PDEs for tensor image processing

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Abstract

Methods based on partial differential equations (PDEs) belong to those image processing techniques that can be extended in a particularly elegant way to tensor fields. In this survey chapter the most important PDEs for discontinuitypreserving denoising of tensor fields are reviewed such that the underlying design principles becomes evident. We consider isotropic and anisotropic diffusion filters and their corresponding variational methods, mean curvature motion, and selfsnakes. These filters preserve positive semidefiniteness of any positive semidefinite initial tensor field. Finally we discuss geodesic active contours for segmenting tensor fields. Experiments are presented that illustrate the behaviour of all these methods.

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Weickert, J., Feddern, C., Welk, M., Burgeth, B., & Brox, T. (2006). PDEs for tensor image processing. In Mathematics and Visualization (Vol. 0, pp. 399–414). Springer Heidelberg. https://doi.org/10.1007/3-540-31272-2_25

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