Quantitative Abel tomography robust to noisy, corrupted and missing data

DOI10.1007/S11081-009-9097-ZzbMath1273.94127OpenAlexW2067398756MaRDI QIDQ374692

Thomas J. Asaki

Publication date: 24 October 2013

Published in: Optimization and Engineering (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s11081-009-9097-z

zbMATH Keywords

noisy dataderivative-free optimizationX-ray tomographyAbel transformsmixed-variable optimization

Mathematics Subject Classification ID

Numerical optimization and variational techniques (65K10) Image processing (compression, reconstruction, etc.) in information and communication theory (94A08)

Related Items (2)

A fast algorithm for the inversion of Abel's transform ⋮ High-order total variation regularization approach for axially symmetric object tomography from a single radiograph

Cites Work

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• Nonlinear total variation based noise removal algorithms
• Pattern Search Algorithms for Mixed Variable Programming
• Abel inversion using total variation regularization: applications
• Quantitative Object Reconstruction Using Abel Transform X-Ray Tomography and Mixed Variable Optimization
• Abel inversion using total-variation regularization
• Computational Methods for Inverse Problems
• An Algorithm Model for Mixed Variable Programming

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