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Geometric calibration of satellite laser altimeters based on waveform matching / Shaoning Li in Photogrammetric record, vol 36 n° 174 (June 2021)  

Public [article]  inPhotogrammetric record > vol 36 n° 174 (June 2021) . - pp 104 - 123 Titre : Geometric calibration of satellite laser altimeters based on waveform matching Type de document : Article/Communication Auteurs : Shaoning Li, Auteur ; Chaokui Li, Auteur ; Guo Zhang, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 104 - 123 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Photogrammétrie numérique [Termes IGN] données IceSat-Glas [Termes IGN] étalonnage géométrique [Termes IGN] forme d'onde pleine [Termes IGN] Geoscience Laser Altimeter System [Termes IGN] lidar à retour d'onde complète [Termes IGN] modèle numérique de surface [Termes IGN] point d'appui [Termes IGN] précision altimétrique [Termes IGN] signal laser [Termes IGN] télémétrie laser Résumé : (auteur) This study proposes a new geometric calibration method for satellite laser altimeters based on waveform matching to solve the problems of poor initial pointing accuracy and a lack of control data. This non-real-time method obtains ground control points without a fixed calibration field. First, a large area with stepped surfaces is chosen from the laser altimetry coverage. Then, the laser echo waveforms are simulated using digital surface model (DSM) data of the stepped features. The real echo waveform attempts to match the simulated echo waveforms through a waveform matching model using a global constraint. Next, the control points of the laser altimeter are obtained through waveform matching. Finally, a geometric calibration model for laser altimeters is proposed to compensate for laser pointing and ranging errors. Two experiments were conducted to verify the calibration method using ICESat/GLAS data and airborne large-footprint laser data. Experimental results confirm that the method is feasible and results in an improvement in the elevation accuracy for the airborne altimeter from 2 to 0.5 m. Numéro de notice : A2021-473 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1111/phor.12362 date de publication en ligne : 07/05/2021 En ligne : https://doi.org/10.1111/phor.12362 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97926 [article]

A generic framework for improving the geopositioning accuracy of multi-source optical and SAR imagery / Niangang Jiao in ISPRS Journal of photogrammetry and remote sensing, vol 169 (November 2020)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 169 (November 2020) . - pp 377 - 388 Titre : A generic framework for improving the geopositioning accuracy of multi-source optical and SAR imagery Type de document : Article/Communication Auteurs : Niangang Jiao, Auteur ; Feng Wang, Auteur ; Hongjian You, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 377 - 388 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image mixte [Termes IGN] chaîne de traitement [Termes IGN] correction géométrique [Termes IGN] étalonnage géométrique [Termes IGN] géolocalisation [Termes IGN] image Gaofen [Termes IGN] image Jilin [Termes IGN] image optique [Termes IGN] image radar moirée [Termes IGN] image satellite [Termes IGN] point d'appui [Termes IGN] précision géométrique (imagerie) Résumé : (auteur) To date, numerous Earth observation datasets from different types of satellites have been widely used in photogrammetric fields, including urban 3D modelling and geographic information systems. The development of small satellites has provided a new way to obtain repeated observations in a short period. However, compared with that of standard satellite imagery, the geometric performance of imagery from small satellites is relatively poor, restricting their photogrammetric applications. Traditional methods can improve the accuracy of optical images with the addition of well-distributed ground control points (GCPs), which require considerable financial and human resources. The collection of multi-view datasets is an alternative method for geometric processing without GCPs, but relies heavily on the stability and revisit period of satellite platforms. Therefore, this paper presents a framework for improving the geopositioning accuracy of multi-source datasets obtained from optical and synthetic aperture radar (SAR) satellites, and a novel heterogeneous weight strategy is proposed based on an analysis of the geometric error sources of SAR and optical images. The geometric performance of multi-source optical imagery from the Jilin-1 (JL-1) small satellite constellation is evaluated and analysed first, and then Gaofen-3 (GF-3) SAR images are calibrated based on statistical analysis for the production of virtual control points (VCPs). Based on our proposed heterogeneous weight strategy, multi-source optical and SAR images are integrated to improve the geopositioning accuracy. Experimental results indicate that our proposed model can achieve the best performance compared with other popular models, producing an accuracy of approximately 3 m in planimetry and 2 m in height, thereby providing a generic way to synergistically use multi-source remote sensing data. Numéro de notice : A2020-642 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2020.09.017 date de publication en ligne : 12/10/2020 En ligne : https://doi.org/10.1016/j.isprsjprs.2020.09.017 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96066 [article]

