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Integrating spatio-temporal-spectral information for downscaling Sentinel-3 OLCI images / Yijie Tang in ISPRS Journal of photogrammetry and remote sensing, vol 180 (October 2021)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 180 (October 2021) . - pp 130 - 150 Titre : Integrating spatio-temporal-spectral information for downscaling Sentinel-3 OLCI images Type de document : Article/Communication Auteurs : Yijie Tang, Auteur ; Qunming Wang, Auteur ; Xiaohua Tong, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 130 - 150 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] données spatiotemporelles [Termes IGN] fusion d'images [Termes IGN] image multibande [Termes IGN] image Sentinel-MSI [Termes IGN] image Sentinel-OLCI [Termes IGN] pouvoir de résolution géométrique [Termes IGN] réduction d'échelle [Termes IGN] réflectance Résumé : (auteur) Sentinel-3 is a newly launched satellite implemented by the European Space Agency (ESA) for global observation. The Ocean and Land Colour Imager (OLCI) sensor onboard Sentinel-3 provides 21 band images with a fine spectral resolution and is of great value for ocean, land and atmospheric monitoring. The two platforms (Sentinel-3A and -3B) can provide OLCI images at an almost daily temporal resolution. The coarse spatial resolution of the 21 band OLCI images (i.e., 300 m), however, limits greatly their utility for local, precise monitoring. Sentinel-2, another satellite provided by ESA, carries the Multispectral Imager (MSI) sensor which can supply much finer spatial resolution (e.g., 10 m and 20 m) images. This paper introduces a new fusion framework integrating spatio-temporal-spectral information for downscaling Sentinel-3 OLCI images, which has two parts. Based on bands with similar wavelengths (i.e., bands 2, 3, 4 and 8a for Sentinel-2 and bands Oa4, Oa6, Oa8 and Oa17 for Sentinel-3), the four Sentinel-3 bands are first downscaled to the spatial resolution of Sentinel-2 images by applying spatio-temporal fusion to Sentinel-2 MSI and Sentinel-3 OLCI images. Then, to take full advantage of all 21 available OLCI bands of the Sentinel-3 images, the extended image pair-based spatio-spectral fusion (EIPSSF) method is proposed in this paper to downscale the other 17 bands. EIPSSF is performed based on the new concept of the extended image pair (EIP) and by exploiting existing spatio-temporal fusion approaches. The framework consisting of spatio-temporal and spatio-spectral fusion is entirely general, which provides a practical solution for comprehensive downscaling of Sentinel-3 OLCI images for fine spatial, temporal and spectral resolution monitoring. Numéro de notice : A2021-654 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2021.08.012 date de publication en ligne : 24/08/2021 En ligne : https://doi.org/10.1016/j.isprsjprs.2021.08.012 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98384 [article]

Landslide susceptibility prediction based on image semantic segmentation / Bowen Du in Computers & geosciences, vol 155 (October 2021)  

Public [article]  inComputers & geosciences > vol 155 (October 2021) . - n° 104860 Titre : Landslide susceptibility prediction based on image semantic segmentation Type de document : Article/Communication Auteurs : Bowen Du, Auteur ; Zirong Zhao, Auteur ; Xiao Hu, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 104860 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] aléa [Termes IGN] apprentissage automatique [Termes IGN] Chine [Termes IGN] classification par réseau neuronal convolutif [Termes IGN] effondrement de terrain [Termes IGN] image captée par drone [Termes IGN] modèle de simulation [Termes IGN] prévention des risques [Termes IGN] segmentation sémantique Résumé : (auteur) Numéro de notice : A2021-683 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1016/j.cageo.2021.104860 date de publication en ligne : 16/06/2021 En ligne : https://doi.org/10.1016/j.cageo.2021.104860 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98408 [article]

Automatic building detection with polygonizing and attribute extraction from high-resolution images / Samitha Daranagama in ISPRS International journal of geo-information, vol 10 n° 9 (September 2021)  

Public [article]  inISPRS International journal of geo-information > vol 10 n° 9 (September 2021) . - n° 606 Titre : Automatic building detection with polygonizing and attribute extraction from high-resolution images Type de document : Article/Communication Auteurs : Samitha Daranagama, Auteur ; Apichon Witayangkurn, Auteur Année de publication : 2021 Article en page(s) : n° 606 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] algorithme de Douglas-Peucker [Termes IGN] apprentissage profond [Termes IGN] détection du bâti [Termes IGN] image à haute résolution [Termes IGN] image captée par drone [Termes IGN] lissage de courbe [Termes IGN] orthophotoplan numérique [Termes IGN] polygonation [Termes IGN] segmentation sémantique Résumé : (auteur) Buildings can be introduced as a fundamental element for forming a city. Therefore, up-to-date building maps have become vital for many applications, including urban mapping and urban expansion analysis. With the development of deep learning, segmenting building footprints from high-resolution remote sensing imagery has become a subject of intense study. Here, a modified version of the U-Net architecture with a combination of pre- and post-processing techniques was developed to extract building footprints from high-resolution aerial imagery and unmanned aerial vehicle (UAV) imagery. Data pre-processing with the logarithmic correction image enhancing algorithm showed the most significant improvement in the building detection accuracy for aerial images; meanwhile, the CLAHE algorithm improved the most concerning UAV images. This study developed a post-processing technique using polygonizing and polygon smoothing called the Douglas–Peucker algorithm, which made the building output directly ready to use for different applications. The attribute information, land use data, and population count data were applied using two open datasets. In addition, the building area and perimeter of each building were calculated as geometric attributes. Numéro de notice : A2021-684 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.3390/ijgi10090606 date de publication en ligne : 14/09/2021 En ligne : https://doi.org/10.3390/ijgi10090606 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98410 [article]

