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Exploiting 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)
[article]
Titre : Exploiting joint sparsity for pansharpening : the J-SparseFI algorithm Type de document : Article/Communication Auteurs : Xiao Xiang Zhu, Auteur ; Claas Grohnfeldt, Auteur ; Richard Bamler, Auteur Année de publication : 2016 Article en page(s) : pp 2664 - 2681 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] algorithme de fusion
[Termes IGN] données clairsemées
[Termes IGN] fusion d'images
[Termes IGN] image multibande
[Termes IGN] image panchromatique
[Termes IGN] image Worldview
[Termes IGN] reconstruction d'image
[Termes IGN] régularisation de Tychonoff
[Termes IGN] réponse spectraleRésumé : (Auteur) Recently, sparse signal representation of image patches has been explored to solve the pansharpening problem. Although these proposed sparse-reconstruction-based methods lead to promising results, three issues remained unsolved: 1) high computational cost; 2) no consideration given to the possibility of mutually correlated information in different multispectral channels; and 3) requirement that the spectral responses of the panchromatic (Pan) image and the multispectral image cover the same wavelength range, which is not necessarily valid for most sensors. In this paper, we propose a sophisticated sparse image fusion algorithm, which is named “jointly sparse fusion of images” (J-SparseFI). It is based on the earlier proposed sparse fusion of images (SparseFI) algorithm and overcomes the aforementioned three drawbacks of the existing sparse image fusion algorithms. The computational problem is handled by reducing the problem size and by proposing a fully parallelizable scheme. Moreover, J-SparseFI exploits the possible signal structure correlations between multispectral channels by introducing the joint sparsity model (JSM) and sharpening the highly correlated adjacent multispectral channels together. This is done by exploiting the distributed compressive sensing theory that restricts the solution of an underdetermined system by considering an ensemble of signals being jointly sparse. J-SparseFI also offers a practical solution to overcome spectral range mismatch between the Pan and multispectral images. By means of sensor spectral response and channel mutual correlation analysis, the multispectral channels are assigned to primary groups of joint channels, secondary groups of joint channels, and individual channels. Primary groups of joint channels, individual channels, and secondary groups of joint channels are then reconstructed sequentially, by the JSM or by modified SparseFI, using a dictionary trained from the Pan image or previously reconstructed high-resolution multispectral channels. A recipe of how to choose appropriate algorithm parameters, including the most crucial regularization parameter, is provided. The algorithm is evaluated and validated using WorldView-2-like images that are simulated using very high resolution airborne HySpex hyperspectral imagery and further practically demonstrated using real WorldView-2 images. The algorithm's performance is compared with other state-of-the-art methods. Visual and quantitative analyses demonstrate the high quality of the proposed method. In particular, the analysis of the difference images suggests that J-SparseFI is superior in image resolution recovery. Numéro de notice : A2016-844 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2015.2504261 En ligne : http://dx.doi.org/10.1109/TGRS.2015.2504261 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=82890
in IEEE Transactions on geoscience and remote sensing > vol 54 n° 5 (May 2016) . - pp 2664 - 2681[article]Autonomous navigation in complex nonplanar environments based on laser ranging / Philipp Andreas Krüsi (2016)
Titre : Autonomous navigation in complex nonplanar environments based on laser ranging Type de document : Thèse/HDR Auteurs : Philipp Andreas Krüsi, Auteur Editeur : Zurich : Eidgenossische Technische Hochschule ETH - Ecole Polytechnique Fédérale de Zurich EPFZ Année de publication : 2016 Note générale : bibliographie
A thesis submitted to attain the degree of doctor of sciences of ETH ZurichLangues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] algorithme ICP
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] navigation autonome
[Termes IGN] robot mobile
[Termes IGN] semis de points
[Termes IGN] télémètre laser
[Termes IGN] télémétrie laser aéroporté
[Termes IGN] télémétrie laser terrestre
[Termes IGN] temps réel
