Scattering transform in microstructure reconstruction
- Descriptor-based microstructure characterization plays a crucial role in the field of reversed material engineering for random heterogeneous media. With the advent of differentiable microstructure characterization and reconstruction, there has been a growing interest in the development of differentiable formulations of descriptors. The search for effective descriptors becomes indispensable to adequately characterize a wide range of microstructures. This work proposes a novel approach to construct a descriptor by utilizing a wavelet-based transformation called the scattering transformation on microstructure images. The characterization and reconstruction capabilities of this newly developed descriptor are compared to a benchmark descriptor based on spatial correlation functions using various 2D microstructure images. The comparative analysis aims to evaluate the effectiveness and potential advantages of the proposed wavelet-based descriptor.
Author: | Paul ReckORCiD, Paul Seibert, Alexander Raßloff, Markus Kästner, Daniel PeterseimORCiDGND |
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URN: | urn:nbn:de:bvb:384-opus4-1097364 |
Frontdoor URL | https://opus.bibliothek.uni-augsburg.de/opus4/109736 |
ISSN: | 1617-7061OPAC |
Parent Title (English): | PAMM: Proceedings in Applied Mathematics and Mechanics |
Publisher: | Wiley |
Place of publication: | Weinheim |
Type: | Article |
Language: | English |
Year of first Publication: | 2023 |
Publishing Institution: | Universität Augsburg |
Release Date: | 2023/12/05 |
Volume: | 23 |
Issue: | 3 |
First Page: | e202300169 |
DOI: | https://doi.org/10.1002/pamm.202300169 |
Institutes: | Mathematisch-Naturwissenschaftlich-Technische Fakultät |
Mathematisch-Naturwissenschaftlich-Technische Fakultät / Institut für Mathematik | |
Mathematisch-Naturwissenschaftlich-Technische Fakultät / Institut für Mathematik / Lehrstuhl für Numerische Mathematik | |
Dewey Decimal Classification: | 5 Naturwissenschaften und Mathematik / 51 Mathematik / 510 Mathematik |
Licence (German): | CC-BY 4.0: Creative Commons: Namensnennung (mit Print on Demand) |