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Structure-from-motion-derived digital surface models from historical aerial photographs: A new 3D application for coastal dune monitoring / Edoardo Grottoli in Remote sensing, vol 13 n° 1 (January 2021)  

Public [article]  inRemote sensing > vol 13 n° 1 (January 2021) . - n° 95 Titre : Structure-from-motion-derived digital surface models from historical aerial photographs: A new 3D application for coastal dune monitoring Type de document : Article/Communication Auteurs : Edoardo Grottoli, Auteur ; Mélanie Biausque, Auteur ; David Rogers, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 95 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques [Termes IGN] analyse diachronique [Termes IGN] carte de profondeur [Termes IGN] données lidar [Termes IGN] dune [Termes IGN] érosion côtière [Termes IGN] filtrage de points [Termes IGN] image captée par drone [Termes IGN] image numérisée [Termes IGN] modèle numérique de surface [Termes IGN] reconstruction 3D [Termes IGN] semis de points [Termes IGN] structure-from-motion [Termes IGN] surveillance du littoral Résumé : (auteur) Recent advances in structure-from-motion (SfM) techniques have proliferated the use of unmanned aerial vehicles (UAVs) in the monitoring of coastal landform changes, particularly when applied in the reconstruction of 3D surface models from historical aerial photographs. Here, we explore a number of depth map filtering and point cloud cleaning methods using the commercial software Agisoft Metashape Pro to determine the optimal methodology to build reliable digital surface models (DSMs). Twelve different aerial photography-derived DSMs are validated and compared against light detection and ranging (LiDAR)- and UAV-derived DSMs of a vegetated coastal dune system that has undergone several decades of coastline retreat. The different studied methods showed an average vertical error (root mean square error, RMSE) of approximately 1 m, with the best method resulting in an error value of 0.93 m. In our case, the best method resulted from the removal of confidence values in the range of 0–3 from the dense point cloud (DPC), with no filter applied to the depth maps. Differences among the methods examined were associated with the reconstruction of the dune slipface. The application of the modern SfM methodology to the analysis of historical aerial (vertical) photography is a novel (and reliable) new approach that can be used to better quantify coastal dune volume changes. DSMs derived from suitable historical aerial photographs, therefore, represent dependable sources of 3D data that can be used to better analyse long-term geomorphic changes in coastal dune areas that have undergone retreat. Numéro de notice : A2021-079 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/rs13010095 date de publication en ligne : 30/12/2020 En ligne : https://doi.org/10.3390/rs13010095 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96821 [article]

Dense stereo matching strategy for oblique images that considers the plane directions in urban areas / Jianchen Liu in IEEE Transactions on geoscience and remote sensing, vol 58 n° 7 (July 2020)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 58 n° 7 (July 2020) . - pp 5109 - 5116 Titre : Dense stereo matching strategy for oblique images that considers the plane directions in urban areas Type de document : Article/Communication Auteurs : Jianchen Liu, Auteur ; Linjing Zhang, Auteur ; Zhen Wang, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 5109 - 5116 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] algorithme d'appariement [Termes IGN] appariement d'images [Termes IGN] appariement semi-global [Termes IGN] bati [Termes IGN] carte de profondeur [Termes IGN] corrélation épipolaire dense [Termes IGN] distorsion d'image [Termes IGN] erreur moyenne quadratique [Termes IGN] image oblique [Termes IGN] perspective [Termes IGN] planéité [Termes IGN] zone urbaine Résumé : (auteur) The perspective distortion of oblique images has a substantial impact on dense matching, i.e., it reduces the matching precision. In this article, a strategy of dense matching in which the object plane direction is considered is proposed. According to many regular planes in urban areas, epipolar rectification with minimum distortions relative to the selected reference planes can be generated. The matching results of epipolar images relative to various reference planes are weighted and fused into a single depth map, which is a better matching result. The experimental results demonstrate that the perspective distortion has a substantial influence on the dense matching performance. The root-mean-square error (RMSE) of the flatness for horizontal objects is increased by approximately 30%, and the RMSE of the flatness for façades is increased by approximately 40%. Hence, the proposed matching strategy, in which the object plane is considered, can effectively improve the matching results. Numéro de notice : A2020-394 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2020.2972312 date de publication en ligne : 20/02/2020 En ligne : https://doi.org/10.1109/TGRS.2020.2972312 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95390 [article]