Binary space partitioning visibility tree for polygonal and environment light rendering / Hiroki Okuno in The Visual Computer, vol 37 n° 9 - 11 (September 2021)  

Public [article]  inThe Visual Computer > vol 37 n° 9 - 11 (September 2021) . - pp 2499 - 2511 Titre : Binary space partitioning visibility tree for polygonal and environment light rendering Type de document : Article/Communication Auteurs : Hiroki Okuno, Auteur ; Kei Iwasaki, Auteur Année de publication : 2021 Article en page(s) : pp 2499 - 2511 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] arbre BSP [Termes IGN] distribution du coefficient de réflexion bidirectionnelle BRDF [Termes IGN] éclairage [Termes IGN] éclairement lumineux [Termes IGN] équation intégrale [Termes IGN] intensité lumineuse [Termes IGN] ombre [Termes IGN] polygone [Termes IGN] réflectance [Termes IGN] visibilité (optique) Résumé : (auteur) In this paper, we present a geometric approach to render shadows for physically based materials under polygonal light sources. Direct illumination calculation from a polygonal light source involves the triple product integral of the lighting, the bidirectional reflectance distribution function (BRDF), and the visibility function over the polygonal domain, which is computation intensive. To achieve real-time performance, work on polygonal light shading exploits analytical solutions of boundary integrals along the edges of the polygonal light at the cost of lacking shadowing effects. We introduce a hierarchical representation for the precomputed visibility function to retain the merits of closed-form solutions for boundary integrals. Our method subdivides the polygonal light into a set of polygons visible from a point to be shaded. Experimental results show that our method can render complex shadows with a GGX microfacet BRDF from polygonal light sources at interactive frame rates. In addition, our visibility representation can be easily incorporated into environment lighting. Numéro de notice : A2021-644 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1007/s00371-021-02181-8 date de publication en ligne : 14/06/2021 En ligne : https://doi.org/10.1007/s00371-021-02181-8 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98345 [article]

Hyperspectral image fusion and multitemporal image fusion by joint sparsity / Han Pan in IEEE Transactions on geoscience and remote sensing, Vol 59 n° 9 (September 2021)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > Vol 59 n° 9 (September 2021) . - pp 7887 - 7900 Titre : Hyperspectral image fusion and multitemporal image fusion by joint sparsity Type de document : Article/Communication Auteurs : Han Pan, Auteur ; Zhongliang Jing, Auteur ; Henry Leung, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 7887 - 7900 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] correction d'image [Termes IGN] flou [Termes IGN] fusion d'images [Termes IGN] image hyperspectrale [Termes IGN] image multitemporelle [Termes IGN] image panchromatique [Termes IGN] pansharpening (fusion d'images) [Termes IGN] représentation parcimonieuse Résumé : (auteur) Different image fusion systems have been developed to deal with the massive amounts of image data for different applications, such as remote sensing, computer vision, and environment monitoring. However, the generalizability and versatility of these fusion systems remain unknown. This article proposes an efficient regularization framework to achieve different kinds of fusion tasks accounting for the spatiospectral and spatiotemporal variabilities of the fusion process. A joint minimization functional is developed by taking an advantage of a composite regularizer for enforcing joint sparsity in the gradient domain and the frame domain. The proposed composite regularizer is composed of the Hessian Schatten-norm regularization and contourlet-based regularization terms. The resulting problems are solved by the alternating direction method of multipliers (ADMM). The effectiveness of the proposed method is validated in a variety of image fusion experiments: 1) hyperspectral (HS) and panchromatic image fusion; 2) HS and multispectral image fusion; 3) multitemporal image fusion (MIF); and 4) multi-image deblurring. Results show promising performance compared with state-of-the-art fusion methods. Numéro de notice : A2021-649 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2020.3039046 date de publication en ligne : 07/12/2020 En ligne : https://doi.org/10.1109/TGRS.2020.3039046 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98360 [article]

Multi-task fully convolutional network for tree species mapping in dense forests using small training hyperspectral data / Laura Elena Cué La Rosa in ISPRS Journal of photogrammetry and remote sensing, vol 179 (September 2021)  

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Stochastic super-resolution for downscaling time-evolving atmospheric fields with a generative adversarial network / Jussi Leinonen in IEEE Transactions on geoscience and remote sensing, Vol 59 n° 9 (September 2021)  

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Utilisation de l'apprentissage profond dans la modélisation 3D urbaine [Partie 1] / Hamza Ben Addou in Géomatique expert, n° 135 (septembre 2021)

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Classification of tree species in a heterogeneous urban environment using object-based ensemble analysis and World View-2 satellite imagery / Simbarashe Jombo in Applied geomatics, vol 13 n° 3 (September 2021)  

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Two hidden layer neural network-based rotation forest ensemble for hyperspectral image classification / Laxmi Narayana Eeti in Geocarto international, vol 36 n° 16 ([17/08/2021])  

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Unsupervised band selection of hyperspectral data based on mutual information derived from weighted cluster entropy for snow classification / Divyesh Varade in Geocarto international, Vol 36 n° 15 ([10/08/2021])  

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Background segmentation in multicolored illumination environments / Nikolas Ladas in The Visual Computer, vol 37 n° 8 (August 2021)  

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Deep learning-based image de-raining using discrete Fourier transformation / Prasen Kumar Sharma in The Visual Computer, vol 37 n° 8 (August 2021)  

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Vehicle detection in very-high-resolution remote sensing images based on an anchor-free detection model with a more precise foveal area / Xungen Li in ISPRS International journal of geo-information, vol 10 n° 8 (August 2021)  

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ComNet: combinational neural network for object detection in UAV-borne thermal images / Minglei Li in IEEE Transactions on geoscience and remote sensing, vol 59 n° 8 (August 2021)  

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