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Multiband image fusion based on spectral unmixing / Qi Wei in IEEE Transactions on geoscience and remote sensing, vol 54 n° 12 (December 2016)
[article]
Titre : Multiband image fusion based on spectral unmixing Type de document : Article/Communication Auteurs : Qi Wei, Auteur ; José Bioucas-Dias, Auteur ; Nicolas Dobigeon, Auteur ; et al., Auteur Année de publication : 2016 Article en page(s) : pp 7236 - 7249 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse des mélanges spectraux
[Termes IGN] fusion d'images
[Termes IGN] image à basse résolution
[Termes IGN] image à haute résolution
[Termes IGN] image hyperspectrale
[Termes IGN] image multibande
[Termes IGN] matrice de covarianceRésumé : (Auteur) This paper presents a multiband image fusion algorithm based on unsupervised spectral unmixing for combining a high-spatial-low-spectral-resolution image and a low-spatial-high-spectral-resolution image. The widely used linear observation model (with additive Gaussian noise) is combined with the linear spectral mixture model to form the likelihoods of the observations. The nonnegativity and sum-to-one constraints resulting from the intrinsic physical properties of the abundances are introduced as prior information to regularize this ill-posed problem. The joint fusion and unmixing problem is then formulated as maximizing the joint posterior distribution with respect to the endmember signatures and abundance maps. This optimization problem is attacked with an alternating optimization strategy. The two resulting subproblems are convex and are solved efficiently using the alternating direction method of multipliers. Experiments are conducted for both synthetic and semi-real data. Simulation results show that the proposed unmixing-based fusion scheme improves both the abundance and endmember estimation compared with the state-of-the-art joint fusion and unmixing algorithms. Numéro de notice : A2016-930 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2016.2598784 En ligne : https://doi.org/10.1109/TGRS.2016.2598784 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=83344
in IEEE Transactions on geoscience and remote sensing > vol 54 n° 12 (December 2016) . - pp 7236 - 7249[article]A Computationally efficient algorithm for fusing multispectral and hyperspectral images / Raúl Guerra in IEEE Transactions on geoscience and remote sensing, vol 54 n° 10 (October 2016)
[article]
Titre : A Computationally efficient algorithm for fusing multispectral and hyperspectral images Type de document : Article/Communication Auteurs : Raúl Guerra, Auteur ; Sebastian Lopez, Auteur ; Roberto Sarmiento, Auteur Année de publication : 2016 Article en page(s) : pp 5712 - 5728 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] algorithme de fusion
[Termes IGN] analyse combinatoire (maths)
[Termes IGN] fusion d'images
[Termes IGN] image hyperspectrale
[Termes IGN] image multibande
[Termes IGN] qualité d'imageRésumé : (auteur) Remote sensing systems equipped with multispectral and hyperspectral sensors are able to capture images of the surface of the Earth at different wavelengths. In these systems, hyperspectral sensors typically provide images with a high spectral resolution but a reduced spatial resolution, while on the contrary, multispectral sensors are able to produce images with a rich spatial resolution but a poor spectral resolution. Due to this reason, different fusion algorithms have been proposed during the last years in order to obtain remotely sensed images with enriched spatial and spectral resolutions by wisely combining the data acquired for the same scene by multispectral and hyperspectral sensors. However, the algorithms so far proposed that are able to obtain fused images with a good spatial and spectral quality require a formidable amount of computationally complex operations that cannot be executed in parallel, which clearly prevent the utilization of these algorithms in applications under real-time constraints in which high-performance parallel-based computing systems are normally required for accelerating the overall process. On the other hand, there are other state-of-the-art algorithms that are capable of fusing these images with a lower computational effort but at the cost of decreasing the quality of the resultant fused image. In this paper, a new algorithm named computationally efficient algorithm for fusing multispectral and hyperspectral images (CoEf-MHI) is proposed in order to obtain a high-quality image from hyperspectral and multispectral images of the same scene with a low computational effort. The proposed CoEf-MHI algorithm is based on incorporating the spatial details of the multispectral image into the hyperspectral image, without introducing spectral distortions. To achieve this goal, the CoEf-MHI algorithm first spatially upsamples, by means of a bilinear interpolation, the input hyperspectral image to the spatial resolution of the input multispectral image, and then, it independently refines each pixel of the resulting image by linearly combining the multispectral and hyperspectral pixels in its neighborhood. The simulations performed in this work with different images demonstrate that our proposal is much more efficient than state-of-the-art approaches, being this efficiency understood as the ratio between the quality of the fused image and the computational effort required to obtain such image. Numéro de notice : A2016-860 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2016.2570433 En ligne : https://doi.org/10.1109/TGRS.2016.2570433 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=82889
