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Complementarity of discriminative classifiers and spectral unmixing techniques for the interpretation of hyperspectral images / Jun Li in IEEE Transactions on geoscience and remote sensing, vol 53 n° 5 (mai 2015)

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 53 n° 5 (mai 2015) . - pp 2899 - 2912 Titre : Complementarity of discriminative classifiers and spectral unmixing techniques for the interpretation of hyperspectral images Type de document : Article/Communication Auteurs : Jun Li, Auteur ; Immaculada Dopido, Auteur ; P. Gamba, Auteur ; et al., Auteur Année de publication : 2015 Article en page(s) : pp 2899 - 2912 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes descripteurs IGN] analyse discriminante [Termes descripteurs IGN] analyse linéaire des mélanges spectraux [Termes descripteurs IGN] apprentissage semi-dirigé [Termes descripteurs IGN] classification dirigée [Termes descripteurs IGN] image hyperspectrale Résumé : (Auteur) Classification and spectral unmixing are two important techniques for hyperspectral data exploitation. Traditionally, these techniques have been exploited independently. In this paper, we propose a new technique that exploits their complementarity. Specifically, we develop a new framework for semisupervised hyperspectral image classification that naturally integrates the information provided by discriminative classification and spectral unmixing. The idea is to assign more confidence to the information provided by discriminative classification for those pixels that can be easily catalogued due to their spectral purity. For those pixels that are more highly mixed in nature, we assign more confidence to the information provided by spectral unmixing. In this case, we use a traditional spectral unmixing chain to produce the abundance fractions of the pure signatures (endmembers) that model the mixture information at a subpixel level. The decision on which source of information is prioritized in the process is taken adaptively, when new unlabeled samples are selected and included in our semisupervised framework. In this regard, the proposed approach can adaptively integrate these two sources of information without the need to establish any weight parameters, thus exploiting the complementarity of classification and unmixing and selecting the most appropriate source of information in each case. In order to test our concept, which has similar computational complexity as traditional semisupervised classification strategies, we have used two different hyperspectral data sets with different characteristics and spatial resolution. In our experiments, we consider two different discriminative classifiers: multinomial logistic regression and probabilistic support vector machine. The obtained results indicate that the proposed approach, which jointly exploits the features provided by classification and spectral unmixing in adaptive fashion, offers an effective solution to improve- classification performance in hyperspectral scenes containing mixed pixels. Numéro de notice : A2015-521 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=77532 [article]

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Geographic information system (GIS)-aided per-segment scene analysis of multi-temporal spaceborne synthetic aperture radar (SAR) series with application to urban areas / G. Trianni in International Journal of Remote Sensing IJRS, vol 31 n° 22 (November 2010)

Public [article]  inInternational Journal of Remote Sensing IJRS > vol 31 n° 22 (November 2010) . - pp 6005 - 6014 Titre : Geographic information system (GIS)-aided per-segment scene analysis of multi-temporal spaceborne synthetic aperture radar (SAR) series with application to urban areas Type de document : Article/Communication Auteurs : G. Trianni, Auteur ; F. Dell'acqua, Auteur ; P. Gamba, Auteur Année de publication : 2010 Article en page(s) : pp 6005 - 6014 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes descripteurs IGN] analyse diachronique [Termes descripteurs IGN] détection de changement [Termes descripteurs IGN] image radar moirée [Termes descripteurs IGN] image satellite [Termes descripteurs IGN] logiciel SIG [Termes descripteurs IGN] occupation du sol [Termes descripteurs IGN] segmentation d'image [Termes descripteurs IGN] urbanisation [Termes descripteurs IGN] utilisation du sol [Termes descripteurs IGN] zone rurale [Termes descripteurs IGN] zone urbaine Résumé : (Auteur) It is well known that multi-temporal series of synthetic aperture radar (SAR) data are able to provide interesting clues about temporal evolution of some land covers. In this work, a per-segment approach based on the use of ancillary geographic information system data is proposed. The results of a test case show the effectiveness of the technique and its usefulness for quickly detecting changes from rural to urban land uses and discriminating to some extent different urban dynamics. Numéro de notice : A2010-536 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=30728 [article]

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Rapid mapping of high resolution SAR scenes / F. Dell'acqua in ISPRS Journal of photogrammetry and remote sensing, vol 64 n° 5 (September - October 2009)

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 64 n° 5 (September - October 2009) . - pp 482 - 489 Titre : Rapid mapping of high resolution SAR scenes Type de document : Article/Communication Auteurs : F. Dell'acqua, Auteur ; P. Gamba, Auteur ; G. Lisini, Auteur Année de publication : 2009 Article en page(s) : pp 482 - 489 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes descripteurs IGN] accident géographique artificiel [Termes descripteurs IGN] détection automatique [Termes descripteurs IGN] détection du bâti [Termes descripteurs IGN] extraction du réseau routier [Termes descripteurs IGN] extraction semi-automatique [Termes descripteurs IGN] image radar moirée [Termes descripteurs IGN] interféromètrie par radar à antenne synthétique [Termes descripteurs IGN] reconnaissance de formes [Termes descripteurs IGN] réseau routier [Termes descripteurs IGN] traitement automatique de données Résumé : (Auteur) This paper describes a semi-automatic procedure for cartographic mapping using high resolution SAR and interferometric SAR data. Various two-dimensional features are extracted and combined in order to achieve a basic yet effective recognition of the elements in the scene. Many relevant elements of the landscape are automatically extracted without requiring any deep interaction with the operator. Being based on geometric models assuming regularity of shapes and patterns, the procedure is well suited for detecting man-made features, such as the road network (outside and inside human settlements) and built-up areas. It can be used, however, to extract natural features, focusing on different geometric models. Moreover, extracted elements of the scene can be grouped into higher level ones, such as crossroads, bridges and overpasses, through data fusion at the feature level, because the procedure is characterized by a multi-scale, object-based approach. Copyright ISPRS Numéro de notice : A2009-401 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=30032 [article]

