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Classification of very high spatial resolution imagery based on the fusion of edge and multispectral information / X. Huang in Photogrammetric Engineering & Remote Sensing, PERS, vol 74 n° 12 (December 2008)
[article]
Titre : Classification of very high spatial resolution imagery based on the fusion of edge and multispectral information Type de document : Article/Communication Auteurs : X. Huang, Auteur ; L. Zhang, Auteur ; P. Li, Auteur Année de publication : 2008 Article en page(s) : pp 1585 - 1596 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse en composantes indépendantes
[Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] détection de contours
[Termes IGN] extraction de traits caractéristiques
[Termes IGN] image à résolution subdecamétrique
[Termes IGN] image à très haute résolution
[Termes IGN] image multibande
[Termes IGN] image Quickbird
[Termes IGN] matrice de co-occurrence
[Termes IGN] Normalized Difference Vegetation Index
[Termes IGN] prise en compte du contexteRésumé : (Auteur) A new algorithm based on the fusion of edge and multispectral information is proposed for the pixel-wise classification of very high-resolution (VHR) remotely sensed imagery. It integrates the multispectral, spatial and structural information existing in the image. The edge feature is first extracted using an improved multispectral edge detection method, which takes into account the original multispectral bands, the linear NDVI, and the independent spectral components extracted by independent component analysis (ICA). Direction-lines are then defined using the edge and multispectral information. Two effective spatial measures are calculated based on the direction-lines in order to describe the contextual information and strengthen the multispectral feature space. Then, the support vector machine (SVM) is employed to classify the hybrid structural-multispectral feature set. In experiments, the proposed spatial measures were compared with the pixel shape index (PSI) and the gray level co-occurrence matrix (GLCM). The experimental results show that the proposed algorithm performs well in terms of classification accuracies and visual interpretation. Copyright ASPRS Numéro de notice : A2008-479 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.74.12.1585 En ligne : https://doi.org/10.14358/PERS.74.12.1585 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=29548
in Photogrammetric Engineering & Remote Sensing, PERS > vol 74 n° 12 (December 2008) . - pp 1585 - 1596[article]Applications of ICA for the enhancement and classification of polarimetric SAR images / H. Wang in International Journal of Remote Sensing IJRS, vol 29 n° 6 (March 2008)
[article]
Titre : Applications of ICA for the enhancement and classification of polarimetric SAR images Type de document : Article/Communication Auteurs : H. Wang, Auteur ; Y. Pi, Auteur ; et al., Auteur Année de publication : 2008 Article en page(s) : pp 1649 - 1663 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] analyse en composantes indépendantes
[Termes IGN] couleur à l'écran
[Termes IGN] données polarimétriques
[Termes IGN] filtre de déchatoiement
[Termes IGN] image en couleur composée
[Termes IGN] image radar moirée
[Termes IGN] image RVBRésumé : (Auteur) Independent components analysis (ICA) based methods for polarimetric synthetic aperture radar (SAR) image speckle reduction and ground object classification are studied. Several independent components can be extracted from polarimetric SAR images using ICA directly. The component with lowest speckle index is regarded as the scene after speckle reduction. The disadvantage of this method is that only one image is kept and most polarization information will be lost. In this paper, we use ICA-sparse-coding shrinkage (ICA-SPS) based speckle reduction method, which is implemented on each individual image and can keep polarization information. It is carried out on the combined channels obtained by Pauli-decomposition rather than original polarization channels in order to keep relative phase information among polarization channels and get better performance. After ICA-SPS, the effect of speckle suppression on SAR image classification can be compared favourably with other methods by combining the channels into a false colour image. At last, a new ICA-based classification method is presented. In this method, four independent components are separated by ICA from five polarization and combined channels. One of these independent components which includes little ground object information is regarded as speckle noise and therefore be discarded. The remaining three components can be treated as subordination coefficients of three kinds of targets. A classified image can be obtained based on the components. And by composing these three channels in RGB colour pattern, a false colour image can be constructed. Numéro de notice : A2008-085 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/01431160701395211 En ligne : https://doi.org/10.1080/01431160701395211 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=29080
