Descripteur
Termes IGN > sciences naturelles > physique > traitement d'image > analyse d'image numérique > analyse des mélanges spectraux
analyse des mélanges spectrauxSynonyme(s)SMA démélange spectral |
Documents disponibles dans cette catégorie (139)
Ajouter le résultat dans votre panier
Visionner les documents numériques
Affiner la recherche Interroger des sources externes
Etendre la recherche sur niveau(x) vers le bas
Sampling piecewise convex unmixing and endmember extraction / Alina Zare in IEEE Transactions on geoscience and remote sensing, vol 51 n° 3 Tome 2 (March 2013)
[article]
Titre : Sampling piecewise convex unmixing and endmember extraction Type de document : Article/Communication Auteurs : Alina Zare, Auteur ; Paul Garder, Auteur ; George Casella, Auteur Année de publication : 2013 Article en page(s) : pp 1655 - 1665 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] algorithme du simplexe
[Termes IGN] analyse des mélanges spectraux
[Termes IGN] échantillonnage d'image
[Termes IGN] ensemble convexe
[Termes IGN] image hyperspectrale
[Termes IGN] méthode de Monte-Carlo
[Termes IGN] signature spectraleRésumé : (Auteur) A Metropolis-within-Gibbs sampler for piecewise convex hyperspectral unmixing and endmember extraction is presented. The standard linear mixing model used for hyperspectral unmixing assumes that hyperspectral data reside in a single convex region. However, hyperspectral data are often nonconvex. Furthermore, in standard endmember extraction and unmixing methods, endmembers are generally represented as a single point in the high-dimensional space. However, the spectral signature for a material varies as a function of the inherent variability of the material and environmental conditions. Therefore, it is more appropriate to represent each endmember as a full distribution and use this information during spectral unmixing. The proposed method searches for several sets of endmember distributions. By using several sets of endmember distributions, a piecewise convex mixing model is applied, and given this model, the proposed method performs spectral unmixing and endmember estimation given this nonlinear representation of the data. Each set represents a random simplex. The vertices of the random simplex are modeled by the endmember distributions. The hyperspectral data are partitioned into sets associated with each of the extracted sets of endmember distributions using a Dirichlet process prior. The Dirichlet process prior also estimates the number of sets. Thus, the Metropolis-within-Gibbs sampler partitions the data into convex regions, estimates the required number of convex regions, and estimates endmember distributions and abundance values for all convex regions. Results are presented on real hyperspectral and simulated data that indicate the ability of the method to effectively estimate endmember distributions and the number of sets of endmember distributions. Numéro de notice : A2013-134 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2012.2207905 En ligne : https://doi.org/10.1109/TGRS.2012.2207905 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32272
in IEEE Transactions on geoscience and remote sensing > vol 51 n° 3 Tome 2 (March 2013) . - pp 1655 - 1665[article]Réservation
Réserver ce documentExemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 065-2013031B RAB Revue Centre de documentation En réserve L003 Disponible Crop yield estimation based on unsupervised linear unmixing of multidate hyperspectral imagery / B. Luo in IEEE Transactions on geoscience and remote sensing, vol 51 n° 1 Tome 1 (January 2013)
[article]
Titre : Crop yield estimation based on unsupervised linear unmixing of multidate hyperspectral imagery Type de document : Article/Communication Auteurs : B. Luo, Auteur ; C. Yang, Auteur ; Jocelyn Chanussot, Auteur ; et al., Auteur Année de publication : 2013 Article en page(s) : pp 162 - 173 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] analyse des mélanges spectraux
[Termes IGN] classification non dirigée
[Termes IGN] image hyperspectrale
[Termes IGN] image multitemporelle
[Termes IGN] rendement agricole
