Noise robustness of persistent homology on greyscale images, across filtrations and signatures.
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ABSTRACT:
SUBMITTER: Turkes R
PROVIDER: S-EPMC8462731 | biostudies-literature | 2021
REPOSITORIES: biostudies-literature
Publications
Noise robustness of persistent homology on greyscale images, across filtrations and signatures.
Turkeš Renata R Nys Jannes J Verdonck Tim T Latré Steven S
PloS one 20210924 9
Topological data analysis is a recent and fast growing field that approaches the analysis of datasets using techniques from (algebraic) topology. Its main tool, persistent homology (PH), has seen a notable increase in applications in the last decade. Often cited as the most favourable property of PH and the main reason for practical success are the stability theorems that give theoretical results about noise robustness, since real data is typically contaminated with noise or measurement errors. ...[more]
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