in IEEE Transactions on geoscience and remote sensing > vol 54 n° 10 (October 2016) . - pp 5712 - 5728[article]Image processing and GIS techniques applied to high resolution satellite data for lineament mapping of thermal power plant site in Allahabad district, U.P., India / Aniruddha Uniyal in Geocarto international, Vol 31 n° 9 - 10 (October - November 2016)
[article]
Titre : Image processing and GIS techniques applied to high resolution satellite data for lineament mapping of thermal power plant site in Allahabad district, U.P., India Type de document : Article/Communication Auteurs : Aniruddha Uniyal, Auteur ; P.N. Shah, Auteur ; Rajiva Mohan, Auteur Année de publication : 2016 Article en page(s) : pp 956 - 965 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse en composantes principales
[Termes IGN] centrale thermique
[Termes IGN] fusion d'images
[Termes IGN] géomorphologie locale
[Termes IGN] image IRS-LISS
[Termes IGN] Inde
[Termes IGN] linéament
[Termes IGN] système d'information géographique
[Termes IGN] transformation intensité-teinte-saturationRésumé : (auteur) The present study is based on digital analysis of IRS 1C/1D LISS-III and IRS P6 LISS-IV images for identification of lineaments in Meja Thermal Power Plant site in Allahabad district. In spite of all limitations due to anthropogenic activities of stone quarrying and criss cross unmetalled roads, almost non-existent vegetation indicators and soil moisture, the efforts were made to identify and map a number of lineaments in the study area and these were subsequently verified in the field. Most of the lineaments identified and mapped are not having any major displacement along them or are not displacing or truncating any major rock unit. Field investigations have revealed that there is no drastic change in the trend of rocks along the lineaments mapped in the study area. On the basis of digital analysis of IRS P6 LISS-IV data NE–SW and NW–SE trending lineaments have been identified and mapped. Some NNE–SSW trending lineaments have also been mapped. All the lineaments demarcated in this area still need to be correlated with the seismic data of the area by superimposing the microseismicity data over lineaments. Numéro de notice : A2016-668 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2015.1094525 Date de publication en ligne : 02/11/2015 En ligne : http://dx.doi.org/10.1080/10106049.2015.1094525 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=81900
in Geocarto international > Vol 31 n° 9 - 10 (October - November 2016) . - pp 956 - 965[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 059-2016051 RAB Revue Centre de documentation En réserve L003 Disponible Fusion of LiDAR orthowaveforms and hyperspectral imagery for shallow river bathymetry and turbidity estimation / Zhigang Pan in IEEE Transactions on geoscience and remote sensing, vol 54 n° 7 (July 2016)
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Titre : Fusion of LiDAR orthowaveforms and hyperspectral imagery for shallow river bathymetry and turbidity estimation Type de document : Article/Communication Auteurs : Zhigang Pan, Auteur ; Craig L. Glennie, Auteur ; Juan Carlos Fernandez-Diaz, Auteur ; et al., Auteur Année de publication : 2016 Article en page(s) : pp 4165 - 4177 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image mixte
[Termes IGN] bathymétrie
[Termes IGN] données lidar
[Termes IGN] fusion d'images
[Termes IGN] image hyperspectrale
[Termes IGN] profondeurRésumé : (Auteur) We propose an approach to voxelize bathymetric full-waveform LiDAR (Light Detection and Ranging) to generate orthowaveforms and use them to estimate shallow water bathymetry and turbidity with a nonparametric support vector regression (SVR) method. Two distinct shallow rivers were investigated ranging from clear to turbid water; hyperspectral imagery and traditional full-waveform LiDAR processing were also investigated as a baseline for comparison with the proposed orthowaveform strategy. The orthowaveform showed significant correlation to water depth in both scenarios and outperformed hyperspectral imagery for water depth estimation in more turbid water. The orthowaveforms showed similar performance to full-waveform