[Termes IGN] sorgho (céréale)Résumé : (Auteur) Hyperspectral imagery, which contains hundreds of spectral bands, has the potential to better describe the biological and chemical attributes on the plants than multispectral imagery and has been evaluated in this paper for the purpose of crop yield estimation. The spectrum of each pixel in a hyperspectral image is considered as a linear combinations of the spectra of the vegetation and the bare soil. Recently developed linear unmixing approaches are evaluated in this paper, which automatically extracts the spectra of the vegetation and bare soil from the images. The vegetation abundances are then computed based on the extracted spectra. In order to reduce the influences of this uncertainty and obtain a robust estimation results, the vegetation abundances extracted on two different dates on the same fields are then combined. The experiments are carried on the multidate hyperspectral images taken from two grain sorghum fields. The results show that the correlation coefficients between the vegetation abundances obtained by unsupervised linear unmixing approaches are as good as the results obtained by supervised methods, where the spectra of the vegetation and bare soil are measured in the laboratory. In addition, the combination of vegetation abundances extracted on different dates can improve the correlations (from 0.6 to 0.7). Numéro de notice : A2013-012 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2012.2198826 Date de publication en ligne : 19/06/2012 En ligne : https://doi.org/10.1109/TGRS.2012.2198826 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32150
in IEEE Transactions on geoscience and remote sensing > vol 51 n° 1 Tome 1 (January 2013) . - pp 162 - 173[article]Réservation
Réserver ce documentExemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 065-2013011A RAB Revue Centre de documentation En réserve L003 Disponible 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)
[article]
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] régressionRésumé : (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
in IEEE Transactions on geoscience and remote sensing > vol 50 n° 11 Tome 1 (November 2012) . - pp 4484 - 4502[article]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)
[article]
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 linéaireRésumé : (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
in IEEE Transactions on geoscience and remote sensing > vol 50 n° 11 Tome 1 (November 2012) . - pp 4420 - 4440[article]Multiple endmember unmixing of CHRIS/Proba imagery for mapping impervious surfaces in urban and suburban environments / Luca Demarchi in IEEE Transactions on geoscience and remote sensing, vol 50 n° 9 (October 2012)
[article]
Titre : Multiple endmember unmixing of CHRIS/Proba imagery for mapping impervious surfaces in urban and suburban environments Type de document : Article/Communication Auteurs : Luca Demarchi, Auteur ; Frank Canters, Auteur ; Jonathan Cheung-Wai Chan, Auteur ; T. Van De Voorde, Auteur Année de publication : 2012 Article en page(s) : pp 3409 - 3424 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse de mélange spectral d’extrémités multiples
[Termes IGN] Flandre (Belgique)
[Termes IGN] image PROBA-CHRIS
[Termes IGN] occupation du sol
[Termes IGN] précision infrapixellaire
[Termes IGN] surface imperméable
[Termes IGN] zone urbaineRésumé : (Auteur) In this paper, the potential of Compact High-Resolution Imaging Spectrometer (CHRIS)/Project for On-Board Autonomy data for impervious surface mapping is tested in a mixed urban/suburban/rural environment including part of the city of Leuven (Belgium) using multiple endmember unmixing. Various unmixing scenarios are compared, using different threshold values for the RMSE criterion applied to select the proper model for unmixing each pixel. Validation based on 25-cm aerial photography shows that the use of threshold values that favor the application of models with a small number of endmembers performs better compared to scenarios that make use of models with more endmembers. Detailed analysis of model selection for pixels with different land-cover composition indicates that the error in fraction estimation is partly related to spectral confusion between impervious surface types and bare soil, leading to the selection of inappropriate models for the unmixing. In spite of the spectral similarity of soil and impervious surface endmembers, average fractional error for impervious surfaces, vegetation, and bare soil is around 15%, which demonstrates the potential of CHRIS data for mapping the major physical components of the urban/suburban environment at the subpixel scale. Numéro de notice : A2012-449 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2011.2181853 Date de publication en ligne : 15/03/2012 En ligne : https://doi.org/10.1109/TGRS.2011.2181853 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31895