in International Journal of Remote Sensing IJRS > vol 29 n° 6 (March 2008) . - pp 1649 - 1663[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 080-08041 RAB Revue Centre de documentation En réserve L003 Exclu du prêt N-FindR method versus independent component analysis for lithological identification in hyperspectral imagery / C. Gomez in International Journal of Remote Sensing IJRS, vol 28 n°23-24 (December 2007)
[article]
Titre : N-FindR method versus independent component analysis for lithological identification in hyperspectral imagery Type de document : Article/Communication Auteurs : C. Gomez, Auteur ; H. Le Borgne, Auteur ; P. Allemand, Auteur ; C. Delacourt, Auteur ; P. Ledru, Auteur Année de publication : 2007 Article en page(s) : pp 5315 - 5338 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse comparative
[Termes IGN] analyse des mélanges spectraux
[Termes IGN] analyse en composantes indépendantes
[Termes IGN] classification automatique
[Termes IGN] image EO1-Hyperion
[Termes IGN] image hyperspectrale
[Termes IGN] lithologie
[Termes IGN] méthode robuste
[Termes IGN] Namibie
[Termes IGN] photo-interprétation assistée par ordinateurRésumé : (Auteur) The current study addresses the problem of the identification of each natural material present in each pixel of a hyperspectral image. Two end member extraction methods from hyperspectral imagery were studied: the N-FindR method and the independent component analysis (ICA). The N-FindR is an automatic technique that selects extreme points (end members) of an n-dimensional scatter plot. It assumes the existence of pure pixels in the distribution, which is infrequent in practice. ICA is a blind source separation technique studied in the signal processing community, which allows each spectrum of natural elements (end member spectra) to be extracted from the observation of some linear combinations of these. It considers a more realistic situation than N-FindR, assuming a spectra mixture for all the pixels. To increase the robustness of ICA, continuum-removed reflectance spectra were used and an iterative algorithm was introduced that takes into account a major part of the available information. The end member abundances were estimated by the fully constrained least squares spectral mixture analysis (FLCS). The end member identification and quantification were carried out on two surficial formations of a semi arid region located in the Rehoboth region, in Namibia, from hyperspectral Hyperion data. It appears that the two end member extraction methods have a similar potential. Whichever end member extraction method is used, the analysis of the rock abundance maps produces a lot of geological information: the distribution of natural elements is in line with the field observations and allows the description of the formation processes of surficial units. Copyright Taylor & Francis Numéro de notice : A2007-536 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/01431160701227679 En ligne : https://doi.org/10.1080/01431160701227679 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28899
in International Journal of Remote Sensing IJRS > vol 28 n°23-24 (December 2007) . - pp 5315 - 5338[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 080-07131 RAB Revue Centre de documentation En réserve L003 Disponible A pixel shape index coupled with spectral information for classification of high spatial resolution remotely sensed imagery / L. Zhang in IEEE Transactions on geoscience and remote sensing, vol 44 n° 10 Tome 2 (October 2006)
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Titre : A pixel shape index coupled with spectral information for classification of high spatial resolution remotely sensed imagery Type de document : Article/Communication Auteurs : L. Zhang, Auteur ; X. Huang, Auteur Année de publication : 2006 Article en page(s) : pp 2950 - 2961 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse en composantes indépendantes
[Termes IGN] classification dirigée
[Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] fusion de données
[Termes IGN] image à haute résolution
[Termes IGN] image multibande
[Termes IGN] matrice de co-occurrence
[Termes IGN] niveau de gris (image)
[Termes IGN] pixel
[Termes IGN] précision de la classification
[Termes IGN] précision géométrique (imagerie)
[Termes IGN] reconnaissance de formes
