A Framework for SAR-Optical Stereogrammetry over Urban Areas

Currently, numerous remote sensing satellites provide a huge volume of diverse earth observation data. As these data show different features regarding resolution, accuracy, coverage, and spectral imaging ability, fusion techniques are required to integrate the different properties of each sensor and produce useful information. For example, synthetic aperture radar (SAR) data can be fused with optical imagery to produce 3D information using stereogrammetric methods. The main focus of this study is to investigate the possibility of applying a stereogrammetry pipeline to very-high-resolution (VHR) SAR-optical image pairs. For this purpose, the applicability of semi-global matching is investigated in this unconventional multi-sensor setting. To support the image matching by reducing the search space and accelerating the identification of correct, reliable matches, the possibility of establishing an epipolarity constraint for VHR SAR-optical image pairs is investigated as well. In addition, it is shown that the absolute geolocation accuracy of VHR optical imagery with respect to VHR SAR imagery such as provided by TerraSAR-X can be improved by a multi-sensor block adjustment formulation based on rational polynomial coefficients. Finally, the feasibility of generating point clouds with a median accuracy of about 2m is demonstrated and confirms the potential of 3D reconstruction from SAR-optical image pairs over urban areas.Comment: This is the pre-acceptance version, to read the final version, please go to ISPRS Journal of Photogrammetry and Remote Sensing on ScienceDirec

Innovative strategies for 3D visualisation using photogrammetry and 3D scanning for mobile phones

3D model generation through Photogrammetry is a modern overlay of digital information representing real world objects in a virtual world. The immediate scope of this study aims at generating 3D models using imagery and overcoming the challenge of acquiring accurate 3D meshes. This research aims to achieve optimised ways to document raw 3D representations of real life objects and then converting them into retopologised, textured usable data through mobile phones. Augmented Reality (AR) is a projected combination of real and virtual objects. A lot of work is done to create market dependant AR applications so customers can view products before purchasing them. The need is to develop a product independent photogrammetry to AR pipeline which is freely available to create independent 3D Augmented models. Although for the particulars of this research paper, the aim would be to compare and analyse different open source SDK’s and libraries for developing optimised 3D Mesh using Photogrammetry/3D Scanning which will contribute as a main skeleton to the 3D-AR pipeline. Natural disasters, global political crisis, terrorist attacks and other catastrophes have led researchers worldwide to capture monuments using photogrammetry and laser scans. Some of these objects of “global importance” are processed by companies including CyArk (Cyber Archives) and UNESCO’s World Heritage Centre, who work against time to preserve these historical monuments, before they are damaged or in some cases completely destroyed. The need is to question the significance of preserving objects and monuments which might be of value locally to a city or town. What is done to preserve those objects? This research would develop pipelines for collecting and processing 3D data so the local communities could contribute towards restoring endangered sites and objects using their smartphones and making these objects available to be viewed in location based AR. There exist some companies which charge relatively large amounts of money for local scanning projects. This research would contribute as a non-profitable project which could be later used in school curriculums, visitor attractions and historical preservation organisations all over the globe at no cost. The scope isn’t limited to furniture, museums or marketing, but could be used for personal digital archiving as well. This research will capture and process virtual objects using Mobile Phones comparing methodologies used in Computer Vision design from data conversion on Mobile phones to 3D generation, texturing and retopologising. The outcomes of this research will be used as input for generating AR which is application independent of any industry or product