Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B1, 185-191, 2016
http://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLI-B1/185/2016/
doi:10.5194/isprs-archives-XLI-B1-185-2016
 
03 Jun 2016
ORIENTATION OF OBLIQUE AIRBORNE IMAGE SETS – EXPERIENCES FROM THE ISPRS/EUROSDR BENCHMARK ON MULTI-PLATFORM PHOTOGRAMMETRY
M. Gerke1, F. Nex1, F. Remondino2, K. Jacobsen3, J. Kremer4, W. Karel5, H. Hu6, and W. Ostrowski7 1University of Twente, Faculty of Geo-Information Science and Earth Observation (ITC), Department of Earth Observation Science, The Netherlands
23D Optical Metrology (3DOM) unit, Bruno Kessler Foundation (FBK), Trento, Italy
3Leibniz University Hannover, Institute of Photogrammetry and Geoinformation, Germany
4IGI mbH, Germany
5TU Wien, Faculty of Mathematics and Geoinformation, Department of Geodesy and Geoinformation, Vienna, Austria
6Southwest Jiaotong University, Faculty of Geosciences and Environmental Engineering, Chengdu, China
7Warsaw University of Technology, Faculty of Geodesy and Cartography, Department of Photogrammetry, Remote Sensing and Spatial Information Systems, Poland
Keywords: Orientation, Oblique, Tie point matching, Bundle adjustment Abstract. During the last decade the use of airborne multi camera systems increased significantly. The development in digital camera technology allows mounting several mid- or small-format cameras efficiently onto one platform and thus enables image capture under different angles. Those oblique images turn out to be interesting for a number of applications since lateral parts of elevated objects, like buildings or trees, are visible. However, occlusion or illumination differences might challenge image processing. From an image orientation point of view those multi-camera systems bring the advantage of a better ray intersection geometry compared to nadir-only image blocks. On the other hand, varying scale, occlusion and atmospheric influences which are difficult to model impose problems to the image matching and bundle adjustment tasks. In order to understand current limitations of image orientation approaches and the influence of different parameters such as image overlap or GCP distribution, a commonly available dataset was released. The originally captured data comprises of a state-of-the-art image block with very high overlap, but in the first stage of the so-called ISPRS/EUROSDR benchmark on multi-platform photogrammetry only a reduced set of images was released. In this paper some first results obtained with this dataset are presented. They refer to different aspects like tie point matching across the viewing directions, influence of the oblique images onto the bundle adjustment, the role of image overlap and GCP distribution. As far as the tie point matching is concerned we observed that matching of overlapping images pointing to the same cardinal direction, or between nadir and oblique views in general is quite successful. Due to the quite different perspective between images of different viewing directions the standard tie point matching, for instance based on interest points does not work well. How to address occlusion and ambiguities due to different views onto objects is clearly a non-solved research problem so far. In our experiments we also confirm that the obtainable height accuracy is better when all images are used in bundle block adjustment. This was also shown in other research before and is confirmed here. Not surprisingly, the large overlap of 80/80% provides much better object space accuracy – random errors seem to be about 2-3fold smaller compared to the 60/60% overlap. A comparison of different software approaches shows that newly emerged commercial packages, initially intended to work with small frame image blocks, do perform very well.
Conference paper (PDF, 892 KB)


Citation: Gerke, M., Nex, F., Remondino, F., Jacobsen, K., Kremer, J., Karel, W., Hu, H., and Ostrowski, W.: ORIENTATION OF OBLIQUE AIRBORNE IMAGE SETS – EXPERIENCES FROM THE ISPRS/EUROSDR BENCHMARK ON MULTI-PLATFORM PHOTOGRAMMETRY, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B1, 185-191, doi:10.5194/isprs-archives-XLI-B1-185-2016, 2016.

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