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Triangular factorization-based simplex algorithms for hyperspectral unmixing / W. Xia in IEEE Transactions on geoscience and remote sensing, vol 50 n° 11 Tome 1 (November 2012)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 50 n° 11 Tome 1 (November 2012) . - pp 4420 - 4440 Titre : Triangular factorization-based simplex algorithms for hyperspectral unmixing Type de document : Article/Communication Auteurs : W. Xia, Auteur ; H. Pu, Auteur ; et al., Auteur Année de publication : 2012 Article en page(s) : pp 4420 - 4440 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] algorithme d'apprentissage [Termes IGN] algorithme du simplexe [Termes IGN] analyse des mélanges spectraux [Termes IGN] factorisation [Termes IGN] image hyperspectrale [Termes IGN] programmation linéaire Résumé : (Auteur) In the linear unmixing of hyperspectral images, the observation pixels form a simplex whose vertices correspond to the endmembers, hence finding the endmembers is equivalent to extracting these vertices. A common technique for determining vertices is to analyze the simplex volume, but it usually has a high computational complexity, resulting from the exhaustive searching of volume in the large hyperspectral data. This problem limits the practicability and real-time application. In this paper, we utilize triangular factorization (TF) to calculate the volume, deducing a method named simplex volume analysis based on TF (SVATF). It requires just one comparison through the data to succeed in finding the global optimal solution for all the endmembers, thus improving the searching efficiency. Dimensionality reduction transformation is not necessary, which is another advantage of this method. Moreover, since TF is a broad conception including different methods, SVATF is a framework including various implementations. Based on TF, we also propose a fast learning algorithm named abundance quantification based on TF to estimate the abundances, which further saves the computation by utilizing the intermediate values involved in SVATF. The abundance estimation method can rectify possible errors in the given endmembers by utilizing two important constraints (abundance nonnegative constraint and abundance sum-to-one constraint) of the linear mixture model, so it is useful for the imagery without pure pixels. Experimental results on synthetic and real hyperspectral data demonstrate that the proposed methods can obtain accurate results with much lower computational complexity, with respect to other state-of-the-art methods. Numéro de notice : A2012-587 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2012.2195185 Date de publication en ligne : 22/05/2012 En ligne : https://doi.org/10.1109/TGRS.2012.2195185 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32033 [article]

Total variation spatial regularization for sparse hyperspectral unmixing / M. Iordache in IEEE Transactions on geoscience and remote sensing, vol 50 n° 11 Tome 1 (November 2012)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 50 n° 11 Tome 1 (November 2012) . - pp 4484 - 4502 Titre : Total variation spatial regularization for sparse hyperspectral unmixing Type de document : Article/Communication Auteurs : M. Iordache, Auteur ; J. Biuoucas-Dias, Auteur ; Antonio J. Plaza, Auteur Année de publication : 2012 Article en page(s) : pp 4484 - 4502 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] analyse des mélanges spectraux [Termes IGN] analyse infrapixellaire [Termes IGN] image hyperspectrale [Termes IGN] information géographique [Termes IGN] prise en compte du contexte [Termes IGN] régression Résumé : (Auteur) Spectral unmixing aims at estimating the fractional abundances of pure spectral signatures (also called endmembers) in each mixed pixel collected by a remote sensing hyperspectral imaging instrument. In recent work, the linear spectral unmixing problem has been approached in semisupervised fashion as a sparse regression one, under the assumption that the observed image signatures can be expressed as linear combinations of pure spectra, known a priori and available in a library. It happens, however, that sparse unmixing focuses on analyzing the hyperspectral data without incorporating spatial information. In this paper, we include the total variation (TV) regularization to the classical sparse regression formulation, thus exploiting the spatial-contextual information present in the hyperspectral images and developing a new algorithm called sparse unmixing via variable splitting augmented Lagrangian and TV. Our experimental results, conducted with both simulated and real hyperspectral data sets, indicate the potential of including spatial information (through the TV term) on sparse unmixing formulations for improved characterization of mixed pixels in hyperspectral imagery. Numéro de notice : A2012-588 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2012.2191590 Date de publication en ligne : 07/05/2012 En ligne : https://doi.org/ 10.1109/TGRS.2012.2191590 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32034 [article]

