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Anomaly detection and classification for hyperspectral imagery / C.I. Chang in IEEE Transactions on geoscience and remote sensing, vol 40 n° 6 (June 2002)
[article]
Titre : Anomaly detection and classification for hyperspectral imagery Type de document : Article/Communication Auteurs : C.I. Chang, Auteur ; S.S. Chiang, Auteur Année de publication : 2002 Article en page(s) : pp 1314 - 1325 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse discriminante
[Termes IGN] capteur multibande
[Termes IGN] classification
[Termes IGN] détection d'erreur
[Termes IGN] image hyperspectrale
[Termes IGN] matrice de covarianceRésumé : (Auteur) Anomaly detection becomes increasingly important in hyperspectral image analysis, since hyperspectral imagers can now uncover many material substances which were previously unresolved by multispectral sensors. Two types of anomaly detection are of interest and considered in this paper. One was previously developed by Reed and Yu to detect targets whose signatures are distinct from their surroundings. Another was designed to detect targets with low probabilities in an unknown image scene. Interestingly, they both operate the same form as does a matched filter. Moreover, they can be implemented in realtime processing, provided that the sample covariance matrix is replaced by the sample correlation matrix. One disadvantage of an anomaly detector is the lack of ability to discriminate the detected targets from another. In order to resolve this problem, the concept of target discrimination measures is introduced to cluster different types of anomalies into separate target classes. By using these class means as target information, the detected anomalies can be further classified. With inclusion of target discrimination in anomaly detection, anomaly classification can be implemented in a threestage process, first by anomaly detection to find potential targets, followed by target discrimination to cluster the detected anomalies into separate target classes, and concluded by a classifier to achieve target classification. Experiments show that anomaly classification performs very differently from anomaly detection. Numéro de notice : A2002-189 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2002.800280 En ligne : https://doi.org/10.1109/TGRS.2002.800280 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=22104
in IEEE Transactions on geoscience and remote sensing > vol 40 n° 6 (June 2002) . - pp 1314 - 1325[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-02061 RAB Revue Centre de documentation En réserve L003 Disponible 065-02062 RAB Revue Centre de documentation En réserve L003 Disponible Principal component analysis for hyperspectral image classification / C. Rodarmel in Surveying and land information systems, vol 62 n° 2 (01/06/2002)
[article]
Titre : Principal component analysis for hyperspectral image classification Type de document : Article/Communication Auteurs : C. Rodarmel, Auteur ; J. Shan, Auteur Année de publication : 2002 Article en page(s) : pp 115 - 122 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse en composantes principales
[Termes IGN] classification
[Termes IGN] image hyperspectrale
[Termes IGN] utilisation du solRésumé : (Auteur) The availability of hyperspectral images expands the capability of using image classification to study detailed characteristics of objects, but at a cost of having to deal with huge data sets. This work studies the use of the principal component analysis as a preprocessing technique for the classification of hyperspectral images. Two hyperspectral data sets, HYDICE and AVIRIS, were used for the study. A brief presentation of the principal component analysis approach is followed by an examination of the information contents of the principal component image bands, which revealed that only the first few bands contain significant information. The use of the first few principal component images can yield about 70 percent correct classification rate. This study suggests the benefit and efficiency of using the principal component analysis technique as a preprocessing step for the classification of' hyperspectral images. Numéro de notice : A2002-192 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : sans Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=22107
in Surveying and land information systems > vol 62 n° 2 (01/06/2002) . - pp 115 - 122[article]Object detection using transformed signatures in multitemporal hyperspectral imagery / R. Mayer in IEEE Transactions on geoscience and remote sensing, vol 40 n° 4 (April 2002)
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Titre : Object detection using transformed signatures in multitemporal hyperspectral imagery Type de document : Article/Communication Auteurs : R. Mayer, Auteur ; R. Priest, Auteur Année de publication : 2002 Article en page(s) : pp 831 - 840 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] extraction de traits caractéristiques
[Termes IGN] image hyperspectrale
[Termes IGN] image multitemporelle
[Termes IGN] recouvrement d'images
[Termes IGN] signature spectrale
[Termes IGN] superposition d'imagesRésumé : (Auteur) Changes in atmosphere, ground conditions, and sensor response between multitemporal airborne imaging sessions have limited the use of fixed target hyperspectral libraries in helping to identify targets in heterogeneous (cluttered) backgrounds. This hyperspectral target signature instability has resulted in using anomaly detection algorithms to detect targets in real time applications. The anomaly detection algorithms, however, have not detected targets at sufficiently low false alarm rates. This study examines mathematical transforms of target spectral signatures. Specifically this study uses statistical information regarding background clutter taken from one long-wave infrared (LWIR) hyperspectral (8-12jum) airborne imagery flown on one day, to find the target spectral signature flown on another day (with significantly dissimilar weather conditions). The transforms use overlapping regions in the two data sets but without subpixel level registration. This work analyzes image cubes collected during the November 1998 Hyperspectral Day/Night Radiometry Assessment (HYDRA) data collect. The transformed signatures used in matched filter searches successfully find targets (even targets nearly covered) with low false alarm rates ( Numéro de notice : A2002-178 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2002.1006361 En ligne : https://doi.org/10.1109/TGRS.2002.1006361 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=22093
