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Robust GNSS carrier phase-based position and attitude estimation theory and applications / Daniel Arias Medina (2022)  

Public Titre : Robust GNSS carrier phase-based position and attitude estimation theory and applications Type de document : Thèse/HDR Auteurs : Daniel Arias Medina, Auteur Editeur : Madrid [Espagne] : Universidad Carlos III Année de publication : 2022 Importance : 249 p. Format : 21 x 30 cm Note générale : bibliographie A dissertation submitted by in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Computer Science and Technology, Universidad Carlos III de Madrid Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie spatiale [Termes IGN] classification du maximum a posteriori [Termes IGN] constellation GNSS [Termes IGN] estimation de pose [Termes IGN] filtrage du bruit [Termes IGN] méthode du maximum de vraisemblance (estimation) [Termes IGN] phase GNSS [Termes IGN] positionnement cinématique en temps réel [Termes IGN] résolution d'ambiguïté [Termes IGN] signal GNSS Index. décimale : THESE Thèses et HDR Résumé : (auteur) Navigation information is an essential element for the functioning of robotic platforms and intelligent transportation systems. Among the existing technologies, Global Navigation Satellite Systems (GNSS) have established as the cornerstone for outdoor navigation, allowing for all-weather, all-time positioning and timing at a worldwide scale. GNSS is the generic term for referring to a constellation of satellites which transmit radio signals used primarily for ranging information. Therefore, the successful operation and deployment of prospective autonomous systems is subject to our capabilities to support GNSS in the provision of robust and precise navigational estimates. GNSS signals enable two types of ranging observations: –code pseudorange, which is a measure of the time difference between the signal’s emission and reception at the satellite and receiver, respectively, scaled by the speed of light; –carrier phase pseudorange, which measures the beat of the carrier signal and the number of accumulated full carrier cycles. While code pseudoranges provides an unambiguous measure of the distance between satellites and receiver, with a dm-level precision when disregarding atmospheric delays and clock offsets, carrier phase measurements present a much higher precision, at the cost of being ambiguous by an unknown number of integer cycles, commonly denoted as ambiguities. Thus, the maximum potential of GNSS, in terms of navigational precision, can be reach by the use of carrier phase observations which, in turn, lead to complicated estimation problems. This thesis deals with the estimation theory behind the provision of carrier phase-based precise navigation for vehicles traversing scenarios with harsh signal propagation conditions. Contributions to such a broad topic are made in three directions. First, the ultimate positioning performance is addressed, by proposing lower bounds on the signal processing realized at the receiver level and for the mixed real- and integer-valued problem related to carrier phase-based positioning. Second, multi-antenna configurations are considered for the computation of a vehicle’s orientation, introducing a new model for the joint position and attitude estimation problems and proposing new deterministic and recursive estimators based on Lie Theory. Finally, the framework of robust statistics is explored to propose new solutions to code- and carrier phase-based navigation, able to deal with outlying impulsive noises. Note de contenu : Introduction I- A signal processing approach to satellite-based navigation II- On the position and attitude estimation in multi-antenna GNSS III- Robust estimation for navigation in harsh environments Conclusions and future research Numéro de notice : 15279 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Thèse étrangère Note de thèse : PhD Thesis : Computer Science and Technology : Carlos III Madrid : 2022 Organisme de stage : German Aerospace Center DOI : sans En ligne : https://e-archivo.uc3m.es/handle/10016/35375#preview Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101116

Auxiliary tasks for the conditioning of generative adversarial networks / Cyprien Ruffino (2021)  

