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Quality criteria benchmark for hyperspectral imagery / E. Christophe in IEEE Transactions on geoscience and remote sensing, vol 43 n° 9 (September 2005)
[article]
Titre : Quality criteria benchmark for hyperspectral imagery Type de document : Article/Communication Auteurs : E. Christophe, Auteur ; D. Leger, Auteur ; Corinne Mailhes, Auteur Année de publication : 2005 Article en page(s) : pp 2103 - 2114 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Acquisition d'image(s) et de donnée(s)
[Termes IGN] classification
[Termes IGN] compression de données
[Termes IGN] dégradation d'image
[Termes IGN] image AVIRIS
[Termes IGN] image hyperspectrale
[Termes IGN] qualité des données
[Termes IGN] test de performanceRésumé : (Auteur) Hyperspectral data appear to be of a growing interest over the past few years. However, applications for hyperspectral data are still in their infancy as handling the significant size of the data presents a challenge for the user community. Efficient compression techniques are required, and lossy compression, specifically, will have a role to play, provided its impact on remote sensing applications remains insignificant. To assess the data quality, suitable distortion measures relevant to end-user applications are required. Quality criteria are also of a major interest for the conception and development of new sensors to define their requirements and specifications. This paper proposes a method to evaluate quality criteria in the context of hyperspectral images. The purpose is to provide quality criteria relevant to the impact of degradations on several classification applications. Different quality criteria are considered. Some are traditionnally used in image and video coding and are adapted here to hyperspectral images. Others are specific to hyperspectral data. We also propose the adaptation of two advanced criteria in the presence of different simulated degradations on AVIRIS hyperspectral images. Finally, live criteria are selected to give an accurate representation of the nature and the level of the degradation affecting hyperspectral data. Numéro de notice : A2005-388 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2005.853931 En ligne : https://doi.org/10.1109/TGRS.2005.853931 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=27524
in IEEE Transactions on geoscience and remote sensing > vol 43 n° 9 (September 2005) . - pp 2103 - 2114[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-05091 RAB Revue Centre de documentation En réserve L003 Disponible De-shadowing of satellite/airborne imagery / R. Richter in International Journal of Remote Sensing IJRS, vol 26 n° 15 (August 2005)
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Titre : De-shadowing of satellite/airborne imagery Type de document : Article/Communication Auteurs : R. Richter, Auteur ; A. Muller, Auteur Année de publication : 2005 Article en page(s) : pp 3137 - 3148 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] bande visible
[Termes IGN] correction des ombres
[Termes IGN] filtre numérique
[Termes IGN] image aérienne
[Termes IGN] image hyperspectrale
[Termes IGN] image multibande
[Termes IGN] image spatiale
[Termes IGN] matrice de covariance
[Termes IGN] rayonnement proche infrarouge
[Termes IGN] seuillage d'imageRésumé : (Auteur) A de-shadowing technique is presented for multispectral and hyperspectral imagery over land acquired by satellite/airborne sensors. The method requires a channel in the visible and at least one spectral band in the near-infrared (0.8-1um) region, but performs much better if bands in the short-wave infrared region (around 1.6 and 2.2 um) are available as well. The algorithm consists of these major components: (i) calculation of the covariance matrix and zero-reflectance matched filter vector, (ii) derivation of the unsealed and scaled shadow function, (iii) histogram thresholding of the unscaled shadow function to define the core shadow areas, (iv) region growing to include the surroundings of the core shadow areas for a smooth shadowlclear transition, and (v) de-shadowing of the pixels in the final shadow mask. The critical parameters of the method are discussed. Example images from different climates and landscapes are presented to demonstrate the successful performance of the shadow removal process over land surfaces. Numéro de notice : A2005-323 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/01431160500114664 En ligne : https://doi.org/10.1080/01431160500114664 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=27459
in International Journal of Remote Sensing IJRS > vol 26 n° 15 (August 2005) . - pp 3137 - 3148[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 080-05151 RAB Revue Centre de documentation En réserve L003 Exclu du prêt
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Titre : Clever imaging with Smartscan Type de document : Article/Communication Auteurs : V. Tchernykh, Auteur ; S. Dyblenko, Auteur ; et al., Auteur Année de publication : 2005 Article en page(s) : pp 41 - 45 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Acquisition d'image(s) et de donnée(s)
[Termes IGN] capteur en peigne
[Termes IGN] capteur imageur
[Termes IGN] distorsion d'image
[Termes IGN] image hyperspectrale
[Termes IGN] numériseur à balayage
[Termes IGN] orientation du capteur
[Termes IGN] satellite d'observation de la Terre
