Measurement of volumetric tomographic data, similar to other measurement techniques, suffers from several classes of artifacts, of which noise presence and the partial volume effect belong to the most prominent ones. These artifacts spoil data analysis and/or visualization, which may, for example in the case of medical imaging, lead to erroneous decisions with severe consequences. We propose a set of tools for region-based processing of volumetric data. Here, the basic entity is a spectrally homogeneous region instead of the traditional voxel. This provides for, on the one hand, higher robustness and, on the other hand, speeds up processing owing to many times smaller amount of elements to work with. Homogeneous regions are in our approach detected by the well-known segmentation by means of the watershed transform. In this paper we present algorithms for streamed computation of watershed transform, which allows for processing of very large data, region-based data smoothing and region merging based on the spectral distance. Further, we present an interactive tool for volume data segmentation and visualization which takes advantage of region hierarchies obtained by a hierarchical watershed transform.
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