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A Wavelet and IHS integration method to fuse high resolution SAR with moderate resolution multispectral images / G. Hong in Photogrammetric Engineering & Remote Sensing, PERS, vol 75 n° 10 (October 2009)
[article]
Titre : A Wavelet and IHS integration method to fuse high resolution SAR with moderate resolution multispectral images Type de document : Article/Communication Auteurs : G. Hong, Auteur ; Y. Zhang, Auteur ; J. Bryan Mercer, Auteur Année de publication : 2009 Article en page(s) : pp 1213 - 1223 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image mixte
[Termes IGN] fusion d'images
[Termes IGN] image à haute résolution
[Termes IGN] image à très haute résolution
[Termes IGN] image Landsat-TM
[Termes IGN] image multibande
[Termes IGN] image radar moirée
[Termes IGN] image Radarsat
[Termes IGN] précision millimétrique
[Termes IGN] résolution multiple
[Termes IGN] transformation en ondelettes
[Termes IGN] transformation intensité-teinte-saturationRésumé : (Auteur) Synthetic aperture radar (SAR) imaging can be a feasible alternative or a complement to traditional optical remote sensing techniques because it does not depend on solar illumination and weather conditions. The high spatial resolution of SAR, such as the Intermap STAR-3i airborne SAR image with 1.25 m spatial resolution, makes it applicable for high spatial resolution mapping purposes. However, difficulties sometimes exist in the interpretation of SAR images. Image fusion presents an alternative to improve the interpretability of SAR images by fusing the color information from moderate spatial resolution multispectral (MS) images. In this paper, a new fusion method based on the integration of wavelet transform and IHS (Intensity, Hue, and Saturation) transform is proposed for SAR and MS fusion to maintain the spectral content of the original MS image while retaining the spatial detail of the high-resolution SAR image. Three data sets are used to evaluate the proposed fusion method: two sets are airborne SAR images with MS images at different spatial resolutions; the other set is a Radarsat image with a Landsat TM image. The fusion results are evaluated visually and statistically. The evaluation shows that successful results are achieved in the fusion of all SAR and MS images from a variety of sensors with significant spatial and spectral variations by using the proposed image fusion method. Numéro de notice : A2009-420 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.75.10.1213 En ligne : https://doi.org/10.14358/PERS.75.10.1213 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=30051
in Photogrammetric Engineering & Remote Sensing, PERS > vol 75 n° 10 (October 2009) . - pp 1213 - 1223[article]An adaptive thresholding multiple classifiers system for remote sensing image classification / Y. Tzeng in Photogrammetric Engineering & Remote Sensing, PERS, vol 75 n° 6 (June 2009)
[article]
Titre : An adaptive thresholding multiple classifiers system for remote sensing image classification Type de document : Article/Communication Auteurs : Y. Tzeng, Auteur ; K. Fan, Auteur ; K.S. Chen, Auteur Année de publication : 2009 Article en page(s) : pp 679 - 687 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image mixte
[Termes IGN] classificateur
[Termes IGN] classification automatique
[Termes IGN] classification hybride
[Termes IGN] ensachage
[Termes IGN] image optique
[Termes IGN] image radar
[Termes IGN] seuillage d'imageRésumé : (Auteur) A multiple classifiers system which adopts an effective weighting policy to combine the output of several classifiers, generally leads to a better performance in image classification. The two most commonly used weighting policies are Bagging and Boosting algorithms. However, their performance is limited by high levels of ambiguity among classes. To overcome this difficulty, an adaptive thresholding criterion was proposed. By applying it to SAR and optical images for terrain cover classification, comparisons between the multiple classifiers systems using the Bagging and/or Boosting algorithms with and without the adaptive thresholding criterion were made. Experimental results showed that the classification substantially improved when the adaptive thresholding criterion was used, especially when the level of ambiguity of targets was high. Copyright ASPRS Numéro de notice : A2009-260 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.75.6.679 En ligne : https://doi.org/10.14358/PERS.75.6.679 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=29890