in IEEE Transactions on geoscience and remote sensing > vol 50 n° 9 (October 2012) . - pp 3409 - 3424[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 065-2012091 RAB Revue Centre de documentation En réserve L003 Exclu du prêt Mapping impervious surfaces from superresolution enhanced CHRIS/Proba imagery using multiple endmember unmixing / Luca Demarchi in ISPRS Journal of photogrammetry and remote sensing, vol 72 (August 2012)PermalinkA proposed framework to unmix scattering mechanisms of polarimetric radar images using very high resolution optical images / Sébastien Giordano in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol I-7 (2012)PermalinkThe potential of spectral mixture analysis to improve the estimation accuracy of tropical forest biomass / T.M. Basuki in Geocarto international, vol 27 n° 4 (July 2012)PermalinkGeometric unmixing of large hyperspectral images: A barycentric coordinate approach / Paul Honeine in IEEE Transactions on geoscience and remote sensing, vol 50 n° 6 (June 2012)PermalinkDevelopment of a network-based method for unmixing of hyperspectral data / V. Karathanassi in IEEE Transactions on geoscience and remote sensing, vol 50 n° 3 (March 2012)PermalinkHyperspectral unmixing based on mixtures of Dirichlet components / J. Nascimento in IEEE Transactions on geoscience and remote sensing, vol 50 n° 3 (March 2012)PermalinkCoupled nonnegative matrix factorization unmixing for hyperspectral and multispectral data fusion / N. Yokoya in IEEE Transactions on geoscience and remote sensing, vol 50 n° 2 (February 2012)PermalinkThe unmixing of atmospheric trace gases from hyperspectral satellite data / P. Addabbo in IEEE Transactions on geoscience and remote sensing, vol 50 n° 1 (January 2012)PermalinkIntercomparison and validation of techniques for spectral unmixing of hyperspectral images : a planetary case study / X. Ceamanos in IEEE Transactions on geoscience and remote sensing, vol 49 n° 11 Tome 1 (November 2011)Permalinkvol 49 n° 11 Tome 1 - November 2011 - Part1 of 2 parts (Bulletin de IEEE Transactions on geoscience and remote sensing) / M. WeissPermalinkPixel unmixing in hyperspectral data by means of neural networks / Giorgio Licciardi in IEEE Transactions on geoscience and remote sensing, vol 49 n° 11 Tome 1 (November 2011)PermalinkSVM-based unmixing-to-classification conversion for hyperspectral abundance quantification / F. Mianji in IEEE Transactions on geoscience and remote sensing, vol 49 n° 11 Tome 1 (November 2011)PermalinkA pre-screened and normalized multiple endmember spectral mixture analysis [MESMA] for mapping impervious surface area in Lake Kasumigaura Basin, Japan / F. Yang in ISPRS Journal of photogrammetry and remote sensing, vol 65 n° 5 (September - October 2010)PermalinkApplication of spectral decomposition algorithm for mapping water quality in a turbid lake (Lake Kasumigaura, Japan) from Landsat TM data / Y. Oyama in ISPRS Journal of photogrammetry and remote sensing, vol 64 n° 1 (January - February 2009)PermalinkIntegration of Hyperion satellite data and a household social survey to caracterize the causes and consequences of reforestation patterns in the Northern Ecuadorian Amazon / S.J. Walsh in Photogrammetric Engineering & Remote Sensing, PERS, vol 74 n° 6 (June 2008)PermalinkN-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)PermalinkSeasonal sensitivity analysis of impervious surface estimation with satellite imagery / C. Wu in Photogrammetric Engineering & Remote Sensing, PERS, vol 73 n° 12 (December 2007)PermalinkDerniers développements en télédétection hyperspectrale / V. Carrere in Photo interprétation, vol 43 n° 3 (Septembre 2007)PermalinkEstimation of vegetation parameter for modelling soil erosion using linear spectral mixture analysis of Landsat ETM data / A.M. DE Asis in ISPRS Journal of photogrammetry and remote sensing, vol 62 n° 4 (September 2007)PermalinkIntegrating fine scale information in super-resolution land-cover mapping / A. Boucher in Photogrammetric Engineering & Remote Sensing, PERS, vol 73 n° 8 (August 2007)PermalinkEstimating spatial patterns of rainfall interception from