Public Titre : Auxiliary tasks for the conditioning of generative adversarial networks Type de document : Thèse/HDR Auteurs : Cyprien Ruffino, Auteur ; Gilles Gasso, Directeur de thèse Editeur : Rouen [France] : Institut National des Sciences Appliquées INSA Rouen Année de publication : 2021 Importance : 136 p. Format : 21 x 30 cm Note générale : bibliographie Pour obtenir le grade de Docteur de Normandie Université, Spécialité Informatique Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] apprentissage profond [Termes IGN] classification du maximum a posteriori [Termes IGN] classification non dirigée [Termes IGN] classification par réseau neuronal convolutif [Termes IGN] détection d'objet [Termes IGN] reconstruction d'image [Termes IGN] réseau antagoniste génératif [Termes IGN] restauration d'image Index. décimale : THESE Thèses et HDR Résumé : (auteur) During the last decade, Generative Adversarial Networks (GANs) have caused a tremendous leap forward in image generation as a whole. Their ability to learn very complex, high-dimension distributions not only had a huge impact on the field of generative modeling, their influence extended to the general public at large. By being the first models able generate high-dimension photo-realistic images, GANs very quickly gained popularity as an image generation and photo manipulation technique. For example, their use as "filters" became common practice on social media, but they also allowed for the rise of Deepfakes, images that have been manipulated in order to fake the identity of a person. In this thesis, we explore the conditioning of Generative Adversarial Networks, that is influencing the generation process in order to control the content of a generated image. We focus on conditioning through auxiliary tasks, that is we explicitly implement additional objective to the generative model to complement the initial goal of learning the data distribution. First, we introduce generative modeling through several examples, and present the Generative Adversarial Networks framework. We discuss theoretical interpretations of GANs as well as its most prominent issues, notably the lack of stability during training of the model and the difficulty to generate diverse samples. We review classical techniques for conditioning GANs and propose an overview of recent approaches aiming to both solve the aforementioned issues and enhance the visual quality of the generated images. Afterwards, we focus on a specific generation task that requires conditioning : image reconstruction. In a nutshell, the problem consists in recovering an image from which we only have a handful of pixels available, usually around 0.5%. It stems from an application in geostatistics, namely the reconstruction of underground terrain from a reduced amount of expensive and difficult to obtain measurements. To do so, we propose to introduce an explicit auxiliary reconstruction task to the GAN framework which, in addition to a diversity-restoring technique, allows for the generation of high-quality images that respect the given measurements. Finally, we investigate a task of domain-transfer with generative models, specifically transferring images from the RGB color domain to the polarimetric domain. Polarimetric images bear hard constraints that directly stem from the physics of polarimetry. Leveraging on the cyclic-consistency paradigm, we extend the training of generative models with auxiliary tasks that push the generator towards enforcing the polarimetric constraints. We highlight that the approach manages to generate physically realistic polarimetric. Note de contenu : Introduction 1- Introduction to Generative Adversarial Networks 2- Image reconstruction as an auxiliary task to generative modeling 3- Domain-transfer with with auxiliary tasks for generative modeling 4- Conclusion and Perspectives Numéro de notice : 28640 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Thèse française Note de thèse : Thèse de Doctorat : Informatique : Normandie : 2021 Organisme de stage : LITIS DOI : sans En ligne : https://tel.hal.science/tel-03517304/ Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99721

Spectral–spatial–temporal MAP-based sub-pixel mapping for land-cover change detection / Da He in IEEE Transactions on geoscience and remote sensing, vol 58 n° 3 (March 2020)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 58 n° 3 (March 2020) . - pp 1696 - 1717 Titre : Spectral–spatial–temporal MAP-based sub-pixel mapping for land-cover change detection Type de document : Article/Communication Auteurs : Da He, Auteur ; Yanfei Zhong, Auteur ; Liangpei Zhang, Auteur Année de publication : 2020 Article en page(s) : pp 1696 - 1717 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] changement d'occupation du sol [Termes IGN] classification du maximum a posteriori [Termes IGN] détection de changement [Termes IGN] distribution spatiale [Termes IGN] données spatiotemporelles [Termes IGN] image Aqua-MODIS [Termes IGN] image Landsat-8 [Termes IGN] image Landsat-TM [Termes IGN] image multibande [Termes IGN] image Quickbird [Termes IGN] image Terra-MODIS [Termes IGN] modèle dynamique [Termes IGN] optimisation spatiale [Termes IGN] précision infrapixellaire [Termes IGN] série temporelle [Termes IGN] urbanisation [Termes IGN] Wuhan (Chine) [Termes IGN] zone urbaine Résumé : (Auteur) The maximum a posteriori (MAP) estimation model-based sub-pixel mapping (SPM) method is an alternative way to solve the ill-posed SPM problem. The MAP estimation model has been proven to be an effective SPM approach and has been extensively developed over the past few years, as a result of its effective regularization capability that comes from the spatial regularization model. However, various spatial regularization models do not always truly reflect the detailed spatial distribution in a real situation, and the over-smoothing effect of the spatial regularization model always tends to efface the detailed structural information. In this article, under the scenario of time-series observation by remote sensing imagery, the joint spectral–spatial–temporal MAP-based (SST_MAP) model for SPM is proposed. In SST_MAP, a newly developed temporal regularization model is added to the MAP model, based on the prerequisite for a temporally close fine image covering the same study region. This available fine image can provide the specific spatial structures most closely conforming to the ground truth for a more precise constraint, thereby reducing the over-smoothing effect. Furthermore, the three dimensions are mutually balanced and mutually constrained, to reach an equilibrium point and achieve restoration of both smooth areas for the homogeneous land-cover classes and a detailed structure for the heterogeneous land-cover classes. Four experiments were designed to validate the proposed SST_MAP: three synthetic-image experiments and one real-image experiment. The restoration results confirm the superiority of the proposed SST_MAP model. Notably, under the background of time-series observation, SST_MAP provides an alternative way of land-cover change detection (LCCD), achieving both detailed spatial-scale and high-frequency temporal LCCD observation for the study case of urbanization analysis within the city of Wuhan in China. Numéro de notice : A2020-088 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2019.2947708 Date de publication en ligne : 18/12/2019 En ligne : https://doi.org/10.1109/TGRS.2019.2947708 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94662 [article]