in Photogrammetric Engineering & Remote Sensing, PERS > vol 75 n° 6 (June 2009) . - pp 679 - 687[article]Fusion of support vector machines for classification of multisensor data / Björn Waske in IEEE Transactions on geoscience and remote sensing, vol 45 n° 12 Tome 1 (December 2007)
[article]
Titre : Fusion of support vector machines for classification of multisensor data Type de document : Article/Communication Auteurs : Björn Waske, Auteur ; Jon Atli Benediktsson, Auteur Année de publication : 2007 Article en page(s) : pp 3858 - 3866 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image mixte
[Termes IGN] analyse comparative
[Termes IGN] classificateur non paramétrique
[Termes IGN] classificateur paramétrique
[Termes IGN] classification par arbre de décision
[Termes IGN] classification par maximum de vraisemblance
[Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] fusion d'images
[Termes IGN] image multicapteur
[Termes IGN] image optique
[Termes IGN] image radarRésumé : (Auteur) The classification of multisensor data sets, consisting of multitemporal synthetic aperture radar data and optical imagery, is addressed. The concept is based on the decision fusion of different outputs. Each data source is treated separately and classified by a support vector machine (SVM). Instead of fusing the final classification outputs (i.e., land cover classes), the original outputs of each SVM discriminant function are used in the subsequent fusion process. This fusion is performed by another SVM, which is trained on the a priori outputs. In addition, two voting schemes are applied to create the final classification results. The results are compared with well-known parametric and nonparametric classifier methods, i.e., decision trees, the maximum-likelihood classifier, and classifier ensembles. The proposed SVM-based fusion approach outperforms all other approaches and significantly improves the results of a single SVM, which is trained on the whole multisensor data set. Copyright IEEE Numéro de notice : A2007-581 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2007.898446 En ligne : https://doi.org/10.1109/TGRS.2007.898446 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28944
in IEEE Transactions on geoscience and remote sensing > vol 45 n° 12 Tome 1 (December 2007) . - pp 3858 - 3866[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-07121A RAB Revue Centre de documentation En réserve L003 Disponible Land-cover classification in the Brazilian Amazon with the integration of Landsat ETM+ and Radarsat data / Dong Lu in International Journal of Remote Sensing IJRS, vol 28 n°23-24 (December 2007)
[article]
Titre : Land-cover classification in the Brazilian Amazon with the integration of Landsat ETM+ and Radarsat data Type de document : Article/Communication Auteurs : Dong Lu, Auteur ; M. Batistella, Auteur ; E. Moran, Auteur Année de publication : 2007 Article en page(s) : pp 5447 - 5459 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image mixte
[Termes IGN] Amazonie
[Termes IGN] analyse texturale
[Termes IGN] Brésil
[Termes IGN] classification par maximum de vraisemblance
[Termes IGN] fusion d'images
[Termes IGN] image Landsat-ETM+
[Termes IGN] image multibande
[Termes IGN] image optique
[Termes IGN] image panchromatique
[Termes IGN] image radar
[Termes IGN] image Radarsat
[Termes IGN] niveau de gris (image)
[Termes IGN] occupation du sol
[Termes IGN] transformation en ondelettes
[Termes IGN] zone tropicale humideRésumé : (Auteur) Land-cover classification with remotely sensed data in moist tropical regions is a challenge due to the complex biophysical conditions. This paper explores techniques to improve land-cover classification accuracy through a comparative analysis of different combinations of spectral signatures and textures from Landsat Enhanced Thematic Mapper Plus (ETM+) and Radarsat data. A wavelet-merging technique was used to integrate Landsat ETM+ multispectral and panchromatic data or Radarsat data. Grey-level co-occurrence matrix (GLCM) textures based on Landsat ETM+ panchromatic or Radarsat data and different sizes of moving windows were examined. A maximum-likelihood classifier was used to implement image classification for different combinations. This research indicates the important role of textures in improving land-cover classification accuracies in Amazonian environments. The incorporation of data fusion and textures increases classification accuracy by approximately 5.8-6.9% compared to Landsat ETM+ data, but data fusion of Landsat ETM+ multispectral and panchromatic data or Radarsat data cannot effectively improve land-cover classification accuracies. Copyright Taylor & Francis Numéro de notice : A2007-538 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/01431160701227596 En ligne : https://doi.org/10.1080/01431160701227596 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28901
