001     1047562
005     20251128084740.0
020 _ _ |a 978-3-032-09543-5 (print)
020 _ _ |a 978-3-032-09544-2 (electronic)
024 7 _ |a 10.1007/978-3-032-09544-2_29
|2 doi
024 7 _ |a 0302-9743
|2 ISSN
024 7 _ |a 1611-3349
|2 ISSN
037 _ _ |a FZJ-2025-04388
041 _ _ |a English
100 1 _ |a Welk, Martin
|0 0000-0002-6268-7050
|b 0
|e Corresponding author
111 2 _ |a Discrete Geometry and Mathematical Morphology
|g DGMM 2025
|c Groningen
|d 2025-11-03 - 2025-11-06
|w Netherlands
245 _ _ |a Morphological PDEs with Rotationally Invariant Space-Fractional Derivatives
260 _ _ |a Cham
|c 2025
|b Springer Nature Switzerland
295 1 0 |a Discrete Geometry and Mathematical Morphology
300 _ _ |a 401 - 414
336 7 _ |a CONFERENCE_PAPER
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336 7 _ |a Conference Paper
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336 7 _ |a INPROCEEDINGS
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336 7 _ |a Contribution to a book
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490 0 _ |a Lecture Notes in Computer Science
|v 16296
520 _ _ |a The spatial derivatives in Hamilton-Jacobi partial differential equations for the definition of morphological operations such as dilation and erosion for grey-value images are replaced by fractional derivatives of arbitrary positive order. Focus is laid on geometric invariance with respect to reflections and rotations so that directional bias towards the coordinate directions is avoided. Discretisation of directional fractional derivatives via truncated general power series ultimately leads to an optimisation problem for the advection direction. We numerically compare the proposed fractional morphological operations with conventional counterparts and a simpler fractional-order alternative on grey-value images to show interesting phenomena and gain insights into the effects of the non-local nature of the fractional derivatives which merit further investigation.
536 _ _ |a 5112 - Cross-Domain Algorithms, Tools, Methods Labs (ATMLs) and Research Groups (POF4-511)
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588 _ _ |a Dataset connected to CrossRef Book Series, Journals: juser.fz-juelich.de
700 1 _ |a Kleefeld, Andreas
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700 1 _ |a Breuß, Michael
|0 P:(DE-HGF)0
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700 1 _ |a Burgeth, Bernhard
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773 _ _ |a 10.1007/978-3-032-09544-2_29
|p 401–414
|v 16296
856 4 _ |u https://link.springer.com/chapter/10.1007/978-3-032-09544-2_29
856 4 _ |u https://juser.fz-juelich.de/record/1047562/files/fm-dgmm2025.pdf
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910 1 _ |a Forschungszentrum Jülich
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910 1 _ |a Saarland University
|0 I:(DE-HGF)0
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913 1 _ |a DE-HGF
|b Key Technologies
|l Engineering Digital Futures – Supercomputing, Data Management and Information Security for Knowledge and Action
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|v Enabling Computational- & Data-Intensive Science and Engineering
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914 1 _ |y 2025
915 _ _ |a Nationallizenz
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980 _ _ |a contb
980 _ _ |a I:(DE-Juel1)JSC-20090406
980 _ _ |a UNRESTRICTED


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