Uwe Soergel

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In contrast to conventional airborne multi-echo laser scanner systems, full-waveform (FW) lidar systems are able to record the entire emitted and backscattered signal of each laser pulse. Instead of clouds of individual 3D points, FW devices provide connected 1D profiles of the 3D scene, which contain more detailed and additional information about the(More)
— Modern space borne SAR sensors provide geometric resolution of one meter, airborne systems even higher. In data of this kind many features of urban objects become visible, which were beyond the scope of radar remote sensing only a few years ago. However, layover and occlusion issues inevitably arise in undulated terrain and urban areas because of the(More)
In contrast to conventional airborne multi-echo laser scanner systems, full-waveform (FW) lidar systems are able to record the entire emitted and backscattered signals of each laser pulse. Instead of clouds of individual 3D points, FW devices provide 1D profiles of the 3D scene, which allows gaining additional and more detailed observations of the(More)
We propose a context-based classification method for point clouds acquired by full waveform airborne laser scanners. As these devices provide a higher point density and additional information like echo width or type of return, an accurate distinction of several object classes is possible. However, especially in dense urban areas correct labelling is a(More)
Modern airborne synthetic aperture radar sensors provide high spatial resolution data. Experimental systems have even achieved deci-metre resolution. In such data, many features of urban objects can be identified, which are beyond what has been achieved by radar remote sensing before. An example for the new quality of the appearance of urban man-made(More)
Lidar waveforms are 1-D signals representing a train of echoes caused by reflections at different targets. Modeling these echoes with the appropriate parametric function is useful to retrieve information about the physical characteristics of the targets. This paper presents a new probabilistic model based upon a marked point process which reconstructs the(More)
The GESTALT-System is a stratified architecture for challenging computer vision tasks. This contribution focuses on the 3rd and 4th layer of it – the grouping and decision layers. As example application building recognition from high resolution SAR-Data is presented. The 3rd layer contains an assessment driven perceptual grouping process with anytime(More)
Today's airborne (Memphis, AeS-1, Ramses) and space borne (TerraSAR-X, CosmoSkyMed, Radarsat) SAR sensors provide very high resolution imagery independent of daylight and cloud coverage. Space borne systems achieve geometrical resolutions of down to one meter while airborne sensors are capable of acquiring images with sub metric resolution. In this kind of(More)