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Adaptive non-local Euclidean medians sparse unmixing for hyperspectral imagery / Ruyi Feng in ISPRS Journal of photogrammetry and remote sensing, vol 97 (November 2014)
[article]
Titre : Adaptive non-local Euclidean medians sparse unmixing for hyperspectral imagery Type de document : Article/Communication Auteurs : Ruyi Feng, Auteur ; Yanfei Zhong, Auteur ; Liangpei Zhang, Auteur Année de publication : 2014 Article en page(s) : pp 9 – 24 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse des mélanges spectraux
[Termes IGN] image hyperspectrale
[Termes IGN] traitement d'imageRésumé : (Auteur) Sparse unmixing models based on sparse representation theory and a sparse regression model have been successfully applied to hyperspectral remote sensing image unmixing. To better utilize the abundant spatial information and improve the unmixing accuracy, spatial sparse unmixing methods such as the non-local sparse unmixing (NLSU) approach have been proposed. Although the NLSU method utilizes non-local spatial information as the spatial regularization term and obtains a satisfactory unmixing accuracy, the final abundances are affected by the non-local neighborhoods and drift away from the true abundance values when the observed hyperspectral images have high noise levels. Furthermore, NLSU contains two regularization parameters which need to be appropriately set in real applications, which is a difficult task and often has a high computational cost. To solve these problems, an adaptive non-local Euclidean medians sparse unmixing (ANLEMSU) method is proposed to improve NLSU by replacing the non-local means total variation spatial consideration with the non-local Euclidean medians filtering approach. In addition, ANLEMSU utilizes a joint maximum a posteriori (JMAP) strategy to acquire the relationships between the regularization parameters and the estimated abundances, and achieves the fractional abundances adaptively, without the need to set the two regularization parameters manually. The experimental results using both simulated data and real hyperspectral images indicate that ANLEMSU outperforms the previous sparse unmixing algorithms and, hence, provides an effective option for the unmixing of hyperspectral remote sensing imagery. Numéro de notice : A2014-522 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2014.07.009 En ligne : https://doi.org/10.1016/j.isprsjprs.2014.07.009 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=74134
in ISPRS Journal of photogrammetry and remote sensing > vol 97 (November 2014) . - pp 9 – 24[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2014111 RAB Revue Centre de documentation En réserve L003 Disponible Automatic building extraction using a fuzzy active contour model / Mostafa Kabolizade in Photogrammetric Engineering & Remote Sensing, PERS, vol 80 n° 11 (November 2014)
[article]
Titre : Automatic building extraction using a fuzzy active contour model Type de document : Article/Communication Auteurs : Mostafa Kabolizade, Auteur ; Hamid Ebadi, Auteur ; Mehdi Mokhtarzade, Auteur Année de publication : 2014 Article en page(s) : pp 1061 - 1068 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] détection de contours
[Termes IGN] détection du bâti
[Termes IGN] extraction automatiqueRésumé : (Auteur) Automatic building extraction is currently an important research topic in the field of photagrammetry. An active contour model is a well-received approach in this field. This paper proposes an improved active contour model that focuses on building extraction from aerial images and lidar data. The main research concern in this paper is the development of energy functions to the optimum use of expert human knowledge in the overall process. Based on this approach, a new fuzzy inference system for evaluating energy functions was developed by modeling the human perception of various effective parameters in the energy functions. (Compared to the existing active contour models, the new algorithm is capable of directing the initial contour to building feature boundaries more quickly and robustly. Accuracy assessment showed that the proposed model is capable of achieving a shape accuracy of 98 percent and a total accuracy of 97 percent in complex urban areas. Numéro de notice : A2014-617 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.80.11.1061 En ligne : https://doi.org/10.14358/PERS.80.11.1061 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=74923
in Photogrammetric Engineering & Remote Sensing, PERS > vol 80 n° 11 (November 2014) . - pp 1061 - 1068[article]Changing the light azimuth in shaded relief representation by clustering aspect / Fabio Veronesi in Cartographic journal (the), vol 51 n° 4 (November 2014)
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Titre : Changing the light azimuth in shaded relief representation by clustering aspect Type de document : Article/Communication Auteurs : Fabio Veronesi, Auteur ; Lorenz Hurni, Auteur Année de publication : 2014 Article en page(s) : pp 291 - 300 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Rédaction cartographique
[Termes IGN] ArcGIS
[Termes IGN] estompage automatique
[Termes IGN] ombre
