Wolfgang Middelmann

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Automatically partitioning images into regions ('segmenta-tion') is challenging in terms of quality and performance. We propose a Minimum Spanning Tree-based algorithm with a novel graph-cutting heuristic, the usefulness of which is demonstrated by promising results obtained on standard images. In contrast to data-parallel schemes that divide images into(More)
This paper presents recent and planned activities in the area of computer aided detection and classification (CAD / CAC) of mine like objects (MLOs) at the FWG with assistance of FU-Berlin and FGAN-FOM. These investigations are intended to support software for the analysis of side scan sonar images by an operator and to contribute to automatic target(More)
In the last few years, unmixing of hyperspectral data has become of major importance. The high spectral resolution results in a loss of spatial resolution. Thus, spectra of edges and small objects are composed of mixtures of their neighboring materials. Due to the fact that supervised unmixing is impossible for extensive data sets, the unsupervised(More)
Surface representations in the shape of 3D triangle meshes of heterogeneous quality are readily generated using sensors such as laser scanners. We propose an algorithm to fuse two registered, i.e. aligned in rotation and translation, meshes while using only vertices contained in the input data. Mesh quality is determined for each input mesh depending on the(More)