Nonlocal Total Variation Using the First and Second Order Derivatives and Its Application to CT image Reconstruction
Abstract
:1. Introduction
2. Methodology
2.1. Problem Definition
2.2. Accelerated Algorithm Using the Proximal Splitting with Passty’s Framework
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2.3. Optimization
2.3.1. Update the Data-Fidelity Term
2.3.2. Update the Regularization Term
2.3.3. The Weight
3. Experimental Results
4. Discussion
5. Conclusions
Author Contributions
Funding
Conflicts of Interest
References
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Nonlocal TV | Nonlocal TKV | Nonlocal TV + TKV | |
---|---|---|---|
Convergence | Good | Not bad | Good |
High contrast | Yes | No | Yes |
Smooth intensity change | No | Yes | Yes |
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Kim, Y.; Kudo, H. Nonlocal Total Variation Using the First and Second Order Derivatives and Its Application to CT image Reconstruction. Sensors 2020, 20, 3494. https://doi.org/10.3390/s20123494
Kim Y, Kudo H. Nonlocal Total Variation Using the First and Second Order Derivatives and Its Application to CT image Reconstruction. Sensors. 2020; 20(12):3494. https://doi.org/10.3390/s20123494
Chicago/Turabian StyleKim, Yongchae, and Hiroyuki Kudo. 2020. "Nonlocal Total Variation Using the First and Second Order Derivatives and Its Application to CT image Reconstruction" Sensors 20, no. 12: 3494. https://doi.org/10.3390/s20123494