[Termes IGN] représentation du relief
[Termes IGN] segmentation d'image
[Termes IGN] système d'information géographiqueRésumé : (Auteur) Manual shading, traditionally produced manually by specifically trained cartographers, is still considered superior to automatic methods, particularly for mountainous landscapes. However, manual shading is time-consuming and its results depend on the cartographer and as such difficult to replicate consistently. For this reason there is a need to create an automatic method to standardize its results. A crucial aspect of manual shading is the continuous change of light direction (azimuth) and angle (zenith) in order to better highlight discrete landforms. Automatic hillshading algorithms, widely available in many geographic information systems (GIS) applications, do not provide this feature. This may cause the resulting shaded relief to appear flat in some areas, particularly in areas where the light source is parallel to the mountain ridge. In this work we present a GIS tool to enhance the visual quality of hillshading. We developed a technique based on clustering aspect to provide a seamless change of lighting throughout the scene. We also provide tools to change the light zenith according to either elevation or slope. This way the cartographer has more room for customizing the shaded relief representation. Moreover, the method is completely automatic and this guarantees consistent and reproducible results. This method has been embedded into an ArcGIS toolbox. Numéro de notice : A2014-641 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1179/1743277414Y.0000000100 En ligne : https://doi.org/10.1179/1743277414Y.0000000100 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=75086
in Cartographic journal (the) > vol 51 n° 4 (November 2014) . - pp 291 - 300[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 030-2014041 RAB Revue Centre de documentation En réserve L003 Disponible A discriminative metric learning based anomaly detection method / Bo Du in IEEE Transactions on geoscience and remote sensing, vol 52 n° 11 tome 1 (November 2014)
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Titre : A discriminative metric learning based anomaly detection method Type de document : Article/Communication Auteurs : Bo Du, Auteur ; L. Zhang, Auteur Année de publication : 2014 Article en page(s) : pp 6844 - 6857 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] apprentissage (cognition)
[Termes IGN] détection d'anomalie
[Termes IGN] extraction de traits caractéristiques
[Termes IGN] image à haute résolutionRésumé : (Auteur) Due to the high spectral resolution, anomaly detection from hyperspectral images provides a new way to locate potential targets in a scene, especially those targets that are spectrally different from the majority of the data set. Conventional Mahalanobis-distance-based anomaly detection methods depend on the background statistics to construct the anomaly detection metric. One of the main problems with these methods is that the Gaussian distribution assumption of the background may not be reasonable. Furthermore, these methods are also susceptible to contamination of the conventional background covariance matrix by anomaly pixels. This paper proposes a new anomaly detection method by effectively exploiting a robust anomaly degree metric for increasing the separability between anomaly pixels and other background pixels, using discriminative information. First, the manifold feature is used so as to divide the pixels into the potential anomaly part and the potential background part. This procedure is called discriminative information learning. A metric learning method is then performed to obtain the robust anomaly degree measurements. Experiments with three hyperspectral data sets reveal that the proposed method outperforms other current anomaly detection methods. The sensitivity of the method to several important parameters is also investigated. Numéro de notice : A2014-541 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2014.2303895 En ligne : https://doi.org/10.1109/TGRS.2014.2303895 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=74158
in IEEE Transactions on geoscience and remote sensing > vol 52 n° 11 tome 1 (November 2014) . - pp 6844 - 6857[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-2014111A RAB Revue Centre de documentation En réserve L003 Disponible Estimating fractional land cover in semi-arid central Kalahari: the impact of mapping method (spectral unmixing vs. object-based image analysis) and vegetation morphology / Niti B. Mishra in Geocarto international, vol 29 n° 7 - 8 (November - December 2014)
[article]
Titre : Estimating fractional land cover in semi-arid central Kalahari: the impact of mapping method (spectral unmixing vs. object-based image analysis) and vegetation morphology Type de document : Article/Communication Auteurs : Niti B. Mishra, Auteur ; K.A. Crews, Auteur Année de publication : 2014 Article en page(s) : pp 860-877 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] analyse de mélange spectral d’extrémités multiples
[Termes IGN] classification orientée objet
[Termes IGN] image Geoeye
[Termes IGN] indice de végétation
[Termes IGN] Kalahari, désert du
[Termes IGN] occupation du sol
