Abstract
Abstract. Many remote sensing applications demand for a fast and efficient way of generating orthophoto maps from raw aerial images. One prerequisite is direct georeferencing, which allows to geolocate aerial images to their geographic position on the earth’s surface. But this is only half the story. When dealing with a large quantity of highly overlapping images, a major challenge is to select the most suitable image parts in order to generate seamless aerial maps of the captured area. This paper proposes a method that quickly determines such an optimal (rectangular) section for each single aerial image, which in turn can be used for generating seamless aerial maps. Its key approach is to clip aerial images depending on their geometric intersections with a terrain elevation model of the captured area, which is why we call it terrain aware image clipping (TAC). The method has a modest computational footprint and is therefore applicable even for rather limited embedded vision systems. It can be applied for both, real-time aerial mapping applications using data links as well as for rapid map generation right after landing without any postprocessing step. Referring to real-time applications, this method also minimizes transmission of redundant image data. The proposed method has already been demonstrated in several search-and-rescue scenarios and real-time mapping applications using a broadband data link and diffent kinds of camera and carrier systems. Moreover, a patent for this technology is pending.
Highlights
AND MOTIVATIONGenerating digital aerial maps, respectively orthophoto mosaics from aerial images is a common but usually complex and time consuming process
There is a wide range of established commercial products that provide tools for generating maps and other geospatial data products, such as true orthophoto mosaics (TOM), digital surface models (DSM), point clouds or 3D meshes from aerial imagery (ESRI Inc., California, 2018b, ESRI Inc., California, 2018a, PrecisionHawk Inc., North Carolina, 2018, CGI Systems GmbH, Germany, 2018, nFrames GmbH, Germany, 2018, Vexcel Imaging GmbH, Austria, 2018)
When it comes to mapping or image mosaicing one can distinguish two different approaches: stitching methods that work solely in the texture domain and photogrammetric methods that work in the spatial domain exploiting the imaging geometry (Ghosh and Kaabouch, 2016, Tjahjadi et al, 2017)
Summary
Generating digital aerial maps, respectively (true) orthophoto mosaics from aerial images is a common but usually complex and time consuming process. The necessary image overlap may be small or large, depending on flight speed, flight altitude, terrain height, camera’s field of view and trigger rate. When it comes to render maps by using projective mapping techniques, a key issue is the selection of suitable image parts of the overlapping aerial images. An optimal image area selection provides a minimum of redundant image pixels to be rendered while keeping a seamless coverage of the whole captured area. Such an optimal image area selection could increase the visualization performance, since redundant image areas can be excluded from processing or render stages Such a selection represents a minimum of relevant image data of the captured area. A good image area selection may increase the overall quality and accuracy of the generated aerial maps by selecting only the best image areas, e.g. in terms of radiometric or geometric properties or a preferred angle of view
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