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Robust registration of aerial images and LiDAR data using spatial constraints and Gabor structural features / Bai Zhu in ISPRS Journal of photogrammetry and remote sensing, Vol 181 (November 2021)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > Vol 181 (November 2021) . - pp 129 - 147 Titre : Robust registration of aerial images and LiDAR data using spatial constraints and Gabor structural features Type de document : Article/Communication Auteurs : Bai Zhu, Auteur ; Yuanxin Ye, Auteur ; Liang Zhou, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 129 - 147 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] algorithme ICP [Termes IGN] correction géométrique [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] élément d'orientation externe [Termes IGN] enregistrement de données [Termes IGN] filtre de Gabor [Termes IGN] image aérienne [Termes IGN] recalage d'image [Termes IGN] semis de points [Termes IGN] SIFT (algorithme) [Termes IGN] structure-from-motion Résumé : (auteur) Co-registration of aerial imagery and Light Detection and Ranging (LiDAR) data is quite challenging because the different imaging mechanisms produce significant geometric and radiometric distortions between the two multimodal data sources. To address this problem, we propose a robust and effective coarse-to-fine registration method that is conducted in two stages utilizing spatial constraints and Gabor structural features. In the first stage, the LiDAR point cloud data is transformed into an intensity map that is used as the reference image. Then, coarse registration is completed by designing a partition-based Features from Accelerated Segment Test (FAST) operator to extract the uniformly distributed interest points in the aerial images and thereafter performing a local geometric correction based on the collinearity equations using the exterior orientation parameters (EoPs). The coarse registration aims to provide a reliable spatial geometry relationship for the subsequent fine registration and is designed to eliminate rotation and scale changes, as well as making only a few translation differences exist between the images. In the second stage, a novel feature descriptor called multi-Scale and multi-Directional Features of odd Gabor (SDFG) is first built to capture the multi-scale and multi-directional structural properties of the images. Then, the three-dimensional (3D) phase correlation (PC) of the SDFG descriptor is established to detect the control points (CPs) between the aerial and LiDAR intensity image in the frequency domain, where the image matching is accelerated by the 3D Fast Fourier Transform (FFT) technique. Finally, the obtained CPs not only are employed to refine the EoPs, but also are used to achieve the fine registration of the aerial images and LiDAR data. We conduct experiments to verify the robustness of the proposed registration method using three sets of aerial images and LiDAR data with different scene coverage. Experimental results show that the proposed method is robust to geometric distortions and radiometric changes. Moreover, it achieves the registration accuracy of less than 2 pixels for all cases, which outperforms the current four state-of-the-art methods, demonstrating its superior registration performance. Numéro de notice : A2021-773 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2021.09.010 Date de publication en ligne : 21/09/2021 En ligne : https://doi.org/10.1016/j.isprsjprs.2021.09.010 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98830 [article]

Camera orientation, calibration and inverse perspective with uncertainties: a Bayesian method applied to area estimation from diverse photographs / Grégoire Guillet in ISPRS Journal of photogrammetry and remote sensing, vol 159 (January 2020)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 159 (January 2020) . - pp 237 - 255 Titre : Camera orientation, calibration and inverse perspective with uncertainties: a Bayesian method applied to area estimation from diverse photographs Type de document : Article/Communication Auteurs : Grégoire Guillet, Auteur ; Thomas Guillet, Auteur ; Ludovic Ravanel, Auteur Année de publication : 2020 Article en page(s) : pp 237 - 255 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] ajustement de paramètres [Termes IGN] appariement d'images [Termes IGN] autocorrélation spatiale [Termes IGN] distorsion d'image [Termes IGN] estimation bayesienne [Termes IGN] étalonnage de chambre métrique [Termes IGN] figuration de la densité [Termes IGN] fonction inverse [Termes IGN] image 2D [Termes IGN] image aérienne [Termes IGN] incertitude géométrique [Termes IGN] longueur focale [Termes IGN] méthode de Monte-Carlo par chaînes de Markov [Termes IGN] modèle numérique de surface [Termes IGN] orientation externe [Termes IGN] photographie numérique [Termes IGN] vue 3D [Termes IGN] vue perspective Résumé : (Auteur) Large collections of images have become readily available through modern digital catalogs, from sources as diverse as historical photographs, aerial surveys, or user-contributed pictures. Exploiting the quantitative information present in such wide-ranging collections can greatly benefit studies that follow the evolution of landscape features over decades, such as measuring areas of glaciers to study their shrinking under climate change. However, many available images were taken with low-quality lenses and unknown camera parameters. Useful quantitative data may still be extracted, but it becomes important to both account for imperfect optics, and estimate the uncertainty of the derived quantities. In this paper, we present a method to address both these goals, and apply it to the estimation of the area of a landscape feature traced as a polygon on the image of interest. The technique is based on a Bayesian formulation of the camera calibration problem. First, the probability density function (PDF) of the unknown camera parameters is determined for the image, based on matches between 2D (image) and 3D (world) points together with any available prior information. In a second step, the posterior distribution of the feature area of interest is derived from the PDF of camera parameters. In this step, we also model systematic errors arising in the polygon tracing process, as well as uncertainties in the digital elevation model. The resulting area PDF therefore accounts for most sources of uncertainty. We present validation experiments, and show that the model produces accurate and consistent results. We also demonstrate that in some cases, accounting for optical lens distortions is crucial for accurate area determination with consumer-grade lenses. The technique can be applied to many other types of quantitative features to be extracted from photographs when careful error estimation is important. Numéro de notice : A2020-015 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2019.11.013 Date de publication en ligne : 02/12/2019 En ligne : https://doi.org/10.1016/j.isprsjprs.2019.11.013 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94404 [article]