[Termes IGN] vision par ordinateurRésumé : (auteur) This thesis addresses the problem of autonomous navigation with ground robots in complex environments, which may be characterized as nonplanar and nonstatic. The goal of the presented research is to enable reliable navigation over large distances in generic indoor and outdoor environments, independent of external localization sources such as a global positioning system (GPS). Focusing on these challenges, algorithms for all building blocks of autonomous navigation—localization, mapping, terrain assessment, motion planning, and motion control—are developed, implemented, integrated, and finally evaluated in extensive field experiments. Sensor-based perception of the environment is a basic requirement for localization and mapping. We propose to use a high-frequency three-dimensional (3D) laser scanner as the main exteroceptive sensor. The advantages of this technology lie in the high density and accuracy of the provided measurements, and their independence of lighting and weather conditions. We develop a highly scalable system for six-dimensional (6D) localization and 3D mapping based on iterative closest point (ICP) matching. A topological/metric map representation, where metric information is kept in spatially constrained local submaps representing vertices in a graph, allows to build consistent large-scale maps without requiring global optimization. Long-term application in dynamic and changing environments is enabled by integrating methods for identifying dynamic objects in the scene and for continuously updating existing submaps. Planning feasible and safe motions for a robotic vehicle requires distinguishing obstacles from traversable terrain. We develop two different algorithms for terrain assessment. The first method is targeted at real-time obstacle detection in the vicinity of the robot. Assuming locally planar terrain, a grid-based obstacle map is built by analyzing the raw laser scans. The second approach is based on dense point cloud maps (which can be obtained from the ICP mapping system) and suitable for planar and nonplanar environments. The algorithm computes the geometry and the traversability of the terrain “on demand” at specific query locations, avoiding any artificial discretization or explicit surface reconstruction. The desired terrain characteristics are estimated based on statistics on the local distribution of map points. Given a specific navigation task, motion planning can be defined as the problem of reasoning about how to act based on the knowledge about the environment. This thesis addresses both local obstacle avoidance and global planning over large distances. Our approach to local planning consists of computing a set of candidate trajectories, which are shaped around nearby obstacles or along a given reference path, and enforced to satisfy the robot’s kinematic constraints. The optimal local trajectory is chosen by evaluating the motion alternatives in terms of guidance towards the goal and traversability of the underlying terrain. For global motion planning, we develop an algorithm embedding the proposed point-cloud-based terrain assessment method, which allows trajectories to be directly planned on 3D point cloud maps. The approach is designed to be suitable for generic nonplanar environments, including rough outdoor terrain, multi-level facilities, and more complex geometries. Piecewise continuous trajectories are computed in the full 6D space of robot poses, while strictly considering the vehicle’s kinematic and dynamic constraints. We apply sampling-based planning algorithms to generate an initial trajectory connecting the desired start and goal poses. Subsequently, the trajectory is locally optimized according to a generic cost function, which may include path length, path curvature, and roughness of the traversed terrain. While enforcing the hard constraints to remain satisfied (terrain contact, traversability, kinodynamic feasibility), the trajectory is iteratively deformed until a local minimum of the cost function is reached. We develop two complete systems for autonomous navigation, integrating these approaches. Combining the ICP-based localization and mapping framework with local obstacle detection and local motion planning, we implement a framework for autonomous route following, commonly referred to as teach and repeat (T&R). After a manually controlled teach run, where a graph of local submaps is built, the robot is able to automatically repeat the learned route, using the recorded maps for localization. Unlike classical T&R systems, our framework is suitable for application in dynamic environments, where the integrated obstacle avoidance scheme allows to detect and circumnavigate obstacles appearing on the reference path. In addition to the T&R approach, we present a second navigation system, integrating the point-cloud-based terrain