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An experimental comparison of directly and indirectly derived modulation transfer functions / Chia-Hsiang Yang in Photogrammetric record, vol 30 n° 149 (March - May 2015)
[article]
Titre : An experimental comparison of directly and indirectly derived modulation transfer functions Type de document : Article/Communication Auteurs : Chia-Hsiang Yang, Auteur ; Shue-Chia Wang, Auteur ; Peter T. Y. Shih, Auteur ; et al., Auteur Année de publication : 2015 Article en page(s) : pp 100 - 114 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse comparative
[Termes IGN] estimation de précision
[Termes IGN] étalement radiométrique
[Termes IGN] fonction de transfert de modulationRésumé : (Auteur) The modulation transfer function (MTF) is the indicator most frequently used for image resolution assessment. Traditionally in photogrammetry, the MTF is directly estimated using specifically designed targets such as the USAF 1952 three-bar resolution test target, but it can also be indirectly derived from the system degradation function known as the point-spread function (PSF). Theoretically, MTF and PSF are related through a spatial–frequency domain transformation (a Fourier transformation), meaning the same attributes are expressed in different domains. When using real images, however, it is not clear whether these two functions produce the same result. In this study, both spatial and frequency domain approaches were experimentally compared through simulations. Results show that the MTF derived from the PSF has better accuracy than an MTF estimated directly from the resolution target. Numéro de notice : A2015-365 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1111/phor.12098 Date de publication en ligne : 13/03/2015 En ligne : https://doi.org/10.1111/phor.12098 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=76802
in Photogrammetric record > vol 30 n° 149 (March - May 2015) . - pp 100 - 114[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 106-2015011 RAB Revue Centre de documentation En réserve L003 Disponible Automated 3D feature matching / Tzu-Yi Chuang in Photogrammetric record, vol 30 n° 149 (March - May 2015)
[article]
Titre : Automated 3D feature matching Type de document : Article/Communication Auteurs : Tzu-Yi Chuang, Auteur ; Jen-Jer Jaw, Auteur Année de publication : 2015 Article en page(s) : pp 8 - 29 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] ajustement de paramètres
[Termes IGN] appariement d'images
[Termes IGN] appariement de données localisées
[Termes IGN] données localisées 3D
[Termes IGN] primitive volumique
[Termes IGN] semis de points
[Termes IGN] translationRésumé : (Auteur) Three-dimensional (3D) feature-matching techniques, which are essential for progress towards an automated feature-based procedure, have attracted considerable research attention in both the photogrammetry and computer vision communities. This study introduces a novel matching approach, called RSTG, that comprises four major phases: rotation alignment; scale estimation; translation alignment; and geometry checks. These steps efficiently determine a feature-based correspondence and frame transformation between datasets. RSTG analyses the similarity and relative geometry of features by employing feature observations and their uncertainty; this allows different types of features to be matched exclusively or simultaneously. This study validates the proposed method with both simulated and real datasets, demonstrating its effectiveness with satisfactory matching rates in a diverse range of feature-based point cloud registration tasks. Numéro de notice : A2015-361 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1111/phor.12089 Date de publication en ligne : 12/02/2015 En ligne : https://doi.org/10.1111/phor.12089 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=76798
in Photogrammetric record > vol 30 n° 149 (March - May 2015) . - pp 8 - 29[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 106-2015011 RAB Revue Centre de documentation En réserve L003 Disponible Collaborative representation for hyperspectral anomaly detection / Wei Li in IEEE Transactions on geoscience and remote sensing, vol 53 n° 3 (March 2015)
[article]
Titre : Collaborative representation for hyperspectral anomaly detection Type de document : Article/Communication Auteurs : Wei Li, Auteur ; Qian Du, Auteur Année de publication : 2015 Article en page(s) : pp 1463 - 1474 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] classification pixellaire
[Termes IGN] détection d'anomalie
[Termes IGN] distance pondérée
[Termes IGN] image hyperspectrale
