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Extended random walker-based classification of hyperspectral images / Xudong Kang in IEEE Transactions on geoscience and remote sensing, vol 53 n° 1 (January 2015)
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Titre : Extended random walker-based classification of hyperspectral images Type de document : Article/Communication Auteurs : Xudong Kang, Auteur ; Shutao Li, Auteur ; Leyuan Fang, Auteur ; et al., Auteur Année de publication : 2015 Article en page(s) : pp 144 - 153 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] classification spectrale
[Termes IGN] graphe
[Termes IGN] image hyperspectrale
[Termes IGN] segmentation d'imageRésumé : (Auteur) This paper introduces a novel spectral-spatial classification method for hyperspectral images based on extended random walkers (ERWs), which consists of two main steps. First, a widely used pixelwise classifier, i.e., the support vector machine (SVM), is adopted to obtain classification probability maps for a hyperspectral image, which reflect the probabilities that each hyperspectral pixel belongs to different classes. Then, the obtained pixelwise probability maps are optimized with the ERW algorithm that encodes the spatial information of the hyperspectral image in a weighted graph. Specifically, the class of a test pixel is determined based on three factors, i.e., the pixelwise statistics information learned by a SVM classifier, the spatial correlation among adjacent pixels modeled by the weights of graph edges, and the connectedness between the training and test samples modeled by random walkers. Since the three factors are all well considered in the ERW-based global optimization framework, the proposed method shows very good classification performances for three widely used real hyperspectral data sets even when the number of training samples is relatively small. Numéro de notice : A2015-030 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2014.2319373 En ligne : https://doi.org/10.1109/TGRS.2014.2319373 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=75111
in IEEE Transactions on geoscience and remote sensing > vol 53 n° 1 (January 2015) . - pp 144 - 153[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-2015011 RAB Revue Centre de documentation En réserve L003 Disponible Exterior orientation of hyperspectral frame images collected with UAV for forest applications / Adilson Berveglieri (2015)
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Titre : Exterior orientation of hyperspectral frame images collected with UAV for forest applications Type de document : Article/Communication Auteurs : Adilson Berveglieri, Auteur ; Antonio Maria Garcia Tommaselli, Auteur Editeur : International Society for Photogrammetry and Remote Sensing ISPRS Année de publication : 2015 Collection : International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, ISSN 1682-1750 num. 40-3/W4 Conférence : EuroCOW 2016, the European Calibration and Orientation Workshop 10/02/2016 12/02/2016 Lausanne Suisse ISPRS OA Archives Importance : pp 45 - 50 Format : 21 x 30 cm Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Photogrammétrie numérique
[Termes IGN] Brésil
[Termes IGN] compensation par faisceaux
[Termes IGN] drone
[Termes IGN] forêt tropicale
[Termes IGN] image hyperspectrale
[Termes IGN] orientation externe
[Termes IGN] point d'appui
[Termes IGN] récepteur bifréquenceRésumé : (auteur) This paper describes a preliminary study on the image orientation acquired by a hyperspectral frame camera for applications in small tropical forest areas with dense vegetation. Since access to the interior of forests is complicated and Ground Control Points (GCPs) are not available, this study conducts an assessment of the altimetry accuracy provided by control targets installed on one border of an image block, simulating it outside a forest. A lightweight Unmanned Aerial Vehicle (UAV) was equipped with a hyperspectral camera and a dual-frequency GNSS receiver to collect images at two flying strips covering a vegetation area. The assessment experiments were based on Bundle Block Adjustment (BBA) with images of two spectral bands (from two sensors) using several weighted constraints in the camera position. Trials with GCPs (presignalized targets) positioned only on one side of the image block were compared with trials using GCPs in the corners. Analyses were performed on altimetry discrepancies obtained from altimetry checkpoints. The results showed a discrepancy in Z coordinate of approximately 40 cm using the proposed technique, which is sufficient for applications in forests. Numéro de notice : C2016-002 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Communication En ligne : http://dx.doi.org/10.5194/isprs-archives-XL-3-W4-45-2016 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=80321 Extraction of optimal spectral bands using hierarchical band merging out of hyperspectral data / Arnaud Le Bris (2015)
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Titre : Extraction of optimal spectral bands using hierarchical band merging out of hyperspectral data Type de document : Article/Communication Auteurs : Arnaud Le Bris , Auteur ; Nesrine Chehata
, Auteur ; Xavier Briottet
, Auteur ; Nicolas Paparoditis
, Auteur
Editeur : International Society for Photogrammetry and Remote Sensing ISPRS Année de publication : 2015 Collection : International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, ISSN 1682-1750 num. 40-3/W3 Projets : HYEP / Weber, Christiane Conférence : ISPRS 2015, Geospatial Week : Laserscanning, ISSDQ, CMRT, ISA, GeoVIS, GeoBigData 28/09/2015 03/10/2015 La Grande Motte France ISPRS OA Archives Importance : pp 459 - 465 Format : 21 x 30 cm Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] fusion de données