assessment and global planning algorithms with ICP-based localization and mapping. Given a graph of point cloud maps—typically recorded in a manually controlled survey run—the framework enables navigation within the mapped area without being restricted to known routes. Motion control is implemented by a trajectory tracking controller with integrated real-time collision checking. Together with continuous map updates and frequent replanning of the global trajectory, these techniques enable autonomous navigation in nonplanar, nonstatic environments. Finally, we describe the characteristics of the mobile robot ARTOR, which was set up for the purpose of testing and evaluating the developed algorithms under realistic conditions. ARTOR consists of a six-wheeled, electrically powered base vehicle equipped with sensors, computers, and communication gear. The proposed autonomous navigation algorithms were integrated on the robot and tested in extensive field experiments, demonstrating reliable, GPS-independent navigation over large distances and under greatly varying environmental conditions, in unstructured off-road terrain, multi-level environments, and dynamic urban areas. Numéro de notice : 17367 Affiliation des auteurs : non IGN Thématique : IMAGERIE/INFORMATIQUE Nature : Thèse étrangère Note de thèse : PhD thesis : Sciences : ETH Zurich : 2016 En ligne : http://dx.doi.org/10.3929/ethz-a-010656081 Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=84243 Registration of aerial imagery and lidar data in desert areas using sand ridges / Na Li in Photogrammetric record, vol 30 n° 151 (September - November 2015)
[article]
Titre : Registration of aerial imagery and lidar data in desert areas using sand ridges Type de document : Article/Communication Auteurs : Na Li, Auteur ; Xianfeng Huang, Auteur ; Fan Zhang, Auteur ; Deren Li, Auteur Année de publication : 2015 Article en page(s) : pp 263 – 278 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] algorithme ICP
[Termes IGN] crète (ligne)
[Termes IGN] désert
[Termes IGN] données lidar
[Termes IGN] dune
[Termes IGN] extraction de traits caractéristiques
[Termes IGN] fusion de données multisource
[Termes IGN] image aérienne
[Termes IGN] recalage d'image
[Termes IGN] semis de pointsRésumé : (Auteur) Image registration is a prerequisite for multisource data fusion. In this paper the problem of registering aerial images with lidar point clouds in desert areas is addressed. Compared with urban areas, registration in desert regions is difficult due to the lack of man-made features which are typically used in traditional methods. However, sand ridges can be used as registration primitives. Firstly, sand-ridge information is extracted from both the aerial image and the lidar point cloud. Secondly, by extending the iterative closest point (ICP) approach, a perspective-ICP algorithm is proposed that achieves data registration through matching sand ridges. To automatically deal with outliers, an adaptive weighting strategy is adopted. Experiments and assessment using data from Dunhuang, Gobi Desert, China, demonstrate that the method can achieve efficient and reliable registration for desert areas. Numéro de notice : A2015-562 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1111/phor.12110 Date de publication en ligne : 27/07/2015 En ligne : https://doi.org/10.1111/phor.12110 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=77679
in Photogrammetric record > vol 30 n° 151 (September - November 2015) . - pp 263 – 278[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 106-2015031 RAB Revue Centre de documentation En réserve L003 Disponible Automatic registration of optical aerial imagery to a LiDAR point cloud for generation of city models / Bernard O. Abayowa in ISPRS Journal of photogrammetry and remote sensing, vol 106 (August 2015)
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Titre : Automatic registration of optical aerial imagery to a LiDAR point cloud for generation of city models Type de document : Article/Communication Auteurs : Bernard O. Abayowa, Auteur ; Alper Yilmaz, Auteur ; Russell C. Hardie, Auteur Année de publication : 2015 Article en page(s) : pp 68 - 81 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] algorithme ICP
[Termes IGN] corrélation croisée normalisée
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] image aérienne
[Termes IGN] image optique
[Termes IGN] méthode robuste
[Termes IGN] milieu urbain
[Termes IGN] modèle 3D de l'espace urbain
[Termes IGN] modèle numérique de surface
[Termes IGN] reconstruction 3D
[Termes IGN] scène
[Termes IGN] semis de points
