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A tensor decomposition-based anomaly detection algorithm for hyperspectral image / Xing Zhang in IEEE Transactions on geoscience and remote sensing, vol 54 n° 10 (October 2016)
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Titre : A tensor decomposition-based anomaly detection algorithm for hyperspectral image Type de document : Article/Communication Auteurs : Xing Zhang, Auteur ; Gongjian Wen, Auteur ; Wei Dai, Auteur Année de publication : 2016 Article en page(s) : pp 5801 - 5820 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] décomposition
[Termes IGN] détection d'anomalie
[Termes IGN] image hyperspectrale
[Termes IGN] signature spectrale
[Termes IGN] tenseurRésumé : (auteur) Anomalies usually refer to targets with a spot of pixels (even subpixels) that stand out from their neighboring background clutter pixels in hyperspectral imagery (HSI). Compared to backgrounds, anomalies have two main characteristics. One is the spectral anomaly, i.e., their spectral signatures are different from those associated to their surrounding backgrounds; another is the spatial anomaly, i.e., anomalies occur as few pixels (even subpixels) embedded in the local homogeneous backgrounds. However, most of the existing anomaly detection algorithms for HSI only employed the spectral anomaly. If the two characteristics are exploited in a detection method simultaneously, better performance may be achieved. The third-order (two modes for space and one mode for spectra) tensor representation of HSI has been proved to be an effective tool to describe the spatial and spectral information equivalently; therefore, tensor representation is convenient for exhibiting the two characteristics of anomalies simultaneously. In this paper, a new anomaly detection method based on tensor decomposition is proposed and divided into three steps. Three factor matrices and a core tensor are first estimated from the third-order tensor that is constructed from the HSI data cube by using the Tucker decomposition, and their major and minor principal components (PCs) are more likely to correspond to the spectral signatures of the backgrounds and the anomalies, respectively. In the second step, a reconstruction-error-based method is presented to find the first largest PCs along each mode to eliminate the spectral signatures of the backgrounds as much as possible, and thus, the remaining data may be modeled as the spectral signatures of the anomalies with a Gaussian noise. Finally, a CFAR test is implemented to detect the anomalies from the remaining data. Experiments with simulated, synthetic, and real HSI data sets reveal that the proposed method outperforms those spectral-anomaly-based methods with better detection probability and less false alarm rate. Numéro de notice : A2016-862 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2016.2572400 En ligne : https://doi.org/10.1109/TGRS.2016.2572400 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=82894
in IEEE Transactions on geoscience and remote sensing > vol 54 n° 10 (October 2016) . - pp 5801 - 5820[article]Automatic rough georeferencing of multiview oblique and vertical aerial image datasets of urban scenes / Styliani Verykokou in Photogrammetric record, vol 31 n° 155 (September - November 2016)
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Titre : Automatic rough georeferencing of multiview oblique and vertical aerial image datasets of urban scenes Type de document : Article/Communication Auteurs : Styliani Verykokou, Auteur ; Charalabos Ioannnidis, Auteur Année de publication : 2016 Article en page(s) : pp 281 - 303 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] automatisation
[Termes IGN] calage
[Termes IGN] géoréférencement
[Termes IGN] image aérienne à axe vertical
[Termes IGN] image aérienne oblique
[Termes IGN] scène urbaine
[Termes IGN] système de référence géodésique
[Termes IGN] visée oblique
[Termes IGN] visée verticaleRésumé : (Auteur) Multi-perspective airborne images that combine oblique and vertical views of the ground have proved to be a valuable source of information for numerous applications requiring a digital representation of the world. In this paper, an automatic methodology for rough georeferencing of large datasets of multiview oblique and vertical aerial images of urban regions without any metadata is proposed. Using feature-based matching combined with robust model fitting and least-squares techniques, the method requires the measurement of a minimum number of points with known coordinates in only one image. The results of this methodology are discussed through the presentation of a developed software suite which identifies the overlapping images, georeferences them, extracts their footprints, subdivides the images into groups based on these footprints and detects the images that cover a specific region. Numéro de notice : A2016-722 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1111/phor.12156 Date de publication en ligne : 18/09/2016 En ligne : https://doi.org/10.1111/phor.12156 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=82246
