Uncertainty quantification in image segmentation using the Ambrosio-Tortorelli approximation of the Mumford-Shah energy

DOI10.1007/s10851-021-01034-2OpenAlexW3183923503MaRDI QIDQ2051547

Michael Hintermüller, Steven-Marian Stengl, Thomas M. Surowiec

Publication date: 24 November 2021

Published in: Journal of Mathematical Imaging and Vision (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10851-021-01034-2

zbMATH Keywords

numerical methodsimage segmentationMumford-Shah modelmeasurable selectionsAmbrosio-Tortorelli approximationerror propagation due to noisequantification of uncertainties

Mathematics Subject Classification ID

Computer science (68-XX) Information and communication theory, circuits (94-XX)

Cites Work

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