[Termes IGN] matrice
[Termes IGN] optimisation (mathématiques)
[Termes IGN] plus proche voisin, algorithme duRésumé : (Auteur) In this paper, collaborative representation is proposed for anomaly detection in hyperspectral imagery. The algorithm is directly based on the concept that each pixel in background can be approximately represented by its spatial neighborhoods, while anomalies cannot. The representation is assumed to be the linear combination of neighboring pixels, and the collaboration of representation is reinforced by l2-norm minimization of the representation weight vector. To adjust the contribution of each neighboring pixel, a distance-weighted regularization matrix is included in the optimization problem, which has a simple and closed-form solution. By imposing the sum-to-one constraint to the weight vector, the stability of the solution can be enhanced. The major advantage of the proposed algorithm is the capability of adaptively modeling the background even when anomalous pixels are involved. A kernel extension of the proposed approach is also studied. Experimental results indicate that our proposed detector may outperform the traditional detection methods such as the classic Reed-Xiaoli (RX) algorithm, the kernel RX algorithm, and the state-of-the-art robust principal component analysis based and sparse-representation-based anomaly detectors, with low computational cost. Numéro de notice : A2015-133 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2014.2343955 Date de publication en ligne : 12/08/2014 En ligne : https://doi.org/10.1109/TGRS.2014.2343955 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=75799
in IEEE Transactions on geoscience and remote sensing > vol 53 n° 3 (March 2015) . - pp 1463 - 1474[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-2015031 RAB Revue Centre de documentation En réserve L003 Disponible Constrained least squares algorithms for nonlinear unmixing of hyperspectral imagery / Hanye Pu in IEEE Transactions on geoscience and remote sensing, vol 53 n° 3 (March 2015)
[article]
Titre : Constrained least squares algorithms for nonlinear unmixing of hyperspectral imagery Type de document : Article/Communication Auteurs : Hanye Pu, Auteur ; Zhao Chen, Auteur ; Bin Wang, Auteur ; et al., Auteur Année de publication : 2015 Article en page(s) : pp 1287 - 1303 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse des mélanges spectraux
[Termes IGN] contrainte d'intégrité
[Termes IGN] image hyperspectrale
[Termes IGN] méthode des moindres carrésRésumé : (Auteur) Hyperspectral unmixing is an important issue in hyperspectral image processing. In this paper, we transform the unmixing problem into a constrained nonlinear least squares (CNLS) problem by introducing the abundance sum-to-one constraint, abundance nonnegative constraint, and bound constraints on nonlinearity parameters. The new CNLS-based algorithms assume that the mixing mechanism of each observed pixel can be described by two forms. One is a sum of linear mixtures of endmember spectra and nonlinear variations in reflectance, and the other is a joint mixture resulting from the linearity and nonlinearity in hyperspectral data. For the former, an alternating iterative optimization algorithm is developed to solve the problem of CNLS. As for the latter, the structured total least squares optimization approach is used to obtain the abundance vectors and nonlinearity parameters simultaneously. Current mixing models can be interpreted by either or both of these two mechanisms. A comparative analysis based on Monte Carlo simulations and real data experiments is conducted to evaluate the proposed algorithms and five other state-of-the-art algorithms. Experimental results show that the proposed algorithms give outstanding performance of hyperspectral nonlinear unmixing for both synthetic data and real hyperspectral images, as satisfactory accuracy in term of abundance fractions and low computational complexity are observed. Numéro de notice : A2015-131 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2014.2336858 Date de publication en ligne : 30/07/2014 En ligne : https://doi.org/10.1109/TGRS.2014.2336858 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=75794
in IEEE Transactions on geoscience and remote sensing > vol 53 n° 3 (March 2015) . - pp 1287 - 1303[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-2015031 RAB Revue Centre de documentation En réserve L003 Disponible Improving the spatial resolution of landsat TM/ETM+ through fusion with SPOT5 images via learning-based super-resolution / Huihui Song in IEEE Transactions on geoscience and remote sensing, vol 53 n° 3 (March 2015)