[Termes IGN] image hyperspectraleRésumé : (auteur) Spectral optimization consists in identifying the most relevant band subset for a specific application. It is a way to reduce hyperspectral data huge dimensionality and can be applied to design specific superspectral sensors dedicated to specific land cover applications. Spectral optimization includes both band selection and band extraction. On the one hand, band selection aims at selecting an optimal band subset (according to a relevance criterion) among the bands of a hyperspectral data set, using automatic feature selection algorithms. On the other hand, band extraction defines the most relevant spectral bands optimizing both their position along the spectrum and their width. The approach presented in this paper first builds a hierarchy of groups of adjacent bands, according to a relevance criterion to decide which adjacent bands must be merged. Then, band selection is performed at the different levels of this hierarchy. Two approaches were proposed to achieve this task : a greedy one and a new adaptation of an incremental feature selection algorithm to this hierarchy of merged bands. Numéro de notice : C2015-007 Affiliation des auteurs : LASTIG MATIS+Ext (2012-2019) Thématique : IMAGERIE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.5194/isprsarchives-XL-3-W3-459-2015 Date de publication en ligne : 20/08/2015 En ligne : http://dx.doi.org/10.5194/isprsarchives-XL-3-W3-459-2015 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=80297 Hierarchical unsupervised change detection in multitemporal hyperspectral images / S. Liu in IEEE Transactions on geoscience and remote sensing, vol 53 n° 1 (January 2015)
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Titre : Hierarchical unsupervised change detection in multitemporal hyperspectral images Type de document : Article/Communication Auteurs : S. Liu, Auteur ; Lorenzo Bruzzone, Auteur ; Francesca Bovolo, Auteur ; Peijun Du, Auteur Année de publication : 2015 Article en page(s) : pp 244 - 260 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] analyse diachronique
[Termes IGN] approche hiérarchique
[Termes IGN] détection de changement
[Termes IGN] image hyperspectrale
[Termes IGN] image multitemporelleRésumé : (Auteur) The new generation of satellite hyperspectral (HS) sensors can acquire very detailed spectral information directly related to land surface materials. Thus, when multitemporal images are considered, they allow us to detect many potential changes in land covers. This paper addresses the change-detection (CD) problem in multitemporal HS remote sensing images, analyzing the complexity of this task. A novel hierarchical CD approach is proposed, which is aimed at identifying all the possible change classes present between the considered images. In greater detail, in order to formalize the CD problem in HS images, an analysis of the concept of “change” is given from the perspective of pixel spectral behaviors. The proposed novel hierarchical scheme is developed by considering spectral change information to identify the change classes having discriminable spectral behaviors. Due to the fact that, in real applications, reference samples are often not available, the proposed approach is designed in an unsupervised way. Experimental results obtained on both simulated and real multitemporal HS images demonstrate the effectiveness of the proposed CD method. Numéro de notice : A2015-031 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2014.2321277 En ligne : https://doi.org/10.1109/TGRS.2014.2321277 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=75112
in IEEE Transactions on geoscience and remote sensing > vol 53 n° 1 (January 2015) . - pp 244 - 260[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-2015011 RAB Revue Centre de documentation En réserve L003 Disponible Hyperspectral image denoising via sparse representation and low-rank constraint / Yong-Qiang Zhao in IEEE Transactions on geoscience and remote sensing, vol 53 n° 1 (January 2015)
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Titre : Hyperspectral image denoising via sparse representation and low-rank constraint Type de document : Article/Communication Auteurs : Yong-Qiang Zhao, Auteur ; Jingxiang Yang, Auteur Année de publication : 2015 Article en page(s) : pp 296 - 308 Note générale : Bibliogaphie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] appariement d'images
[Termes IGN] filtrage du bruit
[Termes IGN] image hyperspectrale
[Termes IGN] redondance de donnéesRésumé : (Auteur) Hyperspectral image (HSI) denoising is an essential preprocess step to improve the performance of subsequent applications. For HSI, there is much global and local redundancy and correlation (RAC) in spatial/spectral dimensions. In addition, denoising performance can be improved greatly if RAC is utilized efficiently in the denoising process. In this paper, an HSI denoising method is proposed by jointly utilizing the global and local RAC in spatial/spectral domains. First, sparse coding is exploited to model the global RAC in the spatial domain and local RAC in the spectral domain. Noise can be removed by sparse approximated data with learned dictionary. At this stage, only local RAC in the spectral domain is employed. It will cause spectral distortion. To compensate the shortcoming of local spectral RAC, low-rank constraint is used to deal with the global RAC in the spectral domain. Different hyperspectral data sets are used to test the performance of the proposed method. The denoising results by the proposed method are superior to results obtained by other state-of-the-art hyperspectral denoising methods. Numéro de notice : A2015-033 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2014.2321557 En ligne : https://doi.org/10.1109/TGRS.2014.2321557 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=75115
in IEEE Transactions on geoscience and remote sensing > vol 53 n° 1 (January 2015) . - pp 296 - 308[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-2015011 RAB Revue Centre de documentation En réserve L003 Disponible PermalinkPermalinkMediterranean forest species mapping using classification of Hyperion imagery / Georgia Galidaki in Geocarto international, vol 30 n° 1 - 2 (January - February 2015)
PermalinkPermalinkPerformance assessment of a recent change detection method for homogeneous and heterogeneous images / Jorge Prendes in Revue Française de Photogrammétrie et de Télédétection, n° 209 (Janvier 2015)
PermalinkPléiades satellites image quality commissioning / Laurent Lebègue in Revue Française de Photogrammétrie et de Télédétection, n° 209 (Janvier 2015)
PermalinkPrediction of the presence of topsoil nitrogen from spaceborne hyperspectral data / Binny Gopal in Geocarto international, vol 30 n° 1 - 2 (January - February 2015)
PermalinkA Random Forest class memberships based wrapper band selection criterion : application to hyperspectral / Arnaud Le Bris (2015)
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