, full-waveform (FW) lidar systems are able to record the entire emitted and backscattered signals of each laser pulse. Instead of clouds of individual 3D points, FW devices provide ID profiles of the 3D scene, which allows gaining additional and more detailed observations of the illuminated surfaces. Indeed, lidar waveforms are signals consisting of a train of echoes where each of them corresponds to a scattering target of the Earth surface or a group of close objects leading to superimposed signals. Modelling these echoes with the appropriate parametric function is necessary to retrieve physical information about these objects and characterize their properties. Henceforth, the extracted parameters can be useful for subsequent object segmentation and/or classification. This paper presents a stochastic based model to reconstruct lidar waveforms in terms of a set of parametric functions. The model takes into account both a data term which measures the coherence between the proposed configurations and the waveforms, and a regularizing term which introduces physical knowledge on the reconstructed signal. We search for the best configuration of functions by performing a Reversible Jump Markov Chain Monte Carlo sampler coupled with a stochastic relaxation. Finally, the algorithm is validated on waveforms from several airborne lidar sensors, showing the suitability of the approach even when the traditional assumption of Gaussian decomposition of waveforms is invalid. Numéro de notice : C2009-004 Thématique : IMAGERIE/POSITIONNEMENT Nature : Communication Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=65044 Documents numériques
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Titre : Lidar waveform modeling using a marked point process Type de document : Article/Communication Auteurs : Clément Mallet Congrès : ICIP 2009, IEEE International Conference on Image Processing (7 - 10 novembre 2009; Le Caire, Egypte) Editeur : New York : Institute of Electrical and Electronics Engineers IEEE Année de publication : 07/11/2009 Importance : 4 p. Format : 21 x 30 cm Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement du signal
[Termes descripteurs IGN] algorithme du recuit simulé
[Termes descripteurs IGN] chaîne de Markov
[Termes descripteurs IGN] données localisées 3D
[Termes descripteurs IGN] forme d'onde
[Termes descripteurs IGN] lasergrammétrie
[Termes descripteurs IGN] méthode de Monte-Carlo
[Termes descripteurs IGN] milieu urbain
[Termes descripteurs IGN] processus ponctuel marqué
[Termes descripteurs IGN] reconstruction du signal
[Termes descripteurs IGN] semis de points
[Termes descripteurs IGN] signal laser
[Termes descripteurs IGN] signal lidarRésumé : (Auteur) Lidar waveforms are 1D signal consisting of a train of echoes where each of them correspond to a scattering target of the Earth surface. Modeling these echoes with the appropriate parametric function is necessary to retrieve physical information about these objects and characterize their properties. This paper presents a marked point process based model to reconstruct a lidar signal in terms of a set of parametric functions. The model takes into account both a data term which measures the coherence between the models and the waveforms, and a regularizing term which introduces physical knowledge on the reconstructed signal. We search for the best configuration of functions by performing a Reversible Jump Markov Chain Monte Carlo sampler coupled with a simulated annealing. Results are finally presented on different kinds of signals in urban areas. Numéro de notice : 13911 Thématique : IMAGERIE/POSITIONNEMENT Nature : Communication Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=64296 Documents numériques
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