Enhanced 3D mapping with an RGB-D sensor via integration of depth measurements and image sequences / Bo Wu in Photogrammetric Engineering & Remote Sensing, PERS, vol 85 n° 9 (September 2019)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 85 n° 9 (September 2019) . - pp 633 - 642 Titre : Enhanced 3D mapping with an RGB-D sensor via integration of depth measurements and image sequences Type de document : Article/Communication Auteurs : Bo Wu, Auteur ; Xuming Ge, Auteur ; Linfu Xie, Auteur ; Wu Chen, Auteur Année de publication : 2019 Article en page(s) : pp 633 - 642 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] carte d'intérieur [Termes IGN] carte de profondeur [Termes IGN] cartographie 3D [Termes IGN] Cartographie et localisation simultanées [Termes IGN] données localisées 3D [Termes IGN] état de l'art [Termes IGN] image RVB [Termes IGN] intégration de données [Termes IGN] modélisation 3D [Termes IGN] semis de points [Termes IGN] séquence d'images [Termes IGN] structure-from-motion Résumé : (Auteur) State-of-the-art visual simultaneous localization and mapping (SLAM) techniques greatly facilitate three-dimensional (3D) mapping and modeling with the use of low-cost red-green-blue-depth (RGB-D) sensors. However, the effective range of such sensors is limited due to the working range of the infra-red (IR) camera, which provides depth information, and thus the practicability of such sensors in 3D mapping and modeling is limited. To address this limitation, we present a novel solution for enhanced 3D mapping using a low-cost RGB-D sensor. We carry out state-of-the-art visual SLAM to obtain 3D point clouds within the mapping range of the RGB-D sensor and implement an improved structure-from-motion (SfM) on the collected RGB image sequences with additional constraints from the depth information to produce image-based 3D point clouds. We then develop a feature-based scale-adaptive registration to merge the gained point clouds to further generate enhanced and extended 3D mapping results. We use two challenging test sites to examine the proposed method. At these two sites, the coverage of both generated 3D models increases by more than 50% with the proposed solution. Moreover, the proposed solution achieves a geometric accuracy of about 1% in a measurement range of about 20 m. These positive experimental results not only demonstrate the feasibility and practicality of the proposed solution but also its potential. Numéro de notice : A2019-415 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.85.9.633 date de publication en ligne : 01/09/2019 En ligne : https://doi.org/10.14358/PERS.85.9.633 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93542 [article]

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Improved camera distortion correction and depth estimation for lenslet light field camera / Changkun Yang in Photogrammetric Engineering & Remote Sensing, PERS, vol 85 n° 3 (March 2019)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 85 n° 3 (March 2019) . - pp 197 - 208 Titre : Improved camera distortion correction and depth estimation for lenslet light field camera Type de document : Article/Communication Auteurs : Changkun Yang, Auteur ; Zhaoqin Liu, Auteur ; Kaichang Di, Auteur ; et al., Auteur Année de publication : 2019 Article en page(s) : pp 197 - 208 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Acquisition d'image(s) et de donnée(s) [Termes IGN] carte de profondeur [Termes IGN] chambre de prise de vue numérique [Termes IGN] correction géométrique [Termes IGN] distorsion d'image [Termes IGN] modèle géométrique de prise de vue Résumé : (Auteur) A light field camera can capture both radiance and angular information, providing a novel solution for depth estimation. The paper proposes two improved methods including distortion model optimization and depth estimation refinement for a lenslet light field camera. For distortion model optimization, a novel 14-parameter distortion model that involves sub-aperture images generation is applied to correct the light field camera images. For depth estimation refinement, an algorithm reducing the high influence of outliers on depth estimation in weak texture regions is proposed based on multi-view stereo matching using the cost volume. Experimental results show the projection error has decreased by about 30% and the depth root-mean-squared error on real world images has decreased by about 42% with our distortion correction method and depth estimation method compared with state of art algorithms. It verifies the correctness and effectiveness of our proposed methods and show significant improvement on accuracy of depth map estimation. Numéro de notice : A2019-148 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.85.3.197 date de publication en ligne : 01/03/2019 En ligne : https://doi.org/10.14358/PERS.85.3.197 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92477 [article]