Exemplaires(3)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
081-2020011	RAB	Revue	Centre de documentation	En réserve L003	Disponible
081-2020013	DEP-RECP	Revue	LASTIG	Dépôt en unité	Exclu du prêt
081-2020012	DEP-RECF	Revue	Nancy	Dépôt en unité	Exclu du prêt

Robust external calibration of terrestrial laser scanner and digital camera for structural monitoring / Mohammad Omidalizarandi in Journal of applied geodesy, vol 13 n° 2 (April 2019)  

Public [article]  inJournal of applied geodesy > vol 13 n° 2 (April 2019) . - pp 105 - 130 Titre : Robust external calibration of terrestrial laser scanner and digital camera for structural monitoring Type de document : Article/Communication Auteurs : Mohammad Omidalizarandi, Auteur ; Boris Kargoll, Auteur ; Jens-André Paffenholz, Auteur ; Ingo Neumann, Auteur Année de publication : 2019 Article en page(s) : pp 105 - 130 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques [Termes IGN] algorithme espérance-maximisation [Termes IGN] déformation de la croute terrestre [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] élément d'orientation externe [Termes IGN] méthode des moindres carrés [Termes IGN] modèle de Gauss-Helmert [Termes IGN] modèle de Gauss-Markov [Termes IGN] orthoimage [Termes IGN] semis de points Résumé : (Auteur) In the last two decades, the integration of a terrestrial laser scanner (TLS) and digital photogrammetry, besides other sensors integration, has received considerable attention for deformation monitoring of natural or man-made structures. Typically, a TLS is used for an area-based deformation analysis. A high-resolution digital camera may be attached on top of the TLS to increase the accuracy and completeness of deformation analysis by optimally combining points or line features extracted both from three-dimensional (3D) point clouds and captured images at different epochs of time. For this purpose, the external calibration parameters between the TLS and digital camera needs to be determined precisely. The camera calibration and internal TLS calibration are commonly carried out in advance in the laboratory environments. The focus of this research is to highly accurately and robustly estimate the external calibration parameters between the fused sensors using signalised target points. The observables are the image measurements, the 3D point clouds, and the horizontal angle reading of a TLS. In addition, laser tracker observations are used for the purpose of validation. The functional models are determined based on the space resection in photogrammetry using the collinearity condition equations, the 3D Helmert transformation and the constraint equation, which are solved in a rigorous bundle adjustment procedure. Three different adjustment procedures are developed and implemented: (1) an expectation maximization (EM) algorithm to solve a Gauss-Helmert model (GHM) with grouped t-distributed random deviations, (2) a novel EM algorithm to solve a corresponding quasi-Gauss-Markov model (qGMM) with t-distributed pseudo-misclosures, and (3) a classical least-squares procedure to solve the GHM with variance components and outlier removal. The comparison of the results demonstrates the precise, reliable, accurate and robust estimation of the parameters in particular by the second and third procedures in comparison to the first one. In addition, the results show that the second procedure is computationally more efficient than the other two. Numéro de notice : A2019-145 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1515/jag-2018-0038 Date de publication en ligne : 02/02/2019 En ligne : https://doi.org/10.1515/jag-2018-0038 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92472 [article]

Advancement of close range photogrammetry with a portable panoramic image mapping system (PPIMS) / Yung-Chuan Chen in Photogrammetric record, vol 33 n° 162 (June 2018)  

