On the (Un)Suitability of Strict Feature Definitions for Uncertain Data
2014 (English)In: Scientific Visualization: Uncertainty, Multifield, Biomedical, and Scalable Visualization / [ed] Chen, M.; Hagen, H.; Hansen, C.; Johnson, C.; Kaufmann, A., Springer , 2014Chapter in book (Other academic)Text
We discuss strategies to successfully work with strict feature definitions such as topology in the presence of noisy/uncertain data. To that end, we review previous work from the literature and identify three strategies: the development of fuzzy analogs to strict feature definitions, the aggregation of features, and the filtering of features. Regarding the latter, we will present a detailed discussion of filtering ridges/valleys and topological structures.
Place, publisher, year, edition, pages
Springer , 2014.
Research subject Computer Science; SRA - E-Science (SeRC)
IdentifiersURN: urn:nbn:se:kth:diva-184835OAI: oai:DiVA.org:kth-184835DiVA: diva2:916906
QC 201604052016-04-052016-04-052016-04-05Bibliographically approved