in IEEE Transactions on geoscience and remote sensing > vol 40 n° 4 (April 2002) . - pp 831 - 840[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-02041 RAB Revue Centre de documentation En réserve L003 Disponible 065-02042 RAB Revue Centre de documentation En réserve L003 Disponible Fuzzy modelling of African ecoregions and ecotones using AVHRR NDVI temporal imagery / M. Ji in Geocarto international, vol 17 n° 1 (March - May 2002)
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Titre : Fuzzy modelling of African ecoregions and ecotones using AVHRR NDVI temporal imagery Type de document : Article/Communication Auteurs : M. Ji, Auteur Année de publication : 2002 Article en page(s) : pp 21 - 30 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] Afrique (géographie politique)
[Termes IGN] écosystème
[Termes IGN] flore locale
[Termes IGN] image multibande
[Termes IGN] image multitemporelle
[Termes IGN] image NOAA-AVHRR
[Termes IGN] logique floue
[Termes IGN] modélisation
[Termes IGN] Normalized Difference Vegetation Index
[Termes IGN] télédétection spatialeRésumé : (Auteur) Conventional methods of deriving global or continental vegetation maps from the National Oceanic and Atmospheric Administration's (NOAA) Advanced Very High Resolution Radiometer (AVHRR) time series data are based on two-value Boolean logic, which cannot properly model the so-called ecotone, the transition zone between adjacent ecosystems. New methods and data models that have been developed on the basis of fuzzy logic to address the "mixedpixel " issue in multi-spectral imagery can also be used with multi-temporal imagery to handle the mixture of vegetation types within an ecotone. This study introduces the concept of semantic space and its transformation from spectral feature space, which utilizes a fuzzy logic approach to characterize the continuum of vegetation communities in the African continent from AVHRR multi-temporal (12 months for three years from 1986 to 1988) NDVI data. The fuzzy procedure was based an the Fuzzy c-Means (FCM) algorithm with significant modifications to improve processing speed for handling large volumes of data. A second-order mapping approach was also devised to explicitly represent subdominant vegetative coverage in ecotones and other heterogeneous regions. Comparisons between a Sub-Saharan African Vegetation Map compiled by the International Union for Conservation of Nature (IUCN) in 1986 and the maps derived from this study demonstrated that fuzzy modeling and classification might provide a better and more realistic representation of the vegetative characteristics of the region. Numéro de notice : A2002-121 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106040208542222 En ligne : https://doi.org/10.1080/10106040208542222 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=22036
in Geocarto international > vol 17 n° 1 (March - May 2002) . - pp 21 - 30[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 059-02011 RAB Revue Centre de documentation En réserve L003 Disponible Application of remote sensing to enhance the control of wildlife associated mycobacterium bovis infection / J.S. Mckenzie in Photogrammetric Engineering & Remote Sensing, PERS, vol 68 n° 2 (February 2002)
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Titre : Application of remote sensing to enhance the control of wildlife associated mycobacterium bovis infection Type de document : Article/Communication Auteurs : J.S. Mckenzie, Auteur ; R.S. Morris, Auteur ; D.U. Pfeiffer, Auteur ; J.R. Dymond, Auteur Année de publication : 2002 Article en page(s) : pp 153 - 159 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] biotope
[Termes IGN] cartographie thématique
[Termes IGN] classification
[Termes IGN] image multibande
[Termes IGN] image SPOT
[Termes IGN] prévention des risques
[Termes IGN] risque sanitaireRésumé : (Auteur) The brushtail possum (Trichosurus vulpecula) is a wildlife vector for tuberculosis (TB) caused by Mycobacterium bovis in New Zealand. Supervised automatic classification of a SPOT3 multi spectral image was used to generate a vegetation map, which was used together with slope data to model the risk of TB-infected possums being present in habitat patches. The vegetation data were also used to identify habitat patterns which, together with other geographic variables, were incorporated into logistic regression models to identify predictors of possum TB risk of farms. The impact of the predicted possum TB risk data on the cost-effectiveness of vector control programs at both individual farm and larger regional control areas is discussed, plus issues associated with the uptake of the models by operational managers. Numéro de notice : A2002-013 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : sans En ligne : https://www.asprs.org/wp-content/uploads/pers/2002journal/february/2002_feb_153- [...] Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=21930
in Photogrammetric Engineering & Remote Sensing, PERS > vol 68 n° 2 (February 2002) . - pp 153 - 159[article]Comparison of GENIE and conventional supervised classifiers for multispectral image feature extraction / N.R. Harvey in IEEE Transactions on geoscience and remote sensing, vol 40 n° 2 (February 2002)PermalinkA derivative-aided hyperspectral image analysis system for land-cover classification / F. Tsai in IEEE Transactions on geoscience and remote sensing, vol 40 n° 2 (February 2002)PermalinkLinear spectral random mixture analysis for hyperspectral imagery / C.I. Chang in IEEE Transactions on geoscience and remote sensing, vol 40 n° 2 (February 2002)PermalinkApprofondissement des techniques de diagnostique des propriétés spectrales d'une culture / Laure Chandelier (2002)PermalinkObserving our environment from space / G. Begni (2002)PermalinkOptical imagery from airborne & spaceborne: comparison of resolution, coverage for given ground pixel size / Gordon Petrie in Geoinformatics, vol 5 n° 1 (01/01/2002)PermalinkScale and texture in digital image classification / J.S. Ferro in Photogrammetric Engineering & Remote Sensing, PERS, vol 68 n° 1 (January 2002)PermalinkA synergic automatic clustering technique (syneract) for multispectral image analysis / K.Y. Huang in Photogrammetric Engineering & Remote Sensing, PERS, vol 68 n° 1 (January 2002)PermalinkRevealing the anatomy of cities through spectral mixture analysis of multispectral satellite imagery: a case study of the greater Cairo region, Egypt / T. Rashed in Geocarto international, vol 16 n° 4 (December 2001 - February 2002)PermalinkA robust texture analysis and classification approach for urban land-use and land-cover feature discrimination / S.W. Myint in Geocarto international, vol 16 n° 4 (December 2001 - February 2002)Permalink