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3D hyperspectral point cloud generation: Fusing airborne laser scanning and hyperspectral imaging sensors for improved object-based information extraction / Maximilian Brell in ISPRS Journal of photogrammetry and remote sensing, vol 149 (March 2019)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 149 (March 2019) . - pp 200 - 214 Titre : 3D hyperspectral point cloud generation: Fusing airborne laser scanning and hyperspectral imaging sensors for improved object-based information extraction Type de document : Article/Communication Auteurs : Maximilian Brell, Auteur ; Karl Segl, Auteur ; Luis Guanter, Auteur ; Bodo Bookhagen, Auteur Année de publication : 2019 Article en page(s) : pp 200 - 214 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques [Termes IGN] analyse des mélanges spectraux [Termes IGN] capteur hyperspectral [Termes IGN] classification orientée objet [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] fusion de données [Termes IGN] image hyperspectrale [Termes IGN] impulsion laser [Termes IGN] niveau de détail [Termes IGN] segmentation d'image [Termes IGN] segmentation sémantique [Termes IGN] semis de points Résumé : (Auteur) Remote Sensing technologies allow to map biophysical, biochemical, and earth surface parameters of the land surface. Of especial interest for various applications in environmental and urban sciences is the combination of spectral and 3D elevation information. However, those two data streams are provided separately by different instruments, namely airborne laser scanner (ALS) for elevation and a hyperspectral imager (HSI) for high spectral resolution data. The fusion of ALS and HSI data can thus lead to a single data entity consistently featuring rich structural and spectral information. In this study, we present the application of fusing the first pulse return information from ALS data at a sub-decimeter spatial resolution with the lower-spatial resolution hyperspectral information available from the HSI into a hyperspectral point cloud (HSPC). During the processing, a plausible hyperspectral spectrum is assigned to every first-return ALS point. We show that the complementary implementation of spectral and 3D information at the point-cloud scale improves object-based classification and information extraction schemes. This improvements have great potential for numerous land-cover mapping and environmental applications. Numéro de notice : A2019-119 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2019.01.022 Date de publication en ligne : 06/02/2019 En ligne : https://doi.org/10.1016/j.isprsjprs.2019.01.022 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92448 [article]

Exemplaires(3)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
081-2019031	RAB	Revue	Centre de documentation	En réserve L003	Disponible
081-2019033	DEP-RECP	Revue	LASTIG	Dépôt en unité	Exclu du prêt
081-2019032	DEP-RECF	Revue	Nancy	Dépôt en unité	Exclu du prêt

Hyperspectral and lidar intensity data fusion : A framework for the rigorous correction of illumination, anisotropic effects, and cross calibration / Maximilian Brell in IEEE Transactions on geoscience and remote sensing, vol 55 n° 5 (May 2017)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 55 n° 5 (May 2017) . - pp 2799 - 2810 Titre : Hyperspectral and lidar intensity data fusion : A framework for the rigorous correction of illumination, anisotropic effects, and cross calibration Type de document : Article/Communication Auteurs : Maximilian Brell, Auteur ; Karl Segl, Auteur ; Luis Guanter, Auteur ; Bodo Bookhagen, Auteur Année de publication : 2017 Article en page(s) : pp 2799 - 2810 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques [Termes IGN] anisotropie [Termes IGN] correction radiométrique [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] étalonnage croisé [Termes IGN] fusion d'images [Termes IGN] image hyperspectrale [Termes IGN] intensité lumineuse [Termes IGN] réflectance spectrale Résumé : (Auteur) The fusion of hyperspectral imaging (HSI) sensor and airborne lidar scanner (ALS) data provides promising potential for applications in environmental sciences. Standard fusion approaches use reflectance information from the HSI and distance measurements from the ALS to increase data dimensionality and geometric accuracy. However, the potential for data fusion based on the respective intensity information of the complementary active and passive sensor systems is high and not yet fully exploited. Here, an approach for the rigorous illumination correction of HSI data, based on the radiometric cross-calibrated return intensity information of ALS data, is presented. The cross calibration utilizes a ray tracing-based fusion of both sensor measurements by intersecting their particular beam shapes. The developed method is capable of compensating for the drawbacks of passive HSI systems, such as cast and cloud shadowing effects, illumination changes over time, across track illumination, and partly anisotropy effects. During processing, spatial and temporal differences in illumination patterns are detected and corrected over the entire HSI wavelength domain. The improvement in the classification accuracy of urban and vegetation surfaces demonstrates the benefit and potential of the proposed HSI illumination correction. The presented approach is the first step toward the rigorous in-flight fusion of passive and active system characteristics, enabling new capabilities for a variety of applications. Numéro de notice : A2017-469 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2017.2654516 En ligne : https://doi.org/10.1109/TGRS.2017.2654516 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=86392 [article]