[Termes IGN] temps réelRésumé : (Auteur) The cameras commonly used for Earth observation from satellites require high attitude stability during the image acquisition. For some types of cameras (high-resolution 'pushbroom' scanners in particular), instantaneous attitude changes of even less than one arcsecond result in significant image distortion and blurring. Especially problematic are the effects of high-frequency attitude variations originating from micro-shocks and vibrations produced by the momentum and reaction wheels, mechanically activated coolers, and steering and deployment mechanisms on board. The resulting high attitude-stability requirements for Earth-observation satellites are one of the main reasons for their complexity and high cost. The novel SmartScan imaging concept, based on an opto-electronic system with no moving parts, offers the promise of high-quality imaging with only moderate satellite attitude stability. SmartScan uses real-time recording of the actual image motion in the focal plane of the camera during frame acquisition to correct the distortions in the image. Exceptional real-time performances with subpixel-accuracy image-motion measurement are provided by an innovative high-speed onboard opto-electronic correlation processor. SmartScan will therefore allow pushbroom scanners to be used for hyperspectral imaging from satellites and other space platforms not primarily intended for imaging missions, such as micro- and nano-satellites with simplified attitude control, low-orbiting communications satellites, and manned space stations. Numéro de notice : A2005-404 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : sans En ligne : http://www.esa.int/esapub/bulletin/bulletin123/bul123f_tchernykh.pdf Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=27540
in ESA bulletin > n° 123 (August 2005) . - pp 41 - 45[article]A statistical self-organizing learning system for remote sensing classification / H.M. Chi in IEEE Transactions on geoscience and remote sensing, vol 43 n° 8 (August 2005)
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Titre : A statistical self-organizing learning system for remote sensing classification Type de document : Article/Communication Auteurs : H.M. Chi, Auteur ; O.K. Ersoy, Auteur Année de publication : 2005 Article en page(s) : pp 1890 - 1900 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] apprentissage automatique
[Termes IGN] carte de Kohonen
[Termes IGN] classification par réseau neuronal
[Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] image hyperspectrale
[Termes IGN] méthode des moindres carrés
[Termes IGN] noeud
[Termes IGN] système expert
[Termes IGN] transformation non linéaireRésumé : (Auteur) A new learning system called a statistical self-organizing learning system (SSOLS), combining functional-link neural networks, statistical hypothesis testing, and self-organization of a number of enhancement nodes, is introduced for remote sensing applications. Its structure consists of two stages, a mapping stage and a learning stage. The input training vectors are initially mapped to the enhancement vectors in the mapping stage by multiplying with a random matrix, followed by pointwise nonlinear transformations. Starting with only one enhancement node, the enhancement layer incrementally adds an extra node in each iteration. The optimum dimension of the enhancement layer is determined by using an efficient leave-one-out cross-validation method. In this way, the number of enhancement nodes is also learned automatically. A t-test algorithm can also be applied to the mapping stage to mitigate the effect of overfitting and to further reduce the number of enhancement nodes required, resulting in a more compact network. In the learning stage, both the input vectors and the enhancement vectors are fed into a least squares learning module to obtain the estimated output vectors. This is made possible by choosing the output layer linear. In addition, several SSOLSs can be trained independently in parallel to form a consensual SSOLS, whose final output is a linear combination of the outputs of each SSOLS module. The SSOLS is simple, fast to compute, and suitable for remote sensing applications, especially with hyperspectral image data of high dimensionality. Numéro de notice : A2005-393 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2005.851188 En ligne : https://doi.org/10.1109/TGRS.2005.851188 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=27529
in IEEE Transactions on geoscience and remote sensing > vol 43 n° 8 (August 2005) . - pp 1890 - 1900[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-05081 RAB Revue Centre de documentation En réserve L003 Disponible A whole image approach using field measurements for transforming EO1 Hyperion hyperspectral data into canopy reflectance spectra / E.W. Ramsey in International Journal of Remote Sensing IJRS, vol 26 n° 8 (April 2005)
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Titre : A whole image approach using field measurements for transforming EO1 Hyperion hyperspectral data into canopy reflectance spectra Type de document : Article/Communication Auteurs : E.W. Ramsey, Auteur ; G. Nelson, Auteur Année de publication : 2005 Article en page(s) : pp 1589 - 1610 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] correction atmosphérique
[Termes IGN] diffusion du rayonnement
[Termes IGN] données de terrain
[Termes IGN] éclairement énergétique
[Termes IGN] image EO1-Hyperion
[Termes IGN] image hyperspectrale
[Termes IGN] réflectance végétale