[article]
Titre : Improving the spatial resolution of landsat TM/ETM+ through fusion with SPOT5 images via learning-based super-resolution Type de document : Article/Communication Auteurs : Huihui Song, Auteur ; Bo Huang, Auteur ; Qingshan Liu, Auteur ; et al., Auteur Année de publication : 2015 Article en page(s) : pp 1195 - 1204 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] couple stéréoscopique
[Termes IGN] dégradation d'image
[Termes IGN] fauchée
[Termes IGN] fusion d'images
[Termes IGN] image Landsat-ETM+
[Termes IGN] image Landsat-TM
[Termes IGN] image SPOT 5
[Termes IGN] pouvoir de résolution géométrique
[Termes IGN] résolution multipleRésumé : (Auteur) To take advantage of the wide swath width of Landsat Thematic Mapper (TM)/Enhanced Thematic Mapper Plus (ETM+) images and the high spatial resolution of Système Pour l'Observation de la Terre 5 (SPOT5) images, we present a learning-based super-resolution method to fuse these two data types. The fused images are expected to be characterized by the swath width of TM/ETM+ images and the spatial resolution of SPOT5 images. To this end, we first model the imaging process from a SPOT image to a TM/ETM+ image at their corresponding bands, by building an image degradation model via blurring and downsampling operations. With this degradation model, we can generate a simulated Landsat image from each SPOT5 image, thereby avoiding the requirement for geometric coregistration for the two input images. Then, band by band, image fusion can be implemented in two stages: 1) learning a dictionary pair representing the high- and low-resolution details from the given SPOT5 and the simulated TM/ETM+ images; 2) super-resolving the input Landsat images based on the dictionary pair and a sparse coding algorithm. It is noteworthy that the proposed method can also deal with the conventional spatial and spectral fusion of TM/ETM+ and SPOT5 images by using the learned dictionary pairs. To examine the performance of the proposed method of fusing the swath width of TM/ETM+ and the spatial resolution of SPOT5, we illustrate the fusion results on the actual TM images and compare with several classic pansharpening methods by assuming that the corresponding SPOT5 panchromatic image exists. Furthermore, we implement the classification experiments on both actual images and fusion results to demonstrate the benefits of the proposed method for further classification applications. Numéro de notice : A2015-130 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2014.2335818 Date de publication en ligne : 25/07/2014 En ligne : https://doi.org/10.1109/TGRS.2014.2335818 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=75793
in IEEE Transactions on geoscience and remote sensing > vol 53 n° 3 (March 2015) . - pp 1195 - 1204[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-2015031 RAB Revue Centre de documentation En réserve L003 Disponible Progressive band processing of constrained energy minimization for subpixel detection / Chein-I Chang in IEEE Transactions on geoscience and remote sensing, vol 53 n° 3 (March 2015)PermalinkQuaternion-based solutions for the single photo resection problem / Mehdi Mazaheri in Photogrammetric Engineering & Remote Sensing, PERS, vol 81 n° 3 (March 2015)PermalinkSemisupervised hyperspectral classification using task-driven dictionary learning with Laplacian regularization / Zhangyang Wang in IEEE Transactions on geoscience and remote sensing, vol 53 n° 3 (March 2015)PermalinkSupervised spectral–spatial hyperspectral image classification with weighted markov random fields / Le Sun in IEEE Transactions on geoscience and remote sensing, vol 53 n° 3 (March 2015)PermalinkCoregistration refinement of hyperspectral images and DSM: An object-based approach using spectral information / Janja Avbelj in ISPRS Journal of photogrammetry and remote sensing, vol 100 (February 2015)PermalinkGabor feature-based collaborative representation for hyperspectral imagery classification / Sen Jia in IEEE Transactions on geoscience and remote sensing, vol 53 n° 2 (February 2015)PermalinkHyperspectral Band Selection by Multitask Sparsity Pursuit / Yuan Yuan in IEEE Transactions on geoscience and remote sensing, vol 53 n° 2 (February 2015)PermalinkRadiometric and geometric evaluation of GeoEye-1, WorldView-2 and Pléiades-1A stereo images for 3D information extraction / Daniela Poli in ISPRS Journal of photogrammetry and remote sensing, vol 100 (February 2015)PermalinkSparse unmixing of hyperspectral data using spectral a priori information / Wei Tang in IEEE Transactions on geoscience and remote sensing, vol 53 n° 2 (February 