in Photogrammetric record > vol 31 n° 155 (September - November 2016) . - pp 281 - 303[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 106-2016031 RAB Revue Centre de documentation En réserve L003 Disponible Blending zone determination for aerial orthimage mosaicking / Chao-Hung Lin in ISPRS Journal of photogrammetry and remote sensing, vol 119 (September 2016)
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Titre : Blending zone determination for aerial orthimage mosaicking Type de document : Article/Communication Auteurs : Chao-Hung Lin, Auteur ; Bo-Heng Chen, Auteur ; Bo-Yi Lin, Auteur ; Han-Szu Chou, Auteur Année de publication : 2016 Article en page(s) : pp 426 - 436 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Orthophotographie, orthoimage
[Termes IGN] aberration chromatique
[Termes IGN] aberration instrumentale
[Termes IGN] lissage de valeur
[Termes IGN] mosaïquage d'images
[Termes IGN] orthophotoplan numérique
[Termes IGN] raccord d'images
[Termes IGN] similitude spectrale
[Termes IGN] valeur radiométrique
[Termes IGN] zone tamponRésumé : (Auteur) Creating a composed image from a set of aerial images is a fundamental step in orthomosaic generation. One of the processes involved in this technique is determining an optimal seamline in an overlapping region to stitch image patches seamlessly. Most previous studies have solved this optimization problem by searching for a one-pixel-wide seamline with an objective function. This strategy significantly reduced pixel mismatches on the seamline caused by geometric distortions of images but did not fully consider color discontinuity and mismatch problems that occur around the seamline, which sometimes cause mosaicking artifacts. This study proposes a blending zone determination scheme with a novel path finding algorithm to reduce the occurrence of unwanted artifacts. Instead of searching for a one-pixel-wide seamline, a blending zone, which is a k-pixel-wide seamline that passes through high-similarity pixels in the overlapping region, is determined using a hierarchical structure. This strategy allows for not only seamless stitching but also smooth color blending of neighboring image patches. Moreover, the proposed method searches for a blending zone without the pre-process of highly mismatched pixel removal and additional geographic data of road vectors and digital surface/elevation models, which increases the usability of the approach. Qualitative and quantitative analyses of aerial images demonstrate the superiority of the proposed method to related methods in terms of avoidance of passing highly mismatched pixels. Numéro de notice : A2016-791 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2016.07.005 En ligne : https://doi.org/10.1016/j.isprsjprs.2016.07.005 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=82508
in ISPRS Journal of photogrammetry and remote sensing > vol 119 (September 2016) . - pp 426 - 436[article]Estimating forest species abundance through linear unmixing of CHRIS/PROBA imagery / S. Stagakis in ISPRS Journal of photogrammetry and remote sensing, vol 119 (September 2016)
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Titre : Estimating forest species abundance through linear unmixing of CHRIS/PROBA imagery Type de document : Article/Communication Auteurs : S. Stagakis, Auteur ; Theofilos Vanikiotis, Auteur ; Olga Sykioti, Auteur Année de publication : 2016 Article en page(s) : pp 79 - 89 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] analyse des mélanges spectraux
[Termes IGN] carte de la végétation
[Termes IGN] classification bayesienne
[Termes IGN] effet d'ombre
[Termes IGN] espèce végétale
[Termes IGN] Fagus sylvatica
[Termes IGN] Grèce
[Termes IGN] image hyperspectrale
[Termes IGN] image Landsat-8
[Termes IGN] image PROBA-CHRIS
[Termes IGN] orthoimage
[Termes IGN] parc naturel national
[Termes IGN] partition d'image
[Termes IGN] Pinus nigra
[Termes IGN] richesse floristique
[Vedettes matières IGN] Inventaire forestierRésumé : (Auteur) The advancing technology of hyperspectral remote sensing offers the opportunity of accurate land cover characterization of complex natural environments. In this study, a linear spectral unmixing algorithm that incorporates a novel hierarchical Bayesian approach (BI-ICE) was applied on two spatially and temporally adjacent CHRIS/PROBA images over a forest in North Pindos National Park (Epirus, Greece). The scope is to investigate the potential of this algorithm to discriminate two different forest species (i.e. beech – Fagus sylvatica, pine – Pinus nigra) and produce accurate species-specific abundance maps. The unmixing results were evaluated in uniformly distributed plots across the test site using measured fractions of each species derived by very high resolution aerial orthophotos. Landsat-8 images were also used to produce a conventional discrete-type classification map of the test site. This map was used to define the exact borders of the test site and compare the thematic information of the two mapping approaches (discrete vs abundance mapping). The required ground truth information, regarding training and validation of the applied mapping methodologies, was collected during a field campaign across the study site. Abundance estimates reached very good overall accuracy (R2 = 0.98, RMSE = 0.06). The most significant source of