[Termes IGN] transfert radiatifRésumé : (Auteur) To maximize the spectral distinctiveness (information) of the canopy reflectance, an atmospheric correction strategy was implemented to provide accurate estimates of the intrinsic reflectance from the Earth Observing 1 (EO1) satellite Hyperion sensor signal. In rendering the canopy reflectance, an estimate of optical depth derived from a measurement of downwelling irradiance was used to drive a radiative transfer simulation of atmospheric scattering and attenuation. During the atmospheric model simulation, the input whole-terrain background reflectance estimate was changed to minimize the differences between the model predicted and the observed canopy reflectance spectra at 34 sites. Lacking appropriate spectrally invariant scene targets, inclusion of the field and predicted comparison maximized the model accuracy and, thereby, the detail and precision in the canopy reflectance necessary to detect low percentage occurrences of invasive plants. After accounting for artifacts surrounding prominent absorption features from about 400nm to 1000nm, the atmospheric adjustment strategy correctly explained 99% of the observed canopy reflectance spectra variance. Separately, model simulation explained an average of 88% + 9% of the observed variance in the visible and 98% + 1 % in the near-infrared wavelengths. In the 34 model simulations, maximum différences between the observed and predicted reflectances were typically less than + 1% in the visible ; however, maximum reflectance différences higher than +1.6% ( Numéro de notice : A2005-205 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/0431160512331326729 En ligne : https://doi.org/10.1080/0431160512331326729 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=27342
in International Journal of Remote Sensing IJRS > vol 26 n° 8 (April 2005) . - pp 1589 - 1610[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 080-05081 RAB Revue Centre de documentation En réserve L003 Exclu du prêt Integration of spatial and spectral information by means of unsupervised extraction and classification for homogenous objects applied to multispectral and hyperspectral data / L.O. Jimenez in IEEE Transactions on geoscience and remote sensing, vol 43 n° 4 (April 2005)PermalinkAn automatic nonlinear correlation approach for processing of hyperspectral images / R.N. Ingram in International Journal of Remote Sensing IJRS, vol 25 n° 22 (November 2004)PermalinkThe development of superspectral approaches for the improvement of land cover classification / M. Gianinetto in IEEE Transactions on geoscience and remote sensing, vol 42 n° 11 (November 2004)PermalinkEvaluation of hyperspectral remote sensing as a means of environmental monitoring in the St Austell China clay (kaolin) region, Cornwall, UK / R.J. Ellis in Remote sensing of environment, vol 93 n° 1 (30/10/2004)PermalinkEvaluating airborne hyperspectral imagery for rangeland assessment in south Texas / James H. Everitt in Geocarto international, vol 19 n° 3 (September - November 2004)PermalinkUse of hyperspectral derivative ratios in the red-edge region to identify plant stress responses to gas leaks / K.L. Smith in Remote sensing of environment, vol 92 n° 2 (15/08/2004)PermalinkClassification of hyperspectral remote sensing images with support vector machines / F. Melgani in IEEE Transactions on geoscience and remote sensing, vol 42 n° 8 (August 2004)PermalinkIntegrating imaging spectroscopy (445-2543nm) and geographic information systems for post-disaster management: a case of hailstorm damage in Sydney / S. Bhaskaran in International Journal of Remote Sensing IJRS, vol 25 n° 13 (July 2004)PermalinkMapping coastal vegetation using an expert system and hyperspectral imagery / K.S. Schmidt in Photogrammetric Engineering & Remote Sensing, PERS, vol 70 n° 6 (June 2004)PermalinkWavelet transform applied to EO-1 hyperspectral data for forest LAI and crown closure mapping / R. Pu in Remote sensing of environment, vol 91 n° 2 (30/05/2004)PermalinkClassification of contamination in salt marsh plant using hyperspectral reflectance / M.D. Wilson in IEEE Transactions on geoscience and remote sensing, vol 42 n° 5 (May 2004)PermalinkRefinement of wavelength calibrations of hyperspectral imaging data using a spectrum-machine technique / B.C. Gao in Remote sensing of environment, vol 90 n° 4 (30/04/2004)PermalinkClassification of remotely sensed imagery stochastic gradient boosting as a refinement of classification tree analysis / R. Lawrence in Remote sensing of environment, vol 90 n° 3 (15/04/2004)PermalinkHyperspectral vegetation indices and novel algorithms for predicting green LAI of crop canopies: modelling and validation in the context of precision agriculture / D. Haboudane in Remote sensing of environment, vol 90 n° 3 (15/04/2004)PermalinkLinear mixture analysis-based compression for hyperspectral image analysis / Q. Du in IEEE Transactions on geoscience and remote sensing, vol 42 n° 4 (April 2004)PermalinkIntegrating imaging spectroscopy and neural networks to map grass quality in the Kruger National Park, South Africa / Onisimo Mutanga in Remote sensing of environment, vol 90 n° 1 (15/03/2004)PermalinkLa télédétection avec ENVI / Françoise de Blomac in SIG la lettre, n° 55 (mars 2004)PermalinkPredicting in situ pasture quality in the Kruger National Park, South Africa, using continuum-removed absorption features / Onisimo Mutanga in Remote sensing of environment, vol 89 n° 3 (15/02/2004)PermalinkMapping coal fires based on OMIS1 thermal infrared band image / Y. Wan in International Journal of Remote Sensing IJRS, vol 25 n° 3 (February 2004)PermalinkUnsupervised classification of hyperspectral data: an ICA mixture model based approach / Chintan A. Shah in International Journal of Remote Sensing IJRS, vol 25 n° 2 (January 2004)Permalink