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Development of a SGM-based multi-view reconstruction framework for aerial imagery / Mathias Rothermel (2016)  

Public Titre : Development of a SGM-based multi-view reconstruction framework for aerial imagery Type de document : Thèse/HDR Auteurs : Mathias Rothermel, Auteur Editeur : Munich : Bayerische Akademie der Wissenschaften Année de publication : 2016 Autre Editeur : Stuttgart : University of Stuttgart Collection : DGK - C, ISSN 0065-5325 num. 792 Importance : 115 p. ISBN/ISSN/EAN : 978-3-7696-5204-8 Note générale : bibliographie PhD dissertation Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] appariement d'images [Termes IGN] carte de profondeur [Termes IGN] image aérienne [Termes IGN] image aérienne oblique [Termes IGN] image oblique [Termes IGN] modèle numérique de surface [Termes IGN] pas d'échantillonnage au sol [Termes IGN] reconstruction 3D [Termes IGN] scène [Termes IGN] SURE Résumé : (auteur) Advances in the technology of digital airborne camera systems allow for the observation of surfaces with sampling rates in the range of a few centimeters. In combination with novel matching approaches, which estimate depth information for virtually every pixel, surface reconstructions of impressive density and precision can be generated. Therefore, image based surface generation meanwhile is a serious alternative to LiDAR based data collection for many applications. Surface models serve as primary base for geographic products as for example map creation, production of true-ortho photos or visualization purposes within the framework of virtual globes. The goal of the presented theses is the development of a framework for the fully automatic generation of 3D surface models based on aerial images - both standard nadir as well as oblique views. This comprises several challenges. On the one hand dimensions of aerial imagery is consider-able and the extend of the areas to be reconstructed can encompass whole countries. Beside scalability of methods this also requires decent processing times and efficient handling of the given hardware resources. Moreover, beside high precision requirements, a high degree of automation has to be guaranteed to limit manual interaction as much as possible. Due to the advantages of scalability, a stereo method is utilized in the presented thesis. The approach for dense stereo is based on an adapted version of the semi global matching (SGM) algorithm. Following a hierarchical approach corresponding image regions and meaningful disparity search ranges are identified. It will be verified that, dependent on undulations of the scene, time and memory demands can be reduced significantly, by up to 90% within some of the conducted tests. This enables the processing of aerial datasets on standard desktop machines in reasonable times even for large fields of depth. Stereo approaches generate disparity or depth maps, in which redundant depth information is available. To exploit this redundancy, a method for the refinement of stereo correspondences is proposed. Thereby redundant observations across stereo models are identified, checked for geometric consistency and their reprojection error is minimized. This way outliers are removed and precision of depth estimates is improved. In order to generate consistent surfaces, two algorithms for depth map fusion were developed. The first fusion strategy aims for the generation of 2.5D height models, also known as digital surface models (DSM). The proposed method improves existing methods regarding quality in areas of depth discontinuities, for example at roof edges. Utilizing benchmarks designed for the evaluation of image based DSM generation we show that the developed approaches favorably compare to state-of-the-art algorithms and that height precisions of few GSDs can be achieved. Furthermore, methods for the derivation of meshes based on DSM data are discussed. The fusion of depth maps for 3D scenes, as e.g. frequently required during evaluation of high resolution oblique aerial images in complex urban environments, demands for a different approach since scenes can in general riot be represented as height fields. Moreover, depths across depth maps possess varying precision and sampling rates due to variances in image scale, errors in orientation and other effects. Within this thesis a median-based fusion methodology is proposed. By using geometry-adaptive triangulation of depth maps depth-wise normal arc extracted and, along the point coordinates are filtered and fused using tree structures. The outputs of this method are oriented points which then can be used to generate meshes. Precision and density of the method will be evaluated using established multi-view benchmarks. Beside the capability to process close range datasets, results for large oblique airborne data sets will be presented. The report closes with a summary, discussion of limitations and perspectives regarding improvements and enhancements. The implemented algorithms are core elements of the commercial software package SURE, which is freely available for scientific purposes. Numéro de notice : 17371 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Thèse étrangère Note de thèse : Dissertation : Photogrammetrische Bildverarbeitung : Stuttgart : 2016 En ligne : https://elib.uni-stuttgart.de/handle/11682/9067 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=84247