[Termes IGN] transformation en ondelettesRésumé : (Auteur) Shape and spectra are both important features of high spatial resolution remotely sensed (HSRRS) imagery, and they are concrete manifestation of textures on such imagery. This paper presents a spatial feature index, pixel shape index (PSI), to describe the shape feature in a local area surrounding a pixel. PSI is a pixel-based feature which measures the gray similarity distance in every direction. As merely the shape feature is inadequate for classifying HSRRS imagery, a transformed spectral feature extracted by independent component analysis is added to the input vectors of our classifier, and this replaces the original multispectral bands. Meanwhile, a fast fusion algorithm that integrates both shape and spectral features using the support vector machine has been developed to interpret the complex input vectors. The results by PSI are compared with some spatial features extracted using wavelet transform, gray level co-occurrence matrix, and the length–width extraction algorithm to test its effectiveness. The experiments demonstrate that PSI is capable of describing shape features effectively and result in more accurate classifications than other methods. While it is found that spectral and shape features can complement each other and their integration can improve classification accuracy, the transformed spectral components are also found to be more suitable for classification. Copyright IEEE Numéro de notice : A2006-504 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2006.876704 En ligne : https://doi.org/10.1109/TGRS.2006.876704 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28228
in IEEE Transactions on geoscience and remote sensing > vol 44 n° 10 Tome 2 (October 2006) . - pp 2950 - 2961[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-06101B RAB Revue Centre de documentation En réserve L003 Disponible The contribution of the sources separation method in the decomposition of mixed pixels / Mohamed Saber Naceur in IEEE Transactions on geoscience and remote sensing, vol 42 n° 11 (November 2004)
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Titre : The contribution of the sources separation method in the decomposition of mixed pixels Type de document : Article/Communication Auteurs : Mohamed Saber Naceur, Auteur ; M.A. Loghmari, Auteur ; Mohamed-Rached Boussema, Auteur Année de publication : 2004 Article en page(s) : pp 2642 - 2653 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] accentuation d'image
[Termes IGN] analyse des mélanges spectraux
[Termes IGN] analyse en composantes indépendantes
[Termes IGN] bande spectrale
[Termes IGN] classification pixellaire
[Termes IGN] décomposition d'image
[Termes IGN] fusion de données multisource
[Termes IGN] occupation du sol
[Termes IGN] signature spectrale
[Termes IGN] Tunisie
[Termes IGN] valeur radiométriqueRésumé : (Auteur) In this paper, we propose to prove the importance of the application of blind sources separation methods on remote sensing data. Indeed, satellite images are represented by radiometric values where each one is considered as a mixture of different sources. The primary goal of our research is to hand back the different sources covering the scanned zone. The main constraint to restore these sources is to take our observation images as a mixture of physically independent components. In our work, the independence between the different sources is obtained through two statistical methods. The first method is based on the reduction of the spatial source correlations, and the second one is based on the joint maximization of the fourth-order cumulants. On the opposite of the original multispectral images that are represented according to correlated axes, the source images extracted from the proposed algorithms are represented according to mutually independent axes that allow each source to represent specifically a certain type of land cover. This increases the reliability of the analysis and the interpretation of the scanned zone. The source images obtained from the application of the sources separation method give a more effective representation of the information contained on the observation images. The performance of these source images is investigated through an application for the decomposition of mixed pixels. The originality of our application comes from the determination of the mixing matrix modeling the spectral endmembers based on source filters. These filters model the sensibility of each source channel according to the different spectral bands, which give an interesting information about the spectral theme represented by the corresponding source image. This application shows that the proportions of the different land cover types existing into the pixel are better estimated through the source images than through the original multispectral images. This method could offer an interesting solution to mixed-pixel classification. Numéro de notice : A2004-463 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2004.834764 En ligne : https://doi.org/10.1109/TGRS.2004.834764 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=26983
in IEEE Transactions on geoscience and remote sensing > vol 42 n° 11 (November 2004) . - pp 2642 - 2653[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-04111 RAB Revue Centre de documentation Revues en salle Disponible Unsupervised 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)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)Permalink