[Termes IGN] superposition d'imagesRésumé : (auteur) This paper presents a framework for automatic registration of both the optical and 3D structural information extracted from oblique aerial imagery to a Light Detection and Ranging (LiDAR) point cloud without prior knowledge of an initial alignment. The framework employs a coarse to fine strategy in the estimation of the registration parameters. First, a dense 3D point cloud and the associated relative camera parameters are extracted from the optical aerial imagery using a state-of-the-art 3D reconstruction algorithm. Next, a digital surface model (DSM) is generated from both the LiDAR and the optical imagery-derived point clouds. Coarse registration parameters are then computed from salient features extracted from the LiDAR and optical imagery-derived DSMs. The registration parameters are further refined using the iterative closest point (ICP) algorithm to minimize global error between the registered point clouds. The novelty of the proposed approach is in the computation of salient features from the DSMs, and the selection of matching salient features using geometric invariants coupled with Normalized Cross Correlation (NCC) match validation. The feature extraction and matching process enables the automatic estimation of the coarse registration parameters required for initializing the fine registration process. The registration framework is tested on a simulated scene and aerial datasets acquired in real urban environments. Results demonstrates the robustness of the framework for registering optical and 3D structural information extracted from aerial imagery to a LiDAR point cloud, when co-existing initial registration parameters are unavailable. Numéro de notice : A2015-722 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2015.05.006 En ligne : https://doi.org/10.1016/j.isprsjprs.2015.05.006 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=78369
in ISPRS Journal of photogrammetry and remote sensing > vol 106 (August 2015) . - pp 68 - 81[article]A critical comparison among pansharpening algorithms / Gemine Vivone in IEEE Transactions on geoscience and remote sensing, vol 53 n° 5 (mai 2015)
[article]
Titre : A critical comparison among pansharpening algorithms Type de document : Article/Communication Auteurs : Gemine Vivone, Auteur ; Luciano Alparone, Auteur ; Jocelyn Chanussot, Auteur ; et al., Auteur Année de publication : 2015 Article en page(s) : pp 2565 - 2586 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] algorithme de fusion
[Termes IGN] analyse comparative
[Termes IGN] analyse multibande
[Termes IGN] analyse multirésolution
[Termes IGN] état de l'art
[Termes IGN] image à haute résolution
[Termes IGN] image multibande
[Termes IGN] image panchromatique
[Termes IGN] image satellite
[Termes IGN] Matlab
[Termes IGN] pansharpening (fusion d'images)
[Termes IGN] qualité des donnéesRésumé : (Auteur) Pansharpening aims at fusing a multispectral and a panchromatic image, featuring the result of the processing with the spectral resolution of the former and the spatial resolution of the latter. In the last decades, many algorithms addressing this task have been presented in the literature. However, the lack of universally recognized evaluation criteria, available image data sets for benchmarking, and standardized implementations of the algorithms makes a thorough evaluation and comparison of the different pansharpening techniques difficult to achieve. In this paper, the authors attempt to fill this gap by providing a critical description and extensive comparisons of some of the main state-of-the-art pansharpening methods. In greater details, several pansharpening algorithms belonging to the component substitution or multiresolution analysis families are considered. Such techniques are evaluated through the two main protocols for the assessment of pansharpening results, i.e., based on the full- and reduced-resolution validations. Five data sets acquired by different satellites allow for a detailed comparison of the algorithms, characterization of their performances with respect to the different instruments, and consistency of the two validation procedures. In addition, the implementation of all the pansharpening techniques considered in this paper and the framework used for running the simulations, comprising the two validation procedures and the main assessment indexes, are collected in a MATLAB toolbox that is made available to the community. Numéro de notice : A2015-523 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2014.2361734 En ligne : https://doi.org/10.1109/TGRS.2014.2361734 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=77534
in IEEE Transactions on geoscience and remote sensing > vol 53 n° 5 (mai 2015) . - pp 2565 - 2586[article]Réservation
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