An iterative interpolation deconvolution algorithm for superresolution land cover mapping / Feng Ling in IEEE Transactions on geoscience and remote sensing, vol 54 n° 12 (December 2016)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 54 n° 12 (December 2016) . - pp 7210 - 7222 Titre : An iterative interpolation deconvolution algorithm for superresolution land cover mapping Type de document : Article/Communication Auteurs : Feng Ling, Auteur ; Giles M. Foody, Auteur ; Yong Ge, Auteur ; et al., Auteur Année de publication : 2016 Article en page(s) : pp 7210 - 7222 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] carte d'occupation du sol [Termes IGN] classification du maximum a posteriori [Termes IGN] déconvolution [Termes IGN] image à ultra haute résolution [Termes IGN] itération Résumé : (Auteur) Superresolution mapping (SRM) is a method to produce a fine-spatial-resolution land cover map from coarse-spatial-resolution remotely sensed imagery. A popular approach for SRM is a two-step algorithm, which first increases the spatial resolution of coarse fraction images by interpolation and then determines class labels of fine-resolution pixels using the maximum a posteriori (MAP) principle. By constructing a new image formation process that establishes the relationship between the observed coarse-resolution fraction images and the latent fine-resolution land cover map, it is found that the MAP principle only matches with area-to-point interpolation algorithms and should be replaced by deconvolution if an area-to-area interpolation algorithm is to be applied. A novel iterative interpolation deconvolution (IID) SRM algorithm is proposed. The IID algorithm first interpolates coarse-resolution fraction images with an area-to-area interpolation algorithm and produces an initial fine-resolution land cover map by deconvolution. The fine-spatial-resolution land cover map is then updated by reconvolution, back-projection, and deconvolution iteratively until the final result is produced. The IID algorithm was evaluated with simulated shapes, simulated multispectral images, and degraded Landsat images, including comparison against three widely used SRM algorithms: pixel swapping, bilinear interpolation, and Hopfield neural network. Results show that the IID algorithm can reduce the impact of fraction errors and can preserve the patch continuity and the patch boundary smoothness simultaneously. Moreover, the IID algorithm produced fine-resolution land cover maps with higher accuracies than those produced by other SRM algorithms. Numéro de notice : A2016-928 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2016.2598534 En ligne : http://dx.doi.org/10.1109/TGRS.2016.2598534 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=83342 [article]

An adaptive subpixel mapping method based on MAP model and class determination strategy for hyperspectral remote sensing imagery / Yanfei Zhong in IEEE Transactions on geoscience and remote sensing, vol 53 n° 3 (March 2015)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 53 n° 3 (March 2015) . - pp 1411 - 1426 Titre : An adaptive subpixel mapping method based on MAP model and class determination strategy for hyperspectral remote sensing imagery Type de document : Article/Communication Auteurs : Yanfei Zhong, Auteur ; Yunyun Wu, Auteur ; Xiong Xu, Auteur ; et al., Auteur Année de publication : 2015 Article en page(s) : pp 1411 - 1426 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] analyse infrapixellaire [Termes IGN] analyse linéaire des mélanges spectraux [Termes IGN] classification du maximum a posteriori [Termes IGN] classification pixellaire [Termes IGN] image hyperspectrale [Termes IGN] traitement automatique d'images [Termes IGN] traitement de données localisées Résumé : (Auteur) The subpixel mapping technique can specify the spatial distribution of different categories at the subpixel scale by converting the abundance map into a higher resolution image, based on the assumption of spatial dependence. Traditional subpixel mapping algorithms only utilize the low-resolution image obtained by the classification image downsampling and do not consider the spectral unmixing error, which is difficult to account for in real applications. In this paper, to improve the accuracy of the subpixel mapping, an adaptive subpixel mapping method based on a maximum a posteriori (MAP) model and a winner-take-all class determination strategy, namely, AMCDSM, is proposed for hyperspectral remote sensing imagery. In AMCDSM, to better simulate a real remote sensing scene, the low-resolution abundance images are obtained by the spectral unmixing method from the downsampled original image or real low-resolution images. The MAP model is extended by considering the spatial prior models (Laplacian, total variation (TV), and bilateral TV) to obtain the high-resolution subpixel distribution map. To avoid the setting of the regularization parameter, an adaptive parameter selection method is designed to acquire the optimal subpixel mapping results. In addition, in AMCDSM, to take into account the spectral unmixing error in real applications, a winner-take-all strategy is proposed to achieve a better subpixel mapping result. The proposed method was tested on simulated, synthetic, and real hyperspectral images, and the experimental results demonstrate that the AMCDSM algorithm outperforms the traditional subpixel mapping methods and provides a simple and efficient algorithm to regularize the ill-posed subpixel mapping problem. Numéro de notice : A2015-132 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2014.2340734 Date de publication en ligne : 07/08/2014 En ligne : https://doi.org/10.1109/TGRS.2014.2340734 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=75796 [article]

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Extraction semi-automatique de thèmes d’occupation du sol en milieu montagneux à partir d’ortho-images et de connaissances complémentaires, en vue de la production de la carte de base / Arnaud Le Bris (2010)  

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Color image processing and applications / K.N. Plataniotis (2000)

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