Public [article]  inPhotogrammetric record > vol 33 n° 162 (June 2018) . - pp 196 - 216 Titre : Advancement of close range photogrammetry with a portable panoramic image mapping system (PPIMS) Type de document : Article/Communication Auteurs : Yung-Chuan Chen, Auteur ; Yi-Hsing Tseng, Auteur Année de publication : 2018 Article en page(s) : pp 196 - 216 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Acquisition d'image(s) et de donnée(s) [Termes IGN] caméra numérique [Termes IGN] compensation par faisceaux [Termes IGN] élément d'orientation externe [Termes IGN] étalonnage de capteur (imagerie) [Termes IGN] image panoramique [Termes IGN] positionnement par GPS [Termes IGN] système de numérisation mobile Résumé : (Auteur) Mobile mapping technologies have contributed to close range photogrammetry becoming an efficient method for a wide range of applications over the last two decades. Advancements have included the integration of multi‐camera images and georeferencing data collected with a mobile mapping system (MMS). This paper proposes the use of a portable panoramic image mapping system (PPIMS), which is a specially designed platform equipped with eight cameras to capture panoramic images and a global navigation satellite system (GNSS) receiver (or a prism reflector) for positioning. A rigorous calibration procedure is developed for PPIMS, as well as a bundle adjustment method to solve for the platform exterior orientation parameters (EOPs) which then allows the image EOPs to be calculated. Experimental results demonstrate that PPIMS mapping accuracy can be better than 13 mm, making it comparable with traditional methods but much more efficient in the measuring process. Numéro de notice : A2018-224 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/phor.12236 Date de publication en ligne : 10/04/2018 En ligne : https://doi.org/10.1111/phor.12236 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90044 [article]

Progressive registration of image features and 3D vector lines for orientation modelling / Wen-Chi Chang in Photogrammetric record, vol 33 n° 161 (March 2018)  

Public [article]  inPhotogrammetric record > vol 33 n° 161 (March 2018) . - pp 66 - 85 Titre : Progressive registration of image features and 3D vector lines for orientation modelling Type de document : Article/Communication Auteurs : Wen-Chi Chang, Auteur ; Ching-Hui Hung, Auteur ; Liang-Chien Chen, Auteur Année de publication : 2018 Article en page(s) : pp 66 - 85 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Photogrammétrie numérique [Termes IGN] arc [Termes IGN] élément d'orientation externe [Termes IGN] ligne (géométrie) [Termes IGN] superposition d'images Résumé : (Auteur) This paper proposes a progressive method to register image features and three‐dimensional (3D) vector lines for image orientation modelling. Directed at images acquired with an approximate direct‐georeferencing capability, this study employed 3D vector lines extracted from a geographical information system (GIS) database as ground control. The major work comprises three steps: (1) straight lines were parameterised and applied as control in the collinearity condition equations to determine exterior orientation parameters (EOPs); (2) coarse registration employed quadrangle features formed from straight lines to modify the initial EOPs; and (3) a two‐step fine registration, initially involving all line‐feature candidates, followed by the selection of the most probable one from neighbouring lines. Experimental results indicate that the proposed methods can achieve an accuracy of about 2 pixels (close to the accuracy of the employed GIS database) from initial EOPs with more than 800 pixel errors. Accuracy improvements in each step of the proposed coarse‐to‐fine registration are also demonstrated. Numéro de notice : A2018-220 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/phor.12227 Date de publication en ligne : 12/02/2018 En ligne : https://doi.org/10.1111/phor.12227 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90040 [article]

Shipborne over- and under-water integrated mobile mapping system and its seamless integration of point clouds / Bo Shi in Marine geodesy, vol 40 n° 2-3 (March - June 2017)  

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Exterior orientation revisited : a robust method based on lq -norm / Jiayuan Li in Photogrammetric Engineering & Remote Sensing, PERS, vol 83 n° 1 (January 2017)  

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Automatic orthorectification of high-resolution optical satellite images using vector roads / Aleš Marsetič in IEEE Transactions on geoscience and remote sensing, vol 53 n° 11 (November 2015)  

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Locating control points in aerial images with a multi-scale approach based on terrestrial image patches / Adilson Berveglieri in Photogrammetric record, vol 30 n° 149 (March - May 2015)  

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Direct linear transformation from comparator coordinates into object space coordinates in close-range photogrammetry : An interim report on a study sponsored by the National Science Foundation as a part of research grant GK-11655 / Y.I. Abdel-Aziz in Photogrammetric Engineering & Remote Sensing, PERS, vol 81 n° 2 (February 2015)  

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Exterior orientation of hyperspectral frame images collected with UAV for forest applications / Adilson Berveglieri (2015)  

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Generation of true ortho-images based on virtual worlds: Learning aspects / Eduardo J. Piatti in Photogrammetric record, vol 29 n° 145 (March - May 2014)  

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In-orbit geometric calibration and validation of ZY-3 linear array sensors / Guo Zhang in Photogrammetric record, vol 29 n° 145 (March - May 2014)  

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Semi-automated registration of close-range hyperspectral scans using oriented digital camera imagery and a 3D model / Alessandra A. Sima in Photogrammetric record, vol 29 n° 145 (March - May 2014)  

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Subseasonal GNSS positioning errors / Jim Ray in Geophysical research letters, vol 40 n° 22 (November 2013)    

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