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Image processing and computer vision have robust methods for feature extraction and the computation of derivatives of scalar fields. Furthermore, interpolation and the effects of applying a filter can be analyzed in detail and can be advantages when applying these methods to vector fields to obtain a solid theoretical basis for feature extraction. We(More)
The goal of this paper is to transfer image processing to vector fields and flow visualization by defining a suitable convolution operation. For this, a multiplication of vectors is necessary. Clifford algebra provides such a multiplication of vectors. So we define a Clifford convolution on vector fields with uniform grids. The Clifford con-volution works(More)
Using topology for feature analysis in flow fields faces several problems. First of all, not all features can be detected using topology based methods. Second, while in flow feature analysis the user is interested in a quantification of feature parameters like position, size, shape, radial velocity and other parameters of feature models, many of these(More)
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