in International Journal of Remote Sensing IJRS > vol 28 n°23-24 (December 2007) . - pp 5447 - 5459[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 080-07131 RAB Revue Centre de documentation En réserve L003 Disponible Integration of panchromatic and SAR features into multispectral spot images using the "à trous" wavelet decomposition / Y. Chibani in International Journal of Remote Sensing IJRS, vol 28 n° 10 (May 2007)
[article]
Titre : Integration of panchromatic and SAR features into multispectral spot images using the "à trous" wavelet decomposition Type de document : Article/Communication Auteurs : Y. Chibani, Auteur Année de publication : 2007 Article en page(s) : pp 2295 - 2307 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image mixte
[Termes IGN] algorithme à trous
[Termes IGN] fusion d'images
[Termes IGN] fusion de données multisource
[Termes IGN] image multibande
[Termes IGN] image panchromatique
[Termes IGN] image radar
[Termes IGN] image Radarsat
[Termes IGN] image SPOT
[Termes IGN] radar à antenne synthétique
[Termes IGN] transformation de Brovey
[Termes IGN] transformation en ondelettesRésumé : (Auteur) A method is described for integrating panchromatic (P) and synthetic aperture radar (SAR) features into multispectral (XS) images using conjointly the modified Brovey transform (MBT) and the 'à trous' wavelet decomposition (ATDW). The MBT is based on the local modulation of each multispectral image by the ratio of the new and initial intensity components to produce new multispectral images directly. The ATWD allows extraction of features from P and SAR images, which are combined through a feature selection rule to integrate into the initial intensity component. For evaluating the effect of each feature selection on new XS images, experimental results are conducted on SPOT (XS, P) and Radarsat (SAR) images using both visual inspection and many refined statistical measures. Copyright Taylor & Francis Numéro de notice : A2007-291 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/01431160600606874 En ligne : https://doi.org/10.1080/01431160600606874 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28654
in International Journal of Remote Sensing IJRS > vol 28 n° 10 (May 2007) . - pp 2295 - 2307[article]Exemplaires (1)
Code-barres Cote Support Localisation Section Disponibilité 080-07061 RAB Revue Centre de documentation En réserve L003 Exclu du prêt Comparison and integration of radar and optical data for land use / cover mapping / Nathaniel D. Herold in Geocarto international, vol 21 n° 4 (December 2006 - February 2007)PermalinkAssessment of EOS aqua AMSR-E artic sea ice concentrations using Landsat-7 and airborne microwave imagery / D.J. Cavalieri in IEEE Transactions on geoscience and remote sensing, vol 44 n° 11 Tome 1 (November 2006)PermalinkA robust technique for precise registration of radar and optical satellite images / T.D. Hong in Photogrammetric Engineering & Remote Sensing, PERS, vol 71 n° 5 (May 2005)PermalinkMéthodes d'analyse et d'interprétation d'images de télédétection multi-sources / Danielle Ducrot (2005)PermalinkOn the possibility of automatic multisensor image registration / Jordi Inglada in IEEE Transactions on geoscience and remote sensing, vol 42 n° 10 (October 2004)PermalinkSpatiotriangulation with multisensor VIR/SAR / Thierry Toutin in IEEE Transactions on geoscience and remote sensing, vol 42 n° 10 (October 2004)PermalinkDetecting and quantifying mountain permafrost creep from in situ inventory, space-borne radar interferometry and airborne digital photogrammetry / Tazio Strozzi in International Journal of Remote Sensing IJRS, vol 25 n° 15 (August 2004)PermalinkA new maximum-likelihood joint segmentation technique for multitemporal SAR and multiband optical images / P. Lombardo in IEEE Transactions on geoscience and remote sensing, vol 41 n° 11 (November 2003)PermalinkDetection of building outlines based on the fusion of SAR and optical features / Florence Tupin in ISPRS Journal of photogrammetry and remote sensing, vol 58 n° 1-2 (June - December 2003)PermalinkFusion of hyperspectral and radar data using the IHS transformation to enhance urban surface features / C.M. Chen in ISPRS Journal of photogrammetry and remote sensing, vol 58 n° 1-2 (June - December 2003)Permalink