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Improving building footprints in InSAR data comparison with a Lidar DSM / P. Gamba in Photogrammetric Engineering & Remote Sensing, PERS, vol 72 n° 1 (January 2006)

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 72 n° 1 (January 2006) . - pp 63 - 70 Titre : Improving building footprints in InSAR data comparison with a Lidar DSM Type de document : Article/Communication Auteurs : P. Gamba, Auteur ; F. Dell'acqua, Auteur ; G. Lisini, Auteur ; F. Cisotta, Auteur Année de publication : 2006 Article en page(s) : pp 63 - 70 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes descripteurs IGN] correction géométrique [Termes descripteurs IGN] détection du bâti [Termes descripteurs IGN] données lidar [Termes descripteurs IGN] étalement d'histogramme [Termes descripteurs IGN] image 3D [Termes descripteurs IGN] image radar moirée [Termes descripteurs IGN] milieu urbain [Termes descripteurs IGN] modèle numérique de surface Résumé : (Auteur) The first aim of this paper is to show how the joint use of Digital Surface Models (Dsms) coming from different sources may improve the understanding of an urban environment. More specifically, we consider laser and radar three-dimensional data over the same urban area and show that they can be profitably combined to improve building extraction. We exploit the better vertical and horizontal accuracy of the laser DSM, assumed to be available only for a small area, to ease the deformation of Interferometric Synthetic Aperture Radar (INSAR) DSM with built structures. To achieve this, we propose a method based on subsequent steps of geometrical correction, and mainly on a simple "stretching step" that uses laser data as a reference to adjust INSAR-derived building footprints. We show quantitative results obtained from two different urban areas, using different laser and radar data sets, to assess advantages and drawbacks of the proposed method. Numéro de notice : A2006-002 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=27730 [article]

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Multitemporal/multiband SAR classification of urban areas using spatial analysis: statistical versus neural kernel-based approach / T. Macri Pellizzei in IEEE Transactions on geoscience and remote sensing, vol 41 n° 10 (October 2003)

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 41 n° 10 (October 2003) . - pp 2338 - 2353 Titre : Multitemporal/multiband SAR classification of urban areas using spatial analysis: statistical versus neural kernel-based approach Type de document : Article/Communication Auteurs : T. Macri Pellizzei, Auteur ; P. Gamba, Auteur ; P. Lombardo, Auteur ; F. Dell'acqua, Auteur Année de publication : 2003 Article en page(s) : pp 2338 - 2353 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes descripteurs IGN] analyse comparative [Termes descripteurs IGN] classification dirigée [Termes descripteurs IGN] classification floue [Termes descripteurs IGN] classification par réseau neuronal [Termes descripteurs IGN] image radar moirée [Termes descripteurs IGN] image SIR-C [Termes descripteurs IGN] milieu urbain [Termes descripteurs IGN] réalité de terrain [Termes descripteurs IGN] segmentation d'image [Termes descripteurs IGN] test de performance Résumé : (Auteur) In this paper, we derive two techniques for the classification of Multifrequency/multitemporal polarimetric SAR images, based respectively on a statistical and on a neural approach. Both techniques are especially designed to exploit the spatial structure of the observed scene, thus allowing more stable classification results. Such techniques are useful when looking at medium - to - scale features, like the boundaries between urban and non-urban areas. They are applied to a set of SIR-C images of a urban area, to test their effectiveness in the identification of the different classes that compose the observed scene. A lower and an upper bound to the classification performance are introduced to characterise their limits. They correspond respectively to pixel-by-pixel classification and to the joint classification of the pixels belonging to the different classes identified in the ground truth. The results achieved with the two approaches are quantitatively analysed by comparing them to the ground truth. Moreover, a hybrid approach is presented, where the homogeneous regions identified through statistical segmentation are classified using a neuro-fuzzy technique. Finally, a quantitative analysis of the results achieved with all the proposed techniques is carried out, showing that their classification performance is much higher than the lower bound and reasonably close to the upper bound. This is a consequence of their effectiveness in the exploitation of the spatial information. Numéro de notice : A2003-356 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=26436 [article]

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Improvements to urban area characterization using multitemporal and multiangle SAR images / F. Dell'acqua in IEEE Transactions on geoscience and remote sensing, vol 41 n° 9 (September 2003)

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vol 58 n° 1-2 - June - December 2003 - Algorithms and techniques for multi-source data fusion in urban areas (Bulletin de ISPRS Journal of photogrammetry and remote sensing) / P. Gamba  

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Detection of urban structures in SAR images by robust fuzzy clustering algorithms: the example of street tracking / F. Dell'acqua in IEEE Transactions on geoscience and remote sensing, vol 39 n° 10 (October 2001)

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