Efficient Hyper-Parameter Selection in Total Variation-Penalised XCT Reconstruction Using Freund and Shapire’s Hedge Approach

Efficient Hyper-Parameter Selection in Total Variation-Penalised XCT Reconstruction Using Freund and Shapire’s Hedge Approach

This paper studies the problem of efficiently tuning the hyper-parameters in penalised least-squares reconstruction for XCT. Discovered through the lens of the Compressed Sensing paradigm, penalisation functionals such as Total Variation types of norms, form an essential tool for enforcing structure...

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Bibliographic Details
Main Authors: Stéphane Chrétien, Manasavee Lohvithee, Wenjuan Sun, Manuchehr Soleimani
Format: Article
Language:English
Published: MDPI AG 2020-04-01
Series:Mathematics
Subjects:
hyper-parameter selection
image reconstruction
limited data reconstruction
total variation regularisation
cone-beam computed tomography
Online Access:https://www.mdpi.com/2227-7390/8/4/493

Internet

https://www.mdpi.com/2227-7390/8/4/493

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