LiDAR point observations for bathymetry estimation in clear water and outperformed the bathymetry performance of full-waveform processing in turbid water. The orthowaveforms also showed similar performance to hyperspectral imagery for predicting water turbidity in turbid water, with a root mean square error (RMSE) of 1.32 NTU. The fusion of both hyperspectral imagery and orthowaveforms was also investigated and gave superior performance to using either data set alone. The fused data set was able to estimate depth in clear and turbid water with an RMSE of 10 and 21 cm, respectively, and turbidity with an RMSE of 1.16 NTU. Numéro de notice : A2016-880 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2016.2538089 En ligne : https://doi.org/10.1109/TGRS.2016.2538089 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=83043
in IEEE Transactions on geoscience and remote sensing > vol 54 n° 7 (July 2016) . - pp 4165 - 4177[article]Pan-sharpening quality investigation of PLÉIADES-1A images / Mustafa Ozendi in Geocarto international, vol 31 n° 7 - 8 (July - August 2016)
[article]
Titre : Pan-sharpening quality investigation of PLÉIADES-1A images Type de document : Article/Communication Auteurs : Mustafa Ozendi, Auteur ; Hyseyin Topan, Auteur ; Murat Oruc, Auteur ; Ali Cam, Auteur Année de publication : 2016 Article en page(s) : pp 881 - 890 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] affinage d'image
[Termes IGN] analyse en composantes principales
[Termes IGN] coefficient de corrélation
[Termes IGN] évaluation des données
[Termes IGN] image Pléiades-HR
[Termes IGN] pansharpening (fusion d'images)
[Termes IGN] qualité du processus
[Termes IGN] transformation de Brovey
[Termes IGN] transformation intensité-teinte-saturationRésumé : (Auteur) Optical remote sensing satellites obtain MS and Pan images simultaneously over the same coverage area. Remote sensing and image processing communities are working on different pan-sharpening methods capable of taking advantage of MS and Pan images. Each remote sensing system has its own advantages and disadvantages, leading to the question ‘Which pan-sharpening method should be used for which type of imagery?’ The aim of this research is to investigate the pan-sharpening performance of PLÉIADES-1A images. For this purpose, pan-sharpened images were generated using PCA, IHS and Brovey Transform which are the most popular pan-sharpening methods. Then, the pan-sharpened images were evaluated quantitatively using Correlation Coefficient, Root Mean Square Error, Relative Average Spectral Error, Spectral Angle Mapper and Erreur Relative Globale Adimensionnelle de Synthése. In addition, pan-sharpened images were evaluated qualitatively by taking object availability and completeness into consideration. Numéro de notice : A2016-459 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2015.1094520 Date de publication en ligne : 20/10/2015 En ligne : http://dx.doi.org/10.1080/10106049.2015.1094520 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=81383
in Geocarto international > vol 31 n° 7 - 8 (July - August 2016) . - pp 881 - 890[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 059-2016041 RAB Revue Centre de documentation En réserve L003 Disponible Fusion of hyperspectral and VHR multispectral image classifications in urban α–areas / Alexandre Hervieu in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol III-3 (July 2016)PermalinkExploiting joint sparsity for pansharpening : the J-SparseFI algorithm / Xiao Xiang Zhu in IEEE Transactions on geoscience and remote sensing, vol 54 n° 5 (May 2016)PermalinkData fusion technique using wavelet transform and Taguchi methods for automatic landslide detection from airborne laser scanning data and QuickBird satellite imagery / Biswajeet Pradhan in IEEE Transactions on geoscience and remote sensing, vol 54 n° 3 (March 2016)PermalinkQuantitative quality evaluation of pansharpened imagery: consistency versus synthesis / Frosti Palsson in IEEE Transactions on geoscience and remote sensing, vol 54 n° 3 (March 2016)PermalinkPermalinkTowards a system combining SAR and optical Sentinel data to monitor gold mining in the Guiana shield / Mathieu Rahm (2016)PermalinkFusion of waveform LiDAR data and hyperspectral imagery for land cover classification / Hongzhou Wang in ISPRS Journal of photogrammetry and remote sensing, vol 108 (October 2015)PermalinkMultiangle BSAR imaging based on BeiDou-2 navigation satellite system: experiments and preliminary results / Tao Zeng in IEEE Transactions on geoscience and remote sensing, vol 53 n° 10 (October 2015)PermalinkRoad orthophoto/DTM generation from mobile laser scanning / Bruno Vallet in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol II-3 W5 (October 2015)PermalinkHyperspectral and multispectral image fusion based on a sparse representation / Qi Wei in IEEE Transactions on geoscience and remote sensing, vol 53 n° 7 (July 2015)Permalink