Improving sensor fusion : a parametric method for the geometric coalignment of airborne hyperspectral and lidar data / Maximilian Brell in IEEE Transactions on geoscience and remote sensing, vol 54 n° 6 (June 2016)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 54 n° 6 (June 2016) . - pp 3460 - 3474 Titre : Improving sensor fusion : a parametric method for the geometric coalignment of airborne hyperspectral and lidar data Type de document : Article/Communication Auteurs : Maximilian Brell, Auteur ; Christian Rogass, Auteur ; Karl Segl, Auteur ; et al., Auteur Année de publication : 2016 Article en page(s) : pp 3460 - 3474 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image mixte [Termes IGN] alignement semi-dirigé [Termes IGN] appariement géométrique [Termes IGN] données lidar [Termes IGN] image aérienne [Termes IGN] image hyperspectrale [Termes IGN] image multicapteur [Termes IGN] points homologues [Termes IGN] superposition d'images [Termes IGN] télémétrie laser aéroporté Résumé : (Auteur) Synergistic applications based on integrated hyperspectral and lidar data are receiving a growing interest from the remote-sensing community. A prerequisite for the optimum sensor fusion of hyperspectral and lidar data is an accurate geometric coalignment. The simple unadjusted integration of lidar elevation and hyperspectral reflectance causes a substantial loss of information and does not exploit the full potential of both sensors. This paper presents a novel approach for the geometric coalignment of hyperspectral and lidar airborne data, based on their respective adopted return intensity information. The complete approach incorporates ray tracing and subpixel procedures in order to overcome grid inherent discretization. It aims at the correction of extrinsic and intrinsic (camera resectioning) parameters of the hyperspectral sensor. In additional to a tie-point-based coregistration, we introduce a ray-tracing-based back projection of the lidar intensities for area-based cost aggregation. The approach consists of three processing steps. First is a coarse automatic tie-point-based boresight alignment. The second step coregisters the hyperspectral data to the lidar intensities. Third is a parametric coalignment refinement with an area-based cost aggregation. This hybrid approach of combining tie-point features and area-based cost aggregation methods for the parametric coregistration of hyperspectral intensity values to their corresponding lidar intensities results in a root-mean-square error of 1/3 pixel. It indicates that a highly integrated and stringent combination of different coalignment methods leads to an improvement of the multisensor coregistration. Numéro de notice : A2016-855 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2016.2518930 En ligne : https://doi.org/10.1109/TGRS.2016.2518930 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=82994 [article]

Determination of robust spectral features for identification of urban surface materials in hyperspectral remote sensing data / U. Heiden in Remote sensing of environment, vol 111 n° 4 (28/12/2007)  

