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scientifique

Real-time atmospheric correction of AVIRIS-NG imagery / Brian D. Bue in IEEE Transactions on geoscience and remote sensing, vol 53 n° 12 (December 2015)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 53 n° 12 (December 2015) . - pp 6419 - 6428 Titre : Real-time atmospheric correction of AVIRIS-NG imagery Type de document : Article/Communication Auteurs : Brian D. Bue, Auteur ; David R. Thompson, Auteur ; Michael Eastwood, Auteur ; et al., Auteur Année de publication : 2015 Article en page(s) : pp 6419 - 6428 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] correction atmosphérique [Termes IGN] image aérienne [Termes IGN] image AVIRIS [Termes IGN] image proche infrarouge [Termes IGN] modèle stéréoscopique [Termes IGN] temps réel Résumé : (auteur) We demonstrate real-time model-based atmospheric correction onboard the Next Generation Airborne Visible/Infrared Imaging Spectrometer. We achieve a reduction in processing time from hours or days to seconds by modifying a standard physics-based atmospheric correction algorithm to support real-time execution. We achieved this reduction by modifying the physics-based ATmospheric REMoval algorithm to leverage a large lookup table of precomputed scattering and transmission coefficients, indexed by parameters specifying the aircraft operating conditions at capture time. Interpolation among the precomputed coefficients allows surface reflectance retrieval at the sensor acquisition rate of 500 Mb/s. Our system produced science-quality reflectance products during over 30 test flights and, to our knowledge, is the first reported demonstration of real-time model-driven visible shortwave infrared atmospheric correction onboard an aircraft. Numéro de notice : A2015-841 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2015.2439215 Date de publication en ligne : 23/06/2015 En ligne : https://doi.org/10.1109/TGRS.2015.2439215 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=79185 [article]

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Leveraging in-scene spectra for vegetation species discrimination with MESMA-MDA / Brian D. Bue in ISPRS Journal of photogrammetry and remote sensing, vol 108 (October 2015)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 108 (October 2015) . - pp 33 - 48 Titre : Leveraging in-scene spectra for vegetation species discrimination with MESMA-MDA Type de document : Article/Communication Auteurs : Brian D. Bue, Auteur ; David R. Thompson, Auteur ; R. Glenn Sellar, Auteur ; et al., Auteur Année de publication : 2015 Article en page(s) : pp 33 - 48 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] analyse de mélange spectral d’extrémités multiples [Termes IGN] analyse discriminante [Termes IGN] espèce végétale [Termes IGN] image hyperspectrale [Termes IGN] réflectance végétale [Termes IGN] signature spectrale [Termes IGN] spectromètre imageur Résumé : (auteur) We describe an approach to improve Multiple Endmember Spectral Mixture Analysis (MESMA) results for applications involving discrimination among spectrally-similar species, and commonly occur in multispectral and hyperspectral vegetation remote sensing studies. Such applications are inherently difficult, due to the high degree of similarity between distinct species, coupled with potentially high intra-species variability caused by factors such as growing conditions, canopy structure, ambient illumination, or substrate characteristics. We describe a method to map spectra to a feature space where distinctions between plant species are emphasized using a transformation based on Multiclass Discriminant Analysis. We compute this transformation using groups of pixels that represent individual plant canopies similar to the endmembers in MESMA’s spectral library, and describe a technique to automatically select such spectra from a given image. Compared to conventional MESMA, and also to several alternative MESMA formulations, we observe up to twofold increases in accuracy, along with a factor of ten reduction in computation time using our MESMA approach in several species discrimination applications. We demonstrate the effectiveness of our approach for agricultural species discrimination applications using spectra captured by two different imaging spectrometers. Numéro de notice : A2015-850 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2015.06.001 En ligne : https://doi.org/10.1016/j.isprsjprs.2015.06.001 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=79220 [article]