A multi-parameter persistence framework for mathematical morphology.
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ABSTRACT:
SUBMITTER: Chung YM
PROVIDER: S-EPMC9019063 | biostudies-literature | 2022 Apr
REPOSITORIES: biostudies-literature
Publications
A multi-parameter persistence framework for mathematical morphology.
Chung Yu-Min YM Day Sarah S Hu Chuan-Shen CS
Scientific reports 20220419 1
The field of mathematical morphology offers well-studied techniques for image processing and is applicable for studies ranging from materials science to ecological pattern formation. In this work, we view morphological operations through the lens of persistent homology, a tool at the heart of the field of topological data analysis. We demonstrate that morphological operations naturally form a multiparameter filtration and that persistent homology can then be used to extract information about bot ...[more]
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