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Entropy in image analysis / Amelia Carolina Sparavigna (2019)  

Public Titre : Entropy in image analysis Type de document : Monographie Auteurs : Amelia Carolina Sparavigna, Auteur Editeur : Bâle [Suisse] : Multidisciplinary Digital Publishing Institute MDPI Année de publication : 2019 Importance : 456 p. Format : 17 x 23 cm ISBN/ISSN/EAN : 978-3-03921-093-0 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] carte de profondeur [Termes IGN] classification par forêts aléatoires [Termes IGN] cryptage [Termes IGN] entropie [Termes IGN] extraction de traits caractéristiques [Termes IGN] fusion d'images [Termes IGN] image infrarouge [Termes IGN] optimisation (mathématiques) [Termes IGN] recherche d'image basée sur le contenu [Termes IGN] segmentation d'image [Termes IGN] texture Résumé : (éditeur) Image analysis is a fundamental task for extracting information from images acquired across a range of different devices. Since reliable quantitative results are requested, image analysis requires highly sophisticated numerical and analytical methods--particularly for applications in medicine, security, and remote sensing, where the results of the processing may consist of vitally important data. The contributions to this book provide a good overview of the most important demands and solutions concerning this research area. In particular, the reader will find image analysis applied for feature extraction, encryption and decryption of data, color segmentation, and in the support new technologies. In all the contributions, entropy plays a pivotal role. Note de contenu : 1- An adaptive weight method for image retrieval based multi-feature fusion 2- A New Image Encryption 3- Algorithm Based on Chaos and Secure Hash SHA-256 4- Video summarization for sign languages using the median of entropy of mean frames method 5- Encryption algorithm of multiple-image using mixed image elements and two dimensional chaotic economic map 6- Improved cryptanalysis and enhancements of an image encryption scheme using combined 1D chaotic maps 7- Blind image quality assessment of natural scenes based on entropy differences in the DCT domain 8- A novel multi-exposure image fusion method based on adaptive patch structure 9- An image encryption algorithm based on time-delay and random insertion 10- Uncertainty assessment of hyperspectral image classification: Deep learning vs. random forest 11- Reconstruction of PET images using cross-entropy and field of experts 12- Objective 3D printed surface quality assessment based on entropy of depth maps 13- Non rigid medical image registration using an information theoretic measure based on arimoto entropy with gradient distributions 14- Study on asphalt pavement surface texture degradation using 3-D image processing techniques and entropy theory 15- Entropy and contrast enhancement of infrared thermal images using the multiscale top-hat transform 16- Breaking an image encryption algorithm based on DNA encoding and spatiotemporal chaos Numéro de notice : 28553 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Monographie DOI : 10.3390/books978-3-03921-093-0 En ligne : https://doi.org/10.3390/books978-3-03921-093-0 Format de la ressource électronique : url Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97428

Estimation de profondeur à partir d'images monoculaires par apprentissage profond / Michel Moukari (2019)  

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Geometric camera pose refinement with learned depth maps / Nathan Piasco (2019)  

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Learning scene geometry for visual localization in challenging conditions / Nathan Piasco (2019)    

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Perspective-n-learned-point: pose estimation from relative depth / Nathan Piasco (2019)    

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Vision-based localization with discriminative features from heterogeneous visual data / Nathan Piasco (2019)  

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EMVS : Event-based Multi-View Stereo : 3D reconstruction with an event camera in real-time / Henri Rebecq in International journal of computer vision, vol 126 n° 12 (December 2018)  

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3D reconstruction from multi-view VHR-satellite images in MicMac / Ewelina Rupnik in ISPRS Journal of photogrammetry and remote sensing, vol 139 (May 2018)  

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Global, dense multiscale reconstruction for a billion points / Benjamin Ummenhofer in International journal of computer vision, vol 125 n° 1-3 (December 2017)  

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Efficient edge-aware surface mesh reconstruction for urban scenes / András Bódis-Szomorú in Computer Vision and image understanding, vol 157 (April 2017)  

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Generalizing the prediction sum of squares statistic and formula, application to linear fractional image warp and surface fitting / Adrien Bartoli in International journal of computer vision, vol 122 n° 1 (March 2017)  

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