A wavelet spectral analysis technique for automatic detection of geomagnetic sudden commencements / E. Ghamry in IEEE Transactions on geoscience and remote sensing, vol 50 n° 11 Tome 1 (November 2012)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 50 n° 11 Tome 1 (November 2012) . - pp 4503 - 4512 Titre : A wavelet spectral analysis technique for automatic detection of geomagnetic sudden commencements Type de document : Article/Communication Auteurs : E. Ghamry, Auteur ; A. Hafez, Auteur ; et al., Auteur Année de publication : 2012 Article en page(s) : pp 4503 - 4512 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géophysique interne [Termes IGN] analyse spectrale [Termes IGN] détection automatique [Termes IGN] tempête magnétique [Termes IGN] transformation en ondelettes Résumé : (Auteur) Maximal overlap discrete wavelet transform is used to perform spectral analysis of geomagnetic storm sudden commencements (SCs) (SSCs). This spectral analysis guided us in the development of an automatic SSC detection algorithm. The SC can be an indicator of the onset of a geomagnetic storm; in this case, it is called an SSC. The geomagnetic records used in this study were 3-s resolution data collected from the Circum-Pan Pacific Magnetometer Network. Using such high-resolution data enabled us to achieve a small detection error and short processing time. In addition to these technical merits, we introduce a new algorithm that automatically detects, for the first time, the SC from high-resolution data (sampled at the rate of 1 sample/3 s), unlike previous studies that focused on determining the SSC times automatically using 1-min data. Ninety-three geomagnetic storms were considered for testing the proposed algorithm; it was found that the average and maximum standard deviation of the errors in the detection times determined by the algorithm were 7 and 18 samples, respectively, of the corresponding manually determined arrival times. Numéro de notice : A2012-589 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2012.2192279 Date de publication en ligne : 08/05/2012 En ligne : https://doi.org/110.1109/TGRS.2012.2192279 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32035 [article]

Edge-guided multiscale segmentation of satellite multispectral imagery / J. Chen in IEEE Transactions on geoscience and remote sensing, vol 50 n° 11 Tome 1 (November 2012)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 50 n° 11 Tome 1 (November 2012) . - pp 4513 - 4520 Titre : Edge-guided multiscale segmentation of satellite multispectral imagery Type de document : Article/Communication Auteurs : J. Chen, Auteur ; J. Li, Auteur ; et al., Auteur Année de publication : 2012 Article en page(s) : pp 4513 - 4520 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] analyse d'image numérique [Termes IGN] contour [Termes IGN] détection de contours [Termes IGN] filtre de Canny [Termes IGN] image multibande [Termes IGN] littoral [Termes IGN] segmentation d'image Résumé : (Auteur) This paper presents a new approach to multiscale segmentation of satellite multispectral imagery using edge information. The Canny edge detector is applied to perform multispectral edge detection. The detected edge features are then utilized in a multiscale segmentation loop, and the merge procedure for adjacent image objects is controlled by a separability criterion that combines edge information with segmentation scale. The significance of the edge is measured by adjacent partitioned regions to perform edge assessment. The present method is based on a half-partition structure, which is composed of three steps: single edge detection, separated pixel grouping, and significant feature calculation. The spectral distance of the half-partitions separated by the edge is calculated, compared, and integrated into the edge information. The results show that the proposed approach works well on satellite multispectral images of a coastal area. Numéro de notice : A2012-590 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2012.2194502 Date de publication en ligne : 23/05/2012 En ligne : https://doi.org/10.1109/TGRS.2012.2194502 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32036 [article]

A vector sift detector for interest point detection in hyperspectral imagery / L. Dorado-Munoz in IEEE Transactions on geoscience and remote sensing, vol 50 n° 11 Tome 1 (November 2012)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 50 n° 11 Tome 1 (November 2012) . - pp 4521 - 4533 Titre : A vector sift detector for interest point detection in hyperspectral imagery Type de document : Article/Communication Auteurs : L. Dorado-Munoz, Auteur ; M. Velez-Reys, Auteur ; et al., Auteur Année de publication : 2012 Article en page(s) : pp 4521 - 4533 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] données vectorielles [Termes IGN] extraction automatique [Termes IGN] image AISA+ [Termes IGN] image EO1-Hyperion [Termes IGN] image hyperspectrale [Termes IGN] point d'intérêt [Termes IGN] SIFT (algorithme) Résumé : (Auteur) This paper presents an algorithm for the extraction of interest points in hyperspectral images. Interest points are spatial features of the image that capture information from their neighbors, are distinctive and stable under transformations such as translation and rotation, are helpful in data reduction, and reduce the computational burden of various algorithms such as image registration by replacing an exhaustive search over the entire image domain by a probe into a concise set of highly informative points. Interest points have been applied to problems in computer vision, including image matching, recognition, 3-D reconstruction, and change detection. Interest point operators for monochromatic images were proposed more than a decade ago and have extensively been studied. An interest point operator seeks out points in an image that are structurally distinct, invariant to imaging conditions, and stable under geometric transformations. An extension of Lowe's scale-invariant feature transform (SIFT) to vector images is proposed here. The approach takes the vectorial nature of the hyperspectral images into account. Furthermore, the multiscale representation of the image is generated by vector nonlinear diffusion, which leads to improved detection, because it better preserves edges in the image as opposed to Gaussian blurring, which is used in Lowe's original approach. Experiments with hyperspectral images of the same and different resolutions that were collected with the Airborne Hyperspectral Imaging System (AISA) and Hyperion sensors are presented. Evaluation of the proposed approach using repeatability criterion and image registration is carried out. Comparisons with other approaches that were described in the literature are presented. Numéro de notice : A2012-591 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2012.2191791 Date de publication en ligne : 09/05/2012 En ligne : https://doi.org/10.1109/TGRS.2012.2191791 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32037 [article]