# Image Deblurring under Impulse Noise via Total Generalized Variation and Non-Convex Shrinkage
## 3 Model Proposal and Solution Method
### Solution Method
**Funding:** This work was supported by the Foundation of Fujian Province Great Teaching Reform (F)BfG20180015), and the Education and Scientific Research Foundation of Education Department of Fujian Province for Young and Middle-aged Teachers (grant numbers JT180310, JT180309, and JT180311). \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Images** & **Blur Type** & **Noise Level** & **FTVd** & **TGV** & **OGSTV** & **Proposed** \\ \hline \multirow{3}{*}{**Fingerprint**} & \((G,7,5)\) & 30 & 0.86 & 1.47 & **0.81** & 1.19 \\  & \((A,7)\) & 40 & **0.92** & 1.48 & 0.98 & 1.17 \\  & \((M,20,20)\) & 30 & **0.81** & 1.47 & 1.09 & 1.22 \\  & \((M,20,20)\) & 60 & **0.84** & 1.48 & 1.47 & 1.17 \\  & \((G,7,5)\) & 30 & **3.28** & 6.03 & 6.20 & 5.31 \\
**Plane** & \((A,7)\) & 40 & **3.42** & 6.17 & 5.98 & 5.36 \\ \(512\times 512\) & \((M,20,20)\) & 30 & **3.61** & 6.28 & 6.78 & 5.33 \\  & \((M,20,20)\) & 60 & **3.27** & 6.36 & 4.16 & 5.36 \\  & \((G,7,5)\) & 30 & 3.36 & 7.11 & **3.11** & 5.27 \\
**Satellite** & \((A,7)\) & 40 & 3.50 & 6.20 & **2.66** & 5.34 \\ \(512\times 512\) & \((M,20,20)\) & 30 & **3.31** & 6.22 & 3.59 & 5.16 \\  & \((M,20,20)\) & 60 & **3.23** & 6.23 & 4.09 & 5.14 \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Image restoration time (s) of the degraded test images with different levels of blur and impulse noise. **Acknowledgments:** The authors appreciate [PERSON] and [PERSON] of the University of Electronic Science and Technology of China for sharing the OGSTV code. **Conflicts of Interest:** The authors declare no conflicts of interest. ## References

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