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Global iterative geometric calibration of a linear optical satellite based on sparse GCPs / Yingdong Pi in IEEE Transactions on geoscience and remote sensing, vol 58 n° 1 (January 2020)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 58 n° 1 (January 2020) . - pp 436 - 446 Titre : Global iterative geometric calibration of a linear optical satellite based on sparse GCPs Type de document : Article/Communication Auteurs : Yingdong Pi, Auteur ; Xin Li, Auteur ; Bo Yang, Auteur Année de publication : 2020 Article en page(s) : pp 436 - 446 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] élément d'orientation interne [Termes IGN] erreur systématique [Termes IGN] étalonnage géométrique [Termes IGN] image satellite [Termes IGN] image SPOT-HRV [Termes IGN] itération [Termes IGN] longueur focale [Termes IGN] modèle numérique de surface [Termes IGN] point d'appui Résumé : (auteur) Independent methods for geometric calibration (GC) have become an important research direction in the field of optical satellite technology. The main purpose of this research is to eliminate dependence on ground calibration sites using relative constraints between images. Based on a systematic analysis of these relative constraints, we found that it was difficult, if not impossible, to completely eliminate ground constraints, although the number of ground control points (GCPs) required can be greatly reduced. To achieve practical GC with high accuracy and low cost, we proposed a new method to compensate for systematic errors in linear optical satellite data acquisition using only the relative constraints between two overlapped images, namely, the corresponding elevation constraints and sparse GCPs. We first demonstrated the feasibility of GC with relative constraints and established an optimized GC model suitable for these relative constraints. We then presented a global iterative method to eliminate inaccuracies in internal calibration caused by the different distributions of GCPs within two images. The nadir (NAD) linear camera on board the Zi-Yuan 3 (ZY-3) satellite was used to evaluate the feasibility of the presented GC method; the results indicated that the present method effectively compensated for systematic errors. Thus, this article demonstrated the feasibility of GC without calibration sites. Numéro de notice : A2020-075 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2019.2936891 date de publication en ligne : 12/09/2019 En ligne : https://doi.org/10.1109/TGRS.2019.2936891 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94607 [article]

Learning stereo reconstruction with deep neural networks / Stepan Tulyakov (2020)  