remotely sensed vegetation indices and spectral mixture analysis / S.M. de Jong in International journal of geographical information science IJGIS, vol 21 n° 5 (may 2007)PermalinkUrban surface biophysical descriptors and land surface temperature variations / D. Weng in Photogrammetric Engineering & Remote Sensing, PERS, vol 72 n° 11 (November 2006)PermalinkComparative analysis of urban reflectance and surface temperature / C. Small in Remote sensing of environment, vol 104 n° 2 (30 September 2006)PermalinkSubpixel analysis of Landsat ETM/sup +/ using self-organizing map (SOM) neural networks for urban land cover characterization / S. Lee in IEEE Transactions on geoscience and remote sensing, vol 44 n° 6 (June 2006)PermalinkIncorporating remote sensing information in modelling house values: a regression tree approach / D. Yu in Photogrammetric Engineering & Remote Sensing, PERS, vol 72 n° 2 (February 2006)PermalinkApplication of multiple endmember spectral mixture analysis (MESMA) to AVIRIS imagery for coastal salt marsh mapping: a case study in China Camp, CA, USA / L. Li in International Journal of Remote Sensing IJRS, vol 26 n° 23 (December 2005)PermalinkMapping impervious surface type and sub-pixel abundance using Hyperion hyperspectral imagery / J. Falcone in Geocarto international, vol 20 n° 4 (December 2005 - February 2006)PermalinkSub-pixel estimation of urban land cover components with linear mixture model analysis and Landsat Thematic Mapper imagery / S. Lee in International Journal of Remote Sensing IJRS, vol 26 n° 22 (November 2005)PermalinkImages, modèles et biomasse immergée : cartographie des herbiers de zostères en Camargue à partir d'images SPOT-5 / C. Puech in Revue internationale de géomatique, vol 15 n° 2 (juin – août 2005)PermalinkA land cover distribution composite image from coarse spatial resolution images using an unmixing method / T.M. Uenishi in International Journal of Remote Sensing IJRS, vol 26 n° 5 (March 2005)PermalinkA global analysis urban reflectance / C. Small in International Journal of Remote Sensing IJRS, vol 26 n° 4 (February 2005)PermalinkNormalized spectral mixture analysis for monitoring urban composition using ETM+ imagery / C. Wu in Remote sensing of environment, vol 93 n° 4 (15/12/2004)PermalinkA comparison of error metrics and constraints for multiple endmember spectral analysis and spectral angle mapper / P.E. Dennison in Remote sensing of environment, vol 93 n° 3 (15/11/2004)PermalinkThe 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)PermalinkSpectral mixture analysis of the urban landscape in Indianapolis with Landsat ETM+ imagery / Dong Lu in Photogrammetric Engineering & Remote Sensing, PERS, vol 70 n° 9 (September 2004)PermalinkUrban land-cover change analysis in central Puget Sound / M. Alberti in Photogrammetric Engineering & Remote Sensing, PERS, vol 70 n° 9 (September 2004)PermalinkChange detection techniques / Dong Lu in International Journal of Remote Sensing IJRS, vol 25 n° 12 (June 2004)PermalinkReducing signature variability in unmixing coastal marsh Thematic Mapper scenes using spectral indices / A.S. Rogers in International Journal of Remote Sensing IJRS, vol 25 n° 12 (June 2004)PermalinkEstimation of subpixel target size for remotely sensed imagery / C.I. Chang in IEEE Transactions on geoscience and remote sensing, vol 42 n° 6 (June 2004)PermalinkUsing Lidar and effective LAI data to evaluate Ikonos and Landsat 7 ETM+ vegetation cover estimates in a ponderosa pine forest / X. Chen in Remote sensing of environment, vol 91 n° 1 (15/05/2004)PermalinkLinear mixture analysis-based compression for hyperspectral image analysis / Q. Du in IEEE Transactions on geoscience and remote sensing, vol 42 n° 4 (April 2004)PermalinkEstimation of land surface temperature-vegetation abundance relationship for urban heat island studies / Q. Wenger in Remote sensing of environment, vol 89 n° 4 (29/02/2004)PermalinkSnow-cover mapping in forest by constrained linear spectral unimixing of MODIS data / D. Vikhamar in Remote sensing of environment, vol 88 n° 3 (15/12/2003)PermalinkHigh spatial resolution spectral mixture analysis of urban reflectance / C. Small in Remote sensing of environment, vol 88 n° 1 (30/11/2003)PermalinkMapping forest degradation in the Eastern Amazon SPOT 4 through spectral mixture models / Cristiano B. Souza in Remote sensing of environment, vol 87 n° 4 (15/11/2003)Permalink