@misc{WelkBreussSridhar, author = {Welk, Martin and Breuß, Michael and Sridhar, Vivek}, title = {Matrix Morphology with Extremum Principle}, series = {Mathematical Morphology and Its Applications to Signal and Image Processing : 14th International Symposium, ISMM 2019, Saarbr{\"u}cken, Germany, July 8-10, 2019, Proceedings}, journal = {Mathematical Morphology and Its Applications to Signal and Image Processing : 14th International Symposium, ISMM 2019, Saarbr{\"u}cken, Germany, July 8-10, 2019, Proceedings}, publisher = {Springer}, address = {Cham}, isbn = {978-3-030-20866-0}, doi = {10.1007/978-3-030-20867-7_14}, pages = {177 -- 188}, abstract = {The fundamental operations of mathematical morphology are dilation and erosion. In previous works, these operations have been generalised in a discrete setting to work with fields of symmetric matrices, and also corresponding methods based on partial differential equations have been constructed. However, the existing methods for dilation and erosion in the matrix-valued setting are not overall satisfying. By construction they may violate a discrete extremum principle, which means that results may leave the convex hull of the matrices that participate in the computation. This may not be desirable from the theoretical point of view, as the corresponding property is fundamental for discrete and continuous-scale formulations of dilation and erosion in the scalar setting. Moreover, if such a principle could be established in the matrix-valued framework, this would help to make computed solutions more interpretable. In our paper we address this issue. We show how to construct a method for matrix-valued morphological dilation and erosion that satisfies a discrete extremum principle. We validate the construction by showing experimental results on synthetic data as well as colour images, as the latter can be cast as fields of symmetric matrices.}, language = {en} }