2015)PermalinkAn abundance characteristic-based independent component analysis for hyperspectral unmixing / Nan Wang in IEEE Transactions on geoscience and remote sensing, vol 53 n° 1 (January 2015)PermalinkAutomatic spatial–spectral feature selection for hyperspectral image via discriminative sparse multimodal learning / Qian Zhang in IEEE Transactions on geoscience and remote sensing, vol 53 n° 1 (January 2015)PermalinkCorrection of distorsions in YG-12 high-resolution panchromatic images / Yonghua Jiang in Photogrammetric Engineering & Remote Sensing, PERS, vol 81 n° 1 (January 2015)PermalinkEstimation de la température de surface de la mer par Météosat seconde génération MSG-1 / Abdelkader Labbi in Photo interprétation, European journal of applied remote sensing, vol 51 n° 1 (janvier 2015)PermalinkExtended random walker-based classification of hyperspectral images / Xudong Kang in IEEE Transactions on geoscience and remote sensing, vol 53 n° 1 (January 2015)PermalinkExtraction of optimal spectral bands using hierarchical band merging out of hyperspectral data / Arnaud Le Bris (2015)PermalinkHyperspectral 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)PermalinkPermalinkNote technique : note sur l’utilisation du logiciel CROP-VGT appliqué aux images NDVI du capteur SPOT-Végétation / Natacha Volto in Photo interprétation, European journal of applied remote sensing, vol 51 n° 1 (janvier 2015)PermalinkPerformance 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)PermalinkPrédire la structure des forêts tropicales humides calédoniennes : analyse texturale de la canopée sur des images Pléiades / Elodie Blanchard in Revue Française de Photogrammétrie et de Télédétection, n° 209 (Janvier 2015)PermalinkA Random Forest class memberships based wrapper band selection criterion : application to hyperspectral / Arnaud Le Bris (2015)PermalinkPermalinkSpatial-aware dictionary learning for hyperspectral image classification / Ali Soltani-Farani in IEEE Transactions on geoscience and remote sensing, vol 53 n° 1 (January 2015)PermalinkSpectral–spatial classification of hyperspectral data via morphological component analysis-based image separation / Zhaohui Xue in IEEE Transactions on geoscience and remote sensing, vol 53 n° 1 (January 2015)PermalinkSub-pixel-scale land cover map updating by integrating change detection and sub-pixel mapping / Xiaodong Li in Photogrammetric Engineering & Remote Sensing, PERS, vol 81 n° 1 (January 2015)PermalinkThe Guided Bilateral Filter: When the Joint/Cross Bilateral Filter Becomes Robust / Laurent Caraffa (2015)PermalinkEccentricity in images of circular and spherical targets and its impact on spatial intersection / Thomas Luhmann in Photogrammetric record, vol 29 n° 148 (December 2014 - February 2015)PermalinkEvaluating tree detection and segmentation routines on very high resolution UAV LiDAR data / Luke Wallace in IEEE Transactions on geoscience and remote sensing, vol 52 n° 12 (December 2014)PermalinkManifold-based sparse representation for hyperspectral image classification / Yuan Yan Tang in IEEE Transactions on geoscience and remote sensing, vol 52 n° 12 (December 2014)PermalinkRevue des méthodes de prétraitement des données d'imagerie hyperspectrale acquises depuis un drone / Hachem Agili in Geomatica, vol 68 n° 4 (December 2014)PermalinkAdaptive non-local Euclidean medians sparse unmixing for hyperspectral imagery / Ruyi Feng in ISPRS Journal of photogrammetry and remote sensing, vol 97 (November 2014)PermalinkA 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)PermalinkA fast volume-gradient-based band selection method for hyperspectral image / X. Geng in IEEE Transactions on geoscience and remote sensing, vol 52 n° 11 tome 1 (November 2014)PermalinkHyperspectral 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)PermalinkSemi-supervised classification for hyperspectral imagery based on spatial-spectral Label Propagation / L. Wang in ISPRS Journal of photogrammetry and remote sensing, vol 97 (November 2014)PermalinkAdaptive MAP sub-pixel mapping model based on regularization curve for multiple shifted hyperspectral imagery / Yanfei Zhong in ISPRS Journal of photogrammetry and remote sensing, vol 96 (October 2014)PermalinkAutomated retrieval of forest structure variables based on multi-scale texture analysis of VHR satellite imagery / Benoit Beguet in ISPRS Journal of photogrammetry and remote sensing, vol 96 (October 2014)PermalinkHyperspectral imagery for disaggregation of land surface temperature with selected regression algorithms over different land use land cover scenes / Aniruddha Ghosh in ISPRS Journal of photogrammetry and