Fast Automated Detection of Crystal Distortion and Crystal Defects in Polycrystal Images

DOI10.1137/130916515zbMath1328.68270OpenAlexW2086353618MaRDI QIDQ5250321

Benedikt Wirth, Matt Elsey

Publication date: 19 May 2015

Published in: Multiscale Modeling & Simulation (Search for Journal in Brave)

Full work available at URL: https://semanticscholar.org/paper/e2da2e021fe6a17eaed6f5db0faa9f5d7ebe806a

zbMATH Keywords

dislocationvariational methodcrystal defectatomic image analysiscrystal distortionsparse curl

Mathematics Subject Classification ID

Computing methodologies for image processing (68U10) Crystalline structure (74E15) Image processing (compression, reconstruction, etc.) in information and communication theory (94A08) Numerical solutions to equations with nonlinear operators (65J15)

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Cites Work

• Unnamed Item
• Extracting grain boundaries and macroscopic deformations from images on atomic scale
• \(\Gamma\)-convergence analysis of systems of edge dislocations: the self energy regime
• The Split Bregman Method for L1-Regularized Problems
• A simple and efficient scheme for phase field crystal simulation
• An Iterative Regularization Method for Total Variation-Based Image Restoration