Public Titre : Learning stereo reconstruction with deep neural networks Type de document : Thèse/HDR Auteurs : Stepan Tulyakov, Auteur ; François Fleuret, Directeur de thèse ; Anton Ivanov, Directeur de thèse Editeur : Lausanne : Ecole Polytechnique Fédérale de Lausanne EPFL Année de publication : 2020 Importance : 139 p. Format : 21 x 30 cm Note générale : bibliographie Thèse présentée à l'Ecole Polytechnique Fédérale de Lausanne pour l’obtention du grade de Docteur ès Sciences Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] apprentissage profond [Termes IGN] classification semi-dirigée [Termes IGN] contrainte géométrique [Termes IGN] couple stéréoscopique [Termes IGN] entropie [Termes IGN] estimateur [Termes IGN] étalonnage géométrique [Termes IGN] modèle stéréoscopique [Termes IGN] profondeur [Termes IGN] réalité de terrain [Termes IGN] reconstruction 3D [Termes IGN] reconstruction d'image [Termes IGN] vision par ordinateur [Termes IGN] vision stéréoscopique Résumé : (auteur) Stereo reconstruction is a problem of recovering a 3d structure of a scene from a pair of images of the scene, acquired from different viewpoints. It has been investigated for decades and many successful methods were developed. The main drawback of these methods, is that they typically utilize a single depth cue, such as parallax, defocus blur or shading, and thus are not as robust as a human visual system that simultaneously relies on a range of monocular and binocular cues. This is mainly because it is hard to manually design a model, accounting for multiple depth cues. In this work, we address this problem by focusing on deep learning-based stereo methods that can discover a model for multiple depth cues directly from training data with ground truth depth. The complexity of deep learning-based methods, however, requires very large training sets with ground truth depth, which is often hard or costly to collect. Furthermore, even when training data is available it is often contaminated with noise, which reduces the effectiveness of supervised learning. In this work, in Chapter 3 we show that it is possible to alleviate this problem by using weakly supervised learning, that utilizes geometric constraints of the problem instead of ground truth depth. Besides the large training set requirement, deep stereo methods are not as application-friendlyas traditional methods. They have a large memory footprint and their disparity range is fixed at training time. For some applications, such as satellite stereo i magery, these are serious problems since satellite images are very large, often reaching tens of megapixels, and have a variable baseline, depending on a time difference between stereo images acquisition. In this work, in Chapter 4 we address these problems by introducing a novel network architecture with a bottleneck, capable of processing large images and utilizing more context, and an estimator that makes the network less sensitive to stereo matching ambiguities and applicable to any disparity range without re-training. Because deep learning-based methods discover depth cues directly from training data, they can be adapted to new data modalities without large modifications. In this work, in Chapter 5 we show that our method, developed for a conventional frame-based camera, can be used with a novel event-based camera, that has a higher dynamic range, smaller latency, and low power consumption. Instead of sampling intensity of all pixels with a fixed frequency, this camera asynchronously reports events of significant pixel intensity changes. To adopt our method to this new data modality, we propose a novel event sequence embedding module, that firstly aggregates information locally, across time, using a novel fully-connected layer for an irregularly sampled continuous domain, and then across discrete spatial domain. One interesting application of stereo is a reconstruction of a planet’s surface topography from satellite stereo images. In this work, in Chapter 6 we describe a geometric calibration method, as well as mosaicing and stereo reconstruction tools that we developed in the framework of the doctoral project for Color and Stereo Surface Imaging System onboard of ESA’s Trace Gas Orbiter, orbiting Mars. For the calibration, we propose a novel method, relying on starfield images because large focal lengths and complex optical distortion of the instrument forbid using standard methods. Scientific and practical results of this work are widely used by a scientific community. Note de contenu : 1- Introduction 2- Background 3- Weakly supervised learning of deep patch-matching cost 4- Applications-friendly deep stereo 5- Dense deep event-based stereo 6- Calibration of a satellite stereo system 7- Conclusions Numéro de notice : 25795 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Thèse étrangère Note de thèse : Thèse de Doctorat : Sciences : Lausanne : 2020 En ligne : https://infoscience.epfl.ch/record/275342?ln=fr Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95025

Hemispherical sky radiance measurement using a fish-eye camera / Manchun Lei (2018)    

Public Titre : Hemispherical sky radiance measurement using a fish-eye camera Type de document : Article/Communication Auteurs : Manchun Lei , Auteur ; Ewelina Rupnik , Auteur ; Jean-Pierre Papelard , Auteur ; Lâmân Lelégard , Auteur ; Olivier Martin , Auteur ; Jean-Philippe Souchon, Auteur ; Christophe Meynard, Auteur Editeur : Saint-Mandé : Institut national de l'information géographique et forestière - IGN Année de publication : 2018 Projets : 1-Pas de projet / Conférence : CFPT 2018, Conférence Française de Photogrammétrie et de Télédétection 25/06/2018 28/06/2018 Champs-sur-Marne France Open Access Proceedings Importance : 3 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Acquisition d'image(s) et de donnée(s) [Termes IGN] caméra numérique [Termes IGN] étalonnage géométrique [Termes IGN] étalonnage radiométrique [Termes IGN] image hémisphérique [Termes IGN] image numérique [Termes IGN] objectif grand angulaire Résumé : (auteur) The objective of this work is to perform sky radiance angular distribution measurement using a fish-eye camera. The imaging system provides hemispherical high dynamic range (HDR) sky radiance images at high spatial resolution and radiometric sensibility, which can be used as complementary information for urban remote sensing application such as shaded surface reflectance retrieval. This communication presents the instrument, the radiometric and geometric calibration in detail. Numéro de notice : C2018-012 Affiliation des auteurs : LaSTIG MATIS (2012-2019) Thématique : IMAGERIE Nature : Poster nature-HAL : Poster-avec-CL DOI : sans date de publication en ligne : 25/06/2018 En ligne : https://rfiap2018.ign.fr/sites/default/files/ARTICLES/CFPT2018/Posters/CFPT2018_ [...] Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90383

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Parameterising internal camera geometry with focusing distance / E. Sanz-Ablanedo in Photogrammetric record, vol 27 n° 138 (June - August 2012)  

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