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Total-variation-regularized low-rank matrix factorization for hyperspectral image restoration / Wei He in IEEE Transactions on geoscience and remote sensing, vol 54 n° 1 (January 2016)
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Titre : Total-variation-regularized low-rank matrix factorization for hyperspectral image restoration Type de document : Article/Communication Auteurs : Wei He, Auteur ; Hongyan Zhang, Auteur ; Liangpei Zhang, Auteur ; Huanfeng Shen, Auteur Année de publication : 2016 Article en page(s) : pp 178 - 188 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] factorisation
[Termes IGN] factorisation de matrice non-négative
[Termes IGN] image hyperspectrale
[Termes IGN] matrice
[Termes IGN] restauration d'imageRésumé : (Auteur) In this paper, we present a spatial spectral hyperspectral image (HSI) mixed-noise removal method named total variation (TV)-regularized low-rank matrix factorization (LRTV). In general, HSIs are not only assumed to lie in a low-rank subspace from the spectral perspective but also assumed to be piecewise smooth in the spatial dimension. The proposed method integrates the nuclear norm, TV regularization, and L1-norm together in a unified framework. The nuclear norm is used to exploit the spectral low-rank property, and the TV regularization is adopted to explore the spatial piecewise smooth structure of the HSI. At the same time, the sparse noise, which includes stripes, impulse noise, and dead pixels, is detected by the L1-norm regularization. To tradeoff the nuclear norm and TV regularization and to further remove the Gaussian noise of the HSI, we also restrict the rank of the clean image to be no larger than the number of endmembers. A number of experiments were conducted in both simulated and real data conditions to illustrate the performance of the proposed LRTV method for HSI restoration. Numéro de notice : A2016-071 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2015.2452812 En ligne : https://doi.org/10.1109/TGRS.2015.2452812 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=79834
in IEEE Transactions on geoscience and remote sensing > vol 54 n° 1 (January 2016) . - pp 178 - 188[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 065-2016011 SL Revue Centre de documentation Revues en salle Disponible An approach to fine coregistration between very high resolution multispectral images based on registration noise distribution / Youkyung Han in IEEE Transactions on geoscience and remote sensing, vol 53 n° 12 (December 2015)
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Titre : An approach to fine coregistration between very high resolution multispectral images based on registration noise distribution Type de document : Article/Communication Auteurs : Youkyung Han, Auteur ; Francesca Bovolo, Auteur ; Lorenzo Bruzzone, Auteur Année de publication : 2015 Article en page(s) : pp 6650 - 6662 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] appariement de points
[Termes IGN] bruit (théorie du signal)
[Termes IGN] filtrage du bruit
[Termes IGN] image à très haute résolution
[Termes IGN] image multibande
[Termes IGN] point d'appui
[Termes IGN] raccord d'images
[Termes IGN] superposition d'imagesRésumé : (auteur) Even after applying effective coregistration methods, multitemporal images are likely to show a residual misalignment, which is referred to as registration noise (RN). This is because coregistration methods from the literature cannot fully handle the local dissimilarities induced by differences in the acquisition conditions (e.g., the stability of the acquisition platform, the off-nadir angle of the sensor, the structure of the considered scene, etc.). This paper addresses the problem of reducing such a residual misalignment by proposing a fine automatic coregistration approach for very high resolution (VHR) multispectral images. The proposed method takes advantage of the properties of the residual misalignment itself. To this end, RN is first extracted in the change vector analysis (CVA) polar domain according to the behaviors of the specific multitemporal images considered. Then, a local analysis of RN pixels (i.e., those showing residual misalignment) is conducted for automatically extracting control points (CPs) and matching them according to their estimated displacement. Matched CPs are used for generating a deformation map by interpolation. Finally, one VHR image is warped to the coordinates of the other through a deformation map. Experiments carried out on simulated and real multitemporal VHR images confirm the effectiveness of the proposed approach. Numéro de notice : A2015-846 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2015.2445632 Date de publication en ligne : 07/07/2015 En ligne : https://doi.org/10.1109/TGRS.2015.2445632 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=79196