[Termes IGN] photosynthèseRésumé : (Auteur) Focusing on the central Kalahari, this study utilized fractional cover of photosynthetic vegetation (fPV), non-photosynthetic vegetation (fNPV) and bare soil (fBS), derived in situ and estimated from GeoEye-1 imagery using Multiple Endmember Spectral Mixture Analysis (MESMA) and object-based image analysis (OBIA) to determine superior method for fractional cover estimation and the impact of vegetation morphology on the estimation accuracy. MESMA mapped fractional cover by testing endmember models of varying complexity. Based on OBIA, image was segmented at five segmentation scales followed by classification. MESMA provided more accurate fractional cover estimates than OBIA. The increasing segmentation scale in OBIA resulted in a consistent increase in error. Different vegetation morphology types showed varied responses to the changing segmentation scale, reflecting their unique ecology and physiognomy. While areas under woody cover produced lower error even at coarse segmentation scales, those with herbaceous cover provided low error only at the fine segmentation scale. Numéro de notice : A2014-470 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2013.868041 En ligne : https://doi.org/10.1080/10106049.2013.868041 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=74047
in Geocarto international > vol 29 n° 7 - 8 (November - December 2014) . - pp 860-877[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 059-2014041 RAB Revue Centre de documentation En réserve L003 Disponible Hyperspectral unmixing with [lq] regularization / Jakob Sigurdsson in IEEE Transactions on geoscience and remote sensing, vol 52 n° 11 tome 1 (November 2014)PermalinkA new sparse source separation-based classification approach / M.A. Loghmari in IEEE Transactions on geoscience and remote sensing, vol 52 n° 11 tome 1 (November 2014)PermalinkRecovering quantitative remote sensing products contaminated by thick clouds and shadows using multitemporal dictionary learning / X. Li in IEEE Transactions on geoscience and remote sensing, vol 52 n° 11 tome 1 (November 2014)PermalinkA robust image matching method based on optimized BaySAC / Zhizhong Kang in Photogrammetric Engineering & Remote Sensing, PERS, vol 80 n° 11 (November 2014)PermalinkAutomatic detection of elevation changes by differential DSM analysis: application to urban areas / Cyrielle Guerin in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol 7 n° 10 (October 2014)PermalinkDetecting cars in UAV images with a catalog-based approach / Thomas Moranduzzo in IEEE Transactions on geoscience and remote sensing, vol 52 n° 10 tome 1 (October 2014)PermalinkHyperspectral image resolution enhancement using high-resolution multispectral image based on spectral unmixing / Mohamed Amine Bendoumi in IEEE Transactions on geoscience and remote sensing, vol 52 n° 10 tome 2 (October 2014)PermalinkIntegration of Lidar and Landsat to estimate forest canopy cover in coastal British Columbia / Oumer S. 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Elbakary in IEEE Transactions on geoscience and remote sensing, vol 52 n° 9 Tome 1 (September 2014)PermalinkTraitement de données Thematic Mapper pour la cartographie multi temporelle du plateau sous-marin autour des îles Kerkennah (Tunisie) / Rim Katlane in Photo interprétation, European journal of applied remote sensing, vol 50 n° 3 - 4 (septembre 2014)PermalinkTropical forest change monitoring / David Belton in GEO: Geoconnexion international, vol 13 n° 8 (september 2014)PermalinkAn intelligent approach towards automatic shape modelling and object extraction from satellite images using cellular automata based algorithm / P. V. 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Rampi in Photogrammetric Engineering & Remote Sensing, PERS, vol 80 n° 5 (May 2014)PermalinkBayesian context-dependent learning for anomaly classification in hyperspectral imagery / Christopher Ratto in IEEE Transactions on geoscience and remote sensing, vol 52 n° 4 (April 2014)PermalinkChange detection in high-resolution land use/land cover geodatabases (at object level) / Emilio Domenech (01/04/2014)PermalinkProgressive band selection of spectral unmixing for hyperspectral imagery / Chein-I Chang in IEEE Transactions on geoscience and remote sensing, vol 52 n° 4 (April 2014)PermalinkReconstruct street network from imprecise excavation data using fuzzy Hough transforms / Cyril de Runz in Geoinformatica, vol 18 n° 2 (April 2014)PermalinkSegmentation d'images aériennes par coopération LPE-régions et LPE-contours, application à la caractérisation de toitures / Youssef El Merabet in Revue Française de Photogrammétrie et de Télédétection, n° 206 (Avril 2014)PermalinkJoining-up the dots / George Skrobanski in GEO: Geoconnexion international, vol 13 n° 3 (march 2014)PermalinkSemi-automated registration of close-range hyperspectral scans using oriented digital camera imagery and a 3D model / Alessandra A. 