Public [article]  inRemote sensing of environment > vol 111 n° 4 (28/12/2007) . - pp 537 - 552 Titre : Determination of robust spectral features for identification of urban surface materials in hyperspectral remote sensing data Type de document : Article/Communication Auteurs : U. Heiden, Auteur ; Karl Segl, Auteur ; S. Roessner, Auteur ; H. Kaufmann, Auteur Année de publication : 2007 Article en page(s) : pp 537 - 552 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] Allemagne [Termes IGN] extraction automatique [Termes IGN] image HYMAP [Termes IGN] image hyperspectrale [Termes IGN] matrice de confusion [Termes IGN] méthode robuste [Termes IGN] milieu urbain [Termes IGN] surface du sol Résumé : (Auteur) Hyperspectral remote sensing data open up new opportunities for analyzing urban areas characterized by a large variety of spectrally distinct surface materials. Spectroscopic analysis using diagnostic spectral features yields the potential for automated identification and mapping of these materials. This study proposes a new approach for the determination and evaluation of such spectral features that are robust against spectral overlap between material classes and within-class variability. Analysis is based on comprehensive field and image spectral libraries of more than 21,000 spectra of surface materials widely-used in German cities. The robustness of the interactively defined spectral features is evaluated by a separability analysis. This method is performed based on confusion matrices for each material computed from classification results. For comparison this analysis is also performed for material-specific gray values of selected bands. The obtained commission and omission errors show superiority of the spectral features compared to gray values for most of the investigated materials. The results indicate that robust spectral features yield the potential for unsupervised detection of endmembers in hyperspectral image data. Copyright Elsevier Numéro de notice : A2007-521 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.rse.2007.04.008 En ligne : https://doi.org/10.1016/j.rse.2007.04.008 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28884 [article]

Fusion of spectral and shape features for identification of urban surface cover types using reflective and thermal hyperspectral data / Karl Segl in ISPRS Journal of photogrammetry and remote sensing, vol 58 n° 1-2 (June - December 2003)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 58 n° 1-2 (June - December 2003) . - pp 99 - 112 Titre : Fusion of spectral and shape features for identification of urban surface cover types using reflective and thermal hyperspectral data Type de document : Article/Communication Auteurs : Karl Segl, Auteur ; S. Roessner, Auteur ; U. Heiden, Auteur ; H. Kaufmann, Auteur Année de publication : 2003 Article en page(s) : pp 99 - 112 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] analyse linéaire des mélanges spectraux [Termes IGN] biotope [Termes IGN] carte d'occupation du sol [Termes IGN] fusion d'images [Termes IGN] image DAIS [Termes IGN] image hyperspectrale [Termes IGN] image thermique [Termes IGN] milieu urbain [Termes IGN] morphologie mathématique [Termes IGN] photo-interprétation assistée par ordinateur [Termes IGN] pixel [Termes IGN] reconnaissance de formes [Termes IGN] réflectance [Termes IGN] utilisation du sol Résumé : (Auteur) The urban environment is characterized by an intense multifunctional use of available spaces, where the preservation of open green spaces is of special importance. For this purpose, areawide urban biotope mapping based on CIR aerial photographs has been carried out for the large cities in Germany during the last 10 years. Because of dynamic urban development and high mapping costs, the municipal authorities are interested in effective methods for mapping urban surface cover types, which can be used for evaluation of ecological conditions in urban structures and supporting updates of biotope maps. Against this background, airborne hyperspectral remote sensing data of the DAIS 7915 instrument have been analyzed for a test site in the city of Dresden (Germany) with regard to their potential for automated materialoriented identification of urban surface cover types. Previous investigations have shown that the high spectral and spatial variabilities of these data require the development of special methods, which are capable of dealing with the resulting mixedpixel problem in its specific characteristics in urban areas. Earlier, methodological developments led to an approach based on a combination of spectral classification and pixeloriented unmixing techniques to facilitate sensible endmember selection based on the reflective bands of the DAIS instrument. This approach is now extended by a shapebased classification technique including the thermal bands of the DAIS instrument to improve the detection of buildings during the process of identifying seedling pixels, which represent the starting points for linear spectral unmixing. This new approach increases the reliability of differentiation between buildings and open spaces, leading to more accurate results for the spatial distribution of surface cover types. Thus, the new approach significantly enhances the exploitation of the information potential of the hyperspectral DAIS 7915 data for an areawide identification of urban surface cover types. Copyright ISPRS Numéro de notice : A2003-088 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/S0924-2716(03)00020-0 En ligne : https://doi.org/10.1016/S0924-2716(03)00020-0 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=22384 [article]

Exemplaires(2)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
081-03032	RAB	Revue	Centre de documentation	En réserve L003	Disponible
081-03031	RAB	Revue	Centre de documentation	En réserve L003	Disponible

Integration von Form- und Spektralmerkmalen durch künstliche neuronale Netze bei der Satellitenbildklassifizierung / Karl Segl (1996)

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