in IEEE Transactions on geoscience and remote sensing > vol 53 n° 12 (December 2015) . - pp 6650 - 6662[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 065-2015121 SL Revue Centre de documentation Revues en salle Disponible Automated annual cropland mapping using knowledge-based temporal features / François Waldner in ISPRS Journal of photogrammetry and remote sensing, vol 110 (December 2015)
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Titre : Automated annual cropland mapping using knowledge-based temporal features Type de document : Article/Communication Auteurs : François Waldner, Auteur ; Guadalupe Sepulcre Canto, Auteur ; Pierre Defourny, Auteur Année de publication : 2015 Article en page(s) : pp 1 – 13 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] Argentine
[Termes IGN] Belgique
[Termes IGN] carte agricole
[Termes IGN] carte d'occupation du sol
[Termes IGN] Chine
[Termes IGN] classification dirigée
[Termes IGN] cultures
[Termes IGN] série temporelle
[Termes IGN] surveillance agricole
[Termes IGN] UkraineRésumé : (auteur) Global, timely, accurate and cost-effective cropland mapping is a prerequisite for reliable crop condition monitoring. This article presented a simple and comprehensive methodology capable to meet the requirements of operational cropland mapping by proposing (1) five knowledge-based temporal features that remain stable over time, (2) a cleaning method that discards misleading pixels from a baseline land cover map and (3) a classifier that delivers high accuracy cropland maps (>>80%). This was demonstrated over four contrasted agrosystems in Argentina, Belgium, China and Ukraine. It was found that the quality and accuracy of the baseline impact more the certainty of the classification rather than the classification output itself. In addition, it was shown that interpolation of the knowledge-based features increases the stability of the classifier allowing for its re-use from year to year without recalibration. Hence, the method shows potential for application at larger scale as well as for delivering cropland map in near real time. Numéro de notice : A2015-889 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2015.09.013 En ligne : http://dx.doi.org/10.1016/j.isprsjprs.2015.09.013 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=79438
in ISPRS Journal of photogrammetry and remote sensing > vol 110 (December 2015) . - pp 1 – 13[article]Automated detection of Martian gullies from HiRISE imagery / Wei Li in Photogrammetric Engineering & Remote Sensing, PERS, vol 81 n° 12 (December 2015)
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Titre : Automated detection of Martian gullies from HiRISE imagery Type de document : Article/Communication Auteurs : Wei Li, Auteur ; Kaichang Di, Auteur ; Zongyu Yue, Auteur ; et al., Auteur Année de publication : 2015 Article en page(s) : pp 913 - 920 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] détection de cible
[Termes IGN] image HiRISE
[Termes IGN] Mars (planète)
[Termes IGN] morphologieRésumé : (auteur) Gully is a type of young geological feature on the Martian surface, and the study of gullies can significantly contribute to understanding of the geologic history of Martian surface. As a large amount of high-resolution orbital images have been acquired, manual identification and extraction of all gullies is tedious and prohibitively time consuming. Therefore, it is desirable to develop automated methods for detection of Martian gullies to support scientific studies of the gullies. This paper presents an automated gully detection method based on mathematical morphology techniques. The method integrates a series of morphological operators, including area opening and closing, Bottom-Hat transformation, and path opening. Experimental results using HiRISE images at six sites demonstrate promising performance with detection percentage from 76 percent to 94 percent Numéro de notice : A2015-991 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.81.12.913 En ligne : https://doi.org/10.14358/PERS.81.12.913 Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=80272
in Photogrammetric Engineering & Remote Sensing, PERS > vol 81 n° 12 (December 2015) . - pp 913 - 920[article]Classification of hyperspectral images by exploiting spectral–spatial information of superpixel via multiple kernels / Leyuan Fang in IEEE Transactions on geoscience and remote sensing, vol 53 n° 12 (December 2015)
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Titre : Classification of hyperspectral images by exploiting spectral–spatial information of superpixel via multiple kernels Type de document : Article/Communication Auteurs : Leyuan Fang, Auteur ; Shutao Li, Auteur ; Wuhui Duan, Auteur ; et al., Auteur Année de publication : 2015 Article en page(s) : pp 6663 - 6674 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] classification spectrale
[Termes IGN] données localisées
[Termes IGN] image hyperspectrale