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Drăguț in ISPRS Journal of photogrammetry and remote sensing, vol 88 (February 2014)PermalinkBi-temporal texton forest for land cover transition detection on remotely sensed imagery / Zhen Lei in IEEE Transactions on geoscience and remote sensing, vol 52 n° 2 (February 2014)PermalinkBlind speckle decorrelation for SAR image despeckling / Alessandro Lapini in IEEE Transactions on geoscience and remote sensing, vol 52 n° 2 (February 2014)PermalinkDetecting subcanopy invasive plant species in tropical rainforest by integrating optical and microwave (InSAR/PolInSAR) remote sensing data, and a decision tree algorithm / Abduwasit Ghulam in ISPRS Journal of photogrammetry and remote sensing, vol 88 (February 2014)PermalinkA fully constrained linear spectral unmixing algorithm based on distance geometry / Hanye Pu in IEEE Transactions on geoscience and remote sensing, vol 52 n° 2 (February 2014)PermalinkModel-based analysis–synthesis for realistic tree reconstruction and growth simulation / Corina Iovan in IEEE Transactions on geoscience and remote sensing, vol 52 n° 2 (February 2014)PermalinkMulti-agent recognition system based on object based image analysis using WorldView-2 / Fatemeh Tabib Mahmoudi in Photogrammetric Engineering & Remote Sensing, PERS, vol 80 n° 2 (February 2014)PermalinkMultiagent object-based classifier for high spatial resolution imagery / Yanfei Zhong in IEEE Transactions on geoscience and remote sensing, vol 52 n° 2 (February 2014)PermalinkMultiple-entity based classification of airborne laser scanning data in urban areas / S. Xu in ISPRS Journal of photogrammetry and remote sensing, vol 88 (February 2014)PermalinkNonlinear unmixing of hyperspectral data using semi-nonnegative matrix factorization / Naoto Yokoya in IEEE Transactions on geoscience and remote sensing, vol 52 n° 2 (February 2014)PermalinkStructured sparse method for hyperspectral unmixing / Feiyun Zhu in ISPRS Journal of photogrammetry and remote sensing, vol 88 (February 2014)PermalinkTime may change me / John Hornsby in GEO: Geoconnexion international, vol 13 n° 2 (february 2014)PermalinkAssessment of the image misregistration effects on object-based change detection / Gang Chen in ISPRS Journal of photogrammetry and remote sensing, vol 87 (January 2014)PermalinkCaractérisation et cartographie de la structure forestière à partir d'images satellitaires à très haute résolution spatiale / Benoit Beguet (2014)PermalinkChange detection in high-resolution land use/land cover geodatabase (at object level) / European Spatial Data Research EuroSDR (2014)PermalinkCollaborative sparse regression for hyperspectral unmixing / Marian-Daniel Iordache in IEEE Transactions on geoscience and remote sensing, vol 52 n° 1 tome 1 (January 2014)PermalinkCombining top-down and bottom-up approaches for building detection in a single very high resolution satellite image / Mahmoud Mohammed Sidi Youssef (2014)PermalinkComparaison de méthodes d'extraction automatique à partir d'images multispectrales / Valerio Baiocchi in Géomatique expert, n° 96 (01/01/2014)PermalinkContextual classification of lidar data and building object detection in urban areas / Joachim Niemeyer in ISPRS Journal of photogrammetry and remote sensing, vol 87 (January 2014)PermalinkDétection de bâtiments à partir d’une image satellitaire par combinaison d’approches ascendante et descendante / Mohamed Mahmoud Sidi Yousseff (2014)PermalinkPermalinkPermalinkFast hierarchical segmentation of high-resolution remote sensing images with adaptative edge penalty / Xuellang Zhang in Photogrammetric Engineering & Remote Sensing, PERS, vol 80 n° 1 (January 2014)PermalinkGénération de modèles numériques de surface et détection de changements 3D à partir d'imagerie satellite stéréoscopique très haute résolution / Cyrielle Guerin (2014)PermalinkGeographic Object-Based Image Analysis: Towards a new paradigm / Thomas Blaschke in ISPRS Journal of photogrammetry and remote sensing, vol 87 (January 2014)PermalinkHierarchical extraction of landslides from multiresolution remotely sensed optical images / Camille Kurtz in ISPRS Journal of photogrammetry and remote sensing, vol 87 (January 2014)PermalinkImagerie de télédétection / Florence Tupin (2014)PermalinkIndividual tree segmentation over large areas using airborne LiDAR point cloud and very high resolution optical imagery / Yuchu Qin (2014)PermalinkPermalinkLarge scale road network extraction in forested moutainous areas using airborne laser scanning data / António Ferraz (2014)PermalinkLiDAR-derived surface roughness texture mapping: Application to mount St. Helens Pumice Plain deposit analysis / Patrick L. Whelley in IEEE Transactions on geoscience and remote sensing, vol 52 n° 1 tome 2 (January 2014)PermalinkA local contrast method for small infrared target detection / C.L. Philip Chen in IEEE Transactions on geoscience and remote sensing, vol 52 n° 1 tome 2 (January 2014)PermalinkMise à jour d’une base de données d’occupation du sol à grande échelle en milieux naturels à partir d’une image satellite THR / Adrien Gressin (2014)PermalinkOpenGL ES 3.0 programming guide / Dan Ginsburg (2014)PermalinkReconstruction de modèles 3D photoréalistes de façades à partir de données image et laser terrestre / Jérôme Demantké (2014)PermalinkRemote sensing image segmentation by combining spectral and texture features / H. Li in IEEE Transactions on geoscience and remote sensing, vol 52 n° 1 tome 1 (January 2014)PermalinkPermalink