remote sensing, vol 96 (October 2014)PermalinkObject-based hyperspectral classification of urban areas using marker-based hierarchical segmentation / Davood Akbari in Photogrammetric Engineering & Remote Sensing, PERS, vol 80 n° 10 (October 2014)PermalinkClassification of submerged aquatic vegetation in Black River using hyperspectral image analysis / Roshan Pande-Chhetri in Geomatica, vol 68 n° 3 (September 2014)PermalinkImage matching using SIFT features and relaxation labeling technique—A constraint initializing method for dense stereo matching / Jyoti Joglekar in IEEE Transactions on geoscience and remote sensing, vol 52 n° 9 Tome 1 (September 2014)PermalinkRegularized simultaneous forward–backward greedy algorithm for sparse unmixing of hyperspectral data / Wei Tang in IEEE Transactions on geoscience and remote sensing, vol 52 n° 9 Tome 1 (September 2014)PermalinkShadow detection of man-made buildings in high-resolution panchromatic satellite images / Mohamed I. Elbakary in IEEE Transactions on geoscience and remote sensing, vol 52 n° 9 Tome 1 (September 2014)PermalinkSpectral-angle-based Laplacian Eigenmaps for non linear dimensionality reduction of hyperspectral imagery / L. Yan in Photogrammetric Engineering & Remote Sensing, PERS, vol 80 n° 9 (September 2014)PermalinkAn intelligent approach towards automatic shape modelling and object extraction from satellite images using cellular automata based algorithm / P. V. Arun in Geocarto international, vol 29 n° 5 - 6 (August - October 2014)PermalinkAutomated hyperspectral vegetation index retrieval from multiple correlation matrices with HyperCor / Helge Aasen in Photogrammetric Engineering & Remote Sensing, PERS, vol 80 n° 8 (August 2014)PermalinkA class of cloud detection algorithms based on a MAP-MRF approach in space and time / Gemine Vivone in IEEE Transactions on geoscience and remote sensing, vol 52 n° 8 Tome 2 (August 2014)PermalinkGeospatial method for computing supplemental multi-decadal US coastal land use and land cover classification products, using Landsat data and C-CAP products / Joseph P. Spruce in Geocarto international, vol 29 n° 5 - 6 (August - October 2014)PermalinkHyperspectral data dimensionality reduction and the impact of multi-seasonal Hyperion EO-1 imagery on classification accuracies of tropical forest species / Manjit Saini in Photogrammetric Engineering & Remote Sensing, PERS, vol 80 n° 8 (August 2014)PermalinkHyperspectral remote sensing image subpixel target detection based on supervised metric learning / Lefei Zhang in IEEE Transactions on geoscience and remote sensing, vol 52 n° 8 Tome 2 (August 2014)PermalinkKernel sparse multitask learning for hyperspectral image classification with empirical mode decomposition and morphological wavelet-based features / Z. He in IEEE Transactions on geoscience and remote sensing, vol 52 n° 8 Tome 2 (August 2014)PermalinkA rule-based parameter aided with object-based classification approach for extraction of building and roads from WorldView-2 images / Zahra Ziaei in Geocarto international, vol 29 n° 5 - 6 (August - October 2014)PermalinkApproche de détermination de signature de texture : application à la classification de couverts forestiers d’image satellitaire à haute résolution / Wala Zaaboub in Revue Française de Photogrammétrie et de Télédétection, n° 207 (Juillet 2014)PermalinkAn effective morphological index in automatic recognition of built-up area suitable for high spatial resolution images as ALOS and SPOT data / Bo Yu in Photogrammetric Engineering & Remote Sensing, PERS, vol 80 n° 6 (June 2014)PermalinkAnnual crop type classification of the US great plains for 2000 to 20011 / Daniel M. Howard in Photogrammetric Engineering & Remote Sensing, PERS, vol 80 n° 6 (June 2014)PermalinkUne approche basée objet combinée avec les classifieurs avancés (SVM, RF, Extra Trees) pour la détection des changements du bâti / Loubna Elmansouri in Revue internationale de géomatique, vol 24 n° 2 (juin - août 2014)PermalinkAutomatic reconstruction of regular buildings using a shape-based balloon snake model / Diaro Yari in Photogrammetric record, vol 29 n° 146 (June - August 2014)PermalinkCloud removal for remotely sensed images by similar pixel replacement guided with a spatio-temporal MRF model / Qing Cheng in ISPRS Journal of photogrammetry and remote sensing, vol 92 (June 2014)PermalinkDecision fusion in kernel-induced spaces for hyperspectral image classification / Wei Li in IEEE Transactions on geoscience and remote sensing, vol 52 n° 6 Tome 2 (June 2014)PermalinkFeature extraction of hyperspectral images with image fusion and recursive filtering / Xudong Kang in