error in our results was due to the shadowing effects that were very intense in some areas of the test site due to the low solar elevation during CHRIS acquisitions. It is also demonstrated that the two mapping approaches are in accordance across pure and dense forest areas, but the conventional classification map fails to describe the natural spatial gradients of each species and the actual species mixture across the test site. Overall, the BI-ICE algorithm presented increased potential to unmix challenging objects with high spectral similarity, such as different vegetation species, under real and not optimum acquisition conditions. Its full potential remains to be investigated in further and more complex study sites in view of the upcoming satellite hyperspectral missions. Numéro de notice : A2016-778 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2016.05.013 En ligne : https://doi.org/10.1016/j.isprsjprs.2016.05.013 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=82473
in ISPRS Journal of photogrammetry and remote sensing > vol 119 (September 2016) . - pp 79 - 89[article]Geometric calibration of a hyperspectral frame camera / Raquel A. de Oliveira in Photogrammetric record, vol 31 n° 155 (September - November 2016)
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Titre : Geometric calibration of a hyperspectral frame camera Type de document : Article/Communication Auteurs : Raquel A. de Oliveira, Auteur ; Antonio Maria Garcia Tommaselli, Auteur ; Eija Honkavaara, Auteur Année de publication : 2016 Article en page(s) : pp 325 - 347 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Acquisition d'image(s) et de donnée(s)
[Termes IGN] étalonnage de capteur (imagerie)
[Termes IGN] étalonnage géométrique
[Termes IGN] filtre adaptatif
[Termes IGN] image hyperspectrale
[Termes IGN] interféromètreRésumé : (Auteur) Recently, miniaturised hyperspectral sensors operable from small unmanned airborne vehicle platforms have entered the market. The emerging hyperspectral imaging technologies, based on frame cameras and tuneable filters, are attractive alternatives to hyperspectral pushbroom sensors. This paper addresses the geometric calibration process of a hyperspectral frame camera based on a Fabry–Perot interferometer. However, the addition of more optical elements in front of the image sensor can affect the parameters related to the internal geometry of the camera, and a deficiency in knowledge regarding these parameters can have a critical effect on the accuracy of 3D measurements in photogrammetric applications. The experiments focused on assessing the self-calibrating bundle adjustment to verify the behaviour of the interior parameters, considering different spectral bands. The results indicated that the applied self-calibration method can accurately characterise the interior parameters of this camera and that one set of parameters is required for each internal sensor. Numéro de notice : A2016-724 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1111/phor.12153 Date de publication en ligne : 24/08/2016 En ligne : https://doi.org/10.1111/phor.12153 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=82256
in Photogrammetric record > vol 31 n° 155 (September - November 2016) . - pp 325 - 347[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 106-2016031 RAB Revue Centre de documentation En réserve L003 Disponible Mapping of land cover in northern California with simulated hyperspectral satellite imagery / Matthew L. Clark in ISPRS Journal of photogrammetry and remote sensing, vol 119 (September 2016)
PermalinkNoise removal from hyperspectral image with joint spectral–spatial distributed sparse representation / Jie Li in IEEE Transactions on geoscience and remote sensing, vol 54 n° 9 (September 2016)
PermalinkRegression wavelet analysis for lossless coding of remote-sensing data / Naoufal Amrani in IEEE Transactions on geoscience and remote sensing, vol 54 n° 9 (September 2016)
PermalinkRetrieval of leaf area index in different plant species using thermal hyperspectral data / Elnaz Neinavaz in ISPRS Journal of photogrammetry and remote sensing, vol 119 (September 2016)
PermalinkSatellite images analysis for shadow detection and building height estimation / Gregoris Liasis in ISPRS Journal of photogrammetry and remote sensing, vol 119 (September 2016)
PermalinkSemiblind hyperspectral unmixing in the presence of spectral library mismatches / Xiao Fu in IEEE Transactions on geoscience and remote sensing, vol 54 n° 9 (September 2016)
PermalinkShadow 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)
PermalinkThe impact of integrating WorldView-2 sensor and environmental variables in estimating plantation forest species aboveground biomass and carbon stocks in uMgeni Catchment, South Africa / Timothy Dube in ISPRS Journal of photogrammetry and remote sensing, vol 119 (September 2016)
PermalinkTwo heads are better than one / Brian Curtiss in GEO: Geoconnexion international, vol 15 n° 8 (September 2016)
PermalinkBasal area and diameter distribution estimation using stereoscopic hemispherical images / Mariola Sánchez-González in Photogrammetric Engineering & Remote Sensing, PERS, vol 82 n° 8 (August 2016)
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