[Termes IGN] pixelRésumé : (auteur) For the classification of hyperspectral images (HSIs), this paper presents a novel framework to effectively utilize the spectral-spatial information of superpixels via multiple kernels, which is termed as superpixel-based classification via multiple kernels (SC-MK). In the HSI, each superpixel can be regarded as a shape-adaptive region, which consists of a number of spatial neighboring pixels with very similar spectral characteristics. First, the proposed SC-MK method adopts an oversegmentation algorithm to cluster the HSI into many superpixels. Then, three kernels are separately employed for the utilization of the spectral information, as well as spatial information, within and among superpixels. Finally, the three kernels are combined together and incorporated into a support vector machine classifier. Experimental results on three widely used real HSIs indicate that the proposed SC-MK approach outperforms several well-known classification methods. Numéro de notice : A2015-847 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2015.2445767 Date de publication en ligne : 01/07/2015 En ligne : https://doi.org/10.1109/TGRS.2015.2445767 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=79197
in IEEE Transactions on geoscience and remote sensing > vol 53 n° 12 (December 2015) . - pp 6663 - 6674[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 065-2015121 SL Revue Centre de documentation Revues en salle Disponible Examining the potential of Sentinel-2 MSI spectral resolution in quantifying above ground biomass across different fertilizer treatments / Mbulisi Sibanda in ISPRS Journal of photogrammetry and remote sensing, vol 110 (December 2015)
PermalinkReal-time atmospheric correction of AVIRIS-NG imagery / Brian D. Bue in IEEE Transactions on geoscience and remote sensing, vol 53 n° 12 (December 2015)
PermalinkRoad vectorisation from high-resolution imagery based on dynamic clustering using particle swarm optimisation / Fateme Ameri in Photogrammetric record, vol 30 n° 152 (December 2015 - February 2016)
PermalinkSemi-supervised SVM for individual tree crown species classification / Michele Dalponte in ISPRS Journal of photogrammetry and remote sensing, vol 110 (December 2015)
PermalinkUrban classification by the fusion of thermal infrared hyperspectral and visible data / Jiayi Li in Photogrammetric Engineering & Remote Sensing, PERS, vol 81 n° 12 (December 2015)
PermalinkAutomatic orthorectification of high-resolution optical satellite images using vector roads / Aleš Marsetič in IEEE Transactions on geoscience and remote sensing, vol 53 n° 11 (November 2015)
PermalinkA moving weighted harmonic analysis method for reconstructing high-quality SPOT VEGETATION NDVI time-series data / Gang Yang in IEEE Transactions on geoscience and remote sensing, vol 53 n° 11 (November 2015)
PermalinkA robust mosaicking procedure for high spatial resolution remote sensing images / Xinghua Li in ISPRS Journal of photogrammetry and remote sensing, vol 109 (November 2015)
PermalinkDistinctive order based self-similarity descriptor for multi-sensor remote sensing image matching / Amin Sedaghat in ISPRS Journal of photogrammetry and remote sensing, vol 108 (October 2015)
PermalinkEfficient superpixel-level multitask joint sparse representation for hyperspectral image classification / Jiayi Li in IEEE Transactions on geoscience and remote sensing, vol 53 n° 10 (October 2015)
PermalinkExtraction des zones cohérentes par l’analyse spatio-temporelle d’images de télédétection / Thomas Guyet in Revue internationale de géomatique, vol 25 n° 4 (octobre - décembre 2015)
PermalinkOn diverse noises in hyperspectral unmixing / Chunzhi Li in IEEE Transactions on geoscience and remote sensing, vol 53 n° 10 (October 2015)
PermalinkTwo dimensional linear discriminant analyses for hyperspectral data / Maryam Imani in Photogrammetric Engineering & Remote Sensing, PERS, vol 81 n° 10 (October 2015)
PermalinkUnsupervised segmentation of high-resolution remote sensing images based on classical models of the visual receptive field / Miaozhong Xu in Geocarto international, vol 30 n° 9 - 10 (October - November 2015)
PermalinkAccurate affine invariant image matching using oriented least square / Amin Sedaghat in Photogrammetric Engineering & Remote Sensing, PERS, vol 81 n° 9 (September 2015)
PermalinkMeasuring the effectiveness of various features for thematic information extraction from very high resolution remote sensing imagery / X. Chen in IEEE Transactions on geoscience and remote sensing, vol 53 n° 9 (September 2015)
PermalinkMinimum volume simplex analysis: A fast algorithm for linear hyperspectral unmixing / Jun Li in IEEE Transactions on geoscience and remote sensing, vol 53 n° 9 (September 2015)
PermalinkOn spectral unmixing resolution using extended support vector machines / Xiaofeng Li in IEEE Transactions on geoscience and remote sensing, vol 53 n° 9 (September 2015)
PermalinkRegion-kernel-based support vector machines for hyperspectral image classification / Jiangtao Peng in IEEE Transactions on geoscience and remote sensing, vol 53 n° 9 (September 2015)
PermalinkRemoval of thin clouds using cirrus and QA bands of Landsat-8 / Yang Shen in Photogrammetric Engineering & Remote Sensing, PERS, vol 81 n° 9 (September 2015)
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