IEEE Transactions on geoscience and remote sensing, vol 52 n° 6 Tome 2 (June 2014)PermalinkIn search of lost time / Jason Hodgert in GEO: Geoconnexion international, vol 13 n° 6 (june 2014)PermalinkPerformance evaluation of object-based and pixel-based building detection algorithms from very high spatial resolution imagery / Iman Khosravi in Photogrammetric Engineering & Remote Sensing, PERS, vol 80 n° 6 (June 2014)PermalinkSemisupervised dual-geometric subspace projection for dimensionality reduction of hyperspectral image data / Shuyuan Yang in IEEE Transactions on geoscience and remote sensing, vol 52 n° 6 Tome 2 (June 2014)PermalinkSignificance analysis of different types of ancillary geodata utilized in a multisource classification process for forest identification in Germany / Michael Förster in IEEE Transactions on geoscience and remote sensing, vol 52 n° 6 Tome 2 (June 2014)PermalinkSubspace matching pursuit for sparse unmixing of hyperspectral data / Zhenwei Shi in IEEE Transactions on geoscience and remote sensing, vol 52 n° 6 Tome 1 (June 2014)PermalinkDouble constrained NMF for hyperspectral unmixing / Xiaoqiang Lu in IEEE Transactions on geoscience and remote sensing, vol 52 n° 5 tome 1 (May 2014)PermalinkHyperspectral image denoising with a spatial–spectral view fusion strategy / Qiangqiang Yuan in IEEE Transactions on geoscience and remote sensing, vol 52 n° 5 tome 1 (May 2014)PermalinkSlow feature analysis for change detection in multispectral imagery / Chen Wu in IEEE Transactions on geoscience and remote sensing, vol 52 n° 5 tome 1 (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)PermalinkGeostatistical methods for predicting soil moisture continuously in a subalpine basin / Katherine E. Williams in Photogrammetric Engineering & Remote Sensing, PERS, vol 80 n° 4 (April 2014)PermalinkHyperspectral-based adaptive matched filter detector error as a function of atmospheric water vapor estimation / Allan W. Yarbrough in IEEE Transactions on geoscience and remote sensing, vol 52 n° 4 (April 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)PermalinkAutomated geometric correction of multispectral images from high resolution CCD Camera (HRCC) on-board CBERS-2 and CBERS-2B / Chabitha Devarj in ISPRS Journal of photogrammetry and remote sensing, vol 89 (March 2014)PermalinkAutomatic registration of coastal remotely sensed imagery by affine invariant feature matching with shoreline constraint / Liang Cheng in Marine geodesy, vol 37 n° 1 (March - May 2014)PermalinkEfficient, simultaneous detection of multi-class geospatial targets based on visual saliency modeling and discriminative learning of sparse coding / Junwei Han in ISPRS Journal of photogrammetry and remote sensing, vol 89 (March 2014)PermalinkA real-time MODIS vegetation product for land surface and numerical weather prediction models / Jonathan L. Case in IEEE Transactions on geoscience and remote sensing, vol 52 n° 3 (March 2014)PermalinkSpatial and spectral image fusion using sparse matrix factorization / Bo Huang in IEEE Transactions on geoscience and remote sensing, vol 52 n° 3 (March 2014)PermalinkSynthetic images for evaluating topographic correction algorithms / Ion Sola in IEEE Transactions on geoscience and remote sensing, vol 52 n° 3 (March 2014)PermalinkUL-Isomap based nonlinear dimensionality reduction for hyperspectral imagery classification / Weiwei Sun in ISPRS Journal of photogrammetry and remote sensing, vol 89 (March 2014)PermalinkAdaptive subpixel mapping based on a multiagent system for remote-sensing imagery / Xiong Xu in IEEE Transactions on geoscience and remote sensing, vol 52 n° 2 (February 2014)PermalinkAutomated parameterisation for multi-scale image segmentation on multiple layers / L. Drăguț 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)PermalinkA GIHS-based spectral preservation fusion method for remote sensing images using edge restored spectral modulation / Xiran Zhou in ISPRS Journal of photogrammetry and remote sensing, vol 88 (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)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)PermalinkStatistical data fusion of multi-sensor AOD over the Continental United States / Sweta Jinnagara Puttaswamy in Geocarto international, vol 29 n° 1 - 2 (February - April 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)PermalinkExtension de l’étiquetage géographique des pixels d’une image par fouille de données / Adrien Gressin in Revue des Nouvelles Technologies de l'Information, E.26 ([23/01/2014])PermalinkAgricultural field delimitation using active learning and random forests margin / Karim Ghariani (2014)Permalink