## 3 Results and Discussion
### The Comparison with Other Methods
In addition, the  
\begin{table}
\begin{tabular}{c c c c c c c c c c} \hline \hline \multirow{2}{*}{**Image**} & \multicolumn{8}{c}{**Noise Level**} \\ \cline{2-10}  & \multicolumn{4}{c}{**30\%**} & \multicolumn{4}{c}{**40\%**} & \multicolumn{4}{c}{**50\%**} \\ \cline{2-10}  & **Method** & **PSNR** & **SSIM** & **GMSD** & **PSNR** & **SSIM** & **GMSD** & **PSNR** & **SSIM** & **GMSD** \\ \hline \multirow{4}{*}{Truck} & ITV & 30.0291 & 0.8884 & 0.0616 & 29.5562 & 0.8893 & 0.0651 & 29.1880 & 0.8837 & 0.0691 \\  & ATV & 35.3620 & 0.9228 & 0.0331 & 33.4723 & 0.9087 & 0.0412 & 31.4261 & 0.8976 & 0.0529 \\  & HNHOTV-OGS & 36.9788 & 0.9246 & 0.0280 & 34.6626 & 0.9037 & 0.0365 & 32.1012 & 0.8763 & 0.0490 \\  & L0 TVPADMM & 37.1920 & 0.9033 & 0.0271 & 36.5800 & 0.8964 & 0.0291 & 35.5870 & 0.8682 & 0.0326 \\  & Lp\_HOGS & **39.8380** & **0.9502** & **0.0080** & **39.2490** & **0.9491** & **0.0092** & **38.4970** & **0.9420** & **0.0119** \\ \hline \multirow{4}{*}{Garden} & ITV & 36.4479 & 0.9357 & 0.0379 & 36.0066 & 0.9318 & 0.0400 & 34.5629 & 0.9233 & 0.0456 \\  & ATV & 37.1587 & 0.9376 & 0.0352 & 36.6090 & 0.9321 & 0.0385 & 35.2160 & 0.9221 & 0.0432 \\  & HNHOTV-OGS & 38.8667 & 0.9429 & 0.0290 & 37.7810 & 0.9328 & 0.0329 & 36.5325 & 0.9163 & 0.0380 \\  & L0 TVPADMM & 39.2100 & 0.9290 & 0.0274 & 39.0490 & 0.9347 & 0.0287 & 38.7830 & 0.9260 & 0.0293 \\  & Lp\_HOGS & **41.2420** & **0.9879** & **0.0091** & **0.48009** & **0.9871** & **0.0099** & **40.0002** & **0.9850** & **0.0119** \\ \hline \multirow{4}{*}{Stairs} & ITV & 36.1479 & 0.9353 & 0.0480 & 35.5521 & 0.9303 & 0.0517 & 34.4880 & 0.9225 & 0.0562 \\  & ATV & 37.2454 & 0.9394 & 0.0426 & 36.3834 & 0.9312 & 0.0469 & 35.4070 & 0.9222 & 0.0517 \\  & HNHOTV-OGS & 38.2716 & 0.9351 & 0.0375 & 37.1927 & 0.9226 & 0.0425 & 35.8911 & 0.9027 & 0.0494 \\  & L0 TVPADMM & 38.8690 & 0.9273 & 0.0350 & 38.6270 & 0.9251 & 0.0360 & 38.3940 & 0.9227 & 0.0370 \\  & Lp\_HOGS & **41.4211** & **0.9898** & **0.0084** & **40.9604** & **0.9892** & **0.0096** & **40.0652** & **0.9872** & **0.0127** \\ \hline \multirow{4}{*}{Corridor} & ITV & 35.1721 & 0.9273 & 0.0544 & 34.5450 & 0.9227 & 0.0581 & 33.8964 & 0.9122 & 0.0676 \\  & ATV & 35.7739 & 0.9299 & 0.0519 & 34.8115 & 0.9202 & 0.0565 & 33.9243 & 0.9078 & 0.0628 \\  & HNHOTV-OGS & 37.4461 & 0.9281 & 0.0420 & 36.4630 & 0.9151 & 0.0470 & 34.9757 & 0.8995 & 0.0558 \\  & L0 TVPADMM & 38.5150 & 0.9404 & 0.0373 & 38.4204 & 0.9395 & 0.0375 & 38.0550 & 0.9343 & 0.0391 \\  & Lp\_HOGS & **40.7789** & **0.9904** & **0.0092** & **40.4021** & **0.9897** & **0.0105** & **39.6962** & **0.9872** & **0.0127** \\ \hline \multirow{4}{*}{Road} & ITV & 34.1196 & 0.9351 & 0.0443 & 33.5094 & 0.9300 & 0.0472 & 32.6307 & 0.9202 & 0.0520 \\  & ATV & 34.7909 & 0.9377 & 0.0411 & 33.8026 & 0.9289 & 0.0456 & 32.7069 & 0.9155 & 0.0515 \\  & HNHOTV-OGS & 37.3621 & 0.9451 & 0.0302 & 36.3655 & 0.9355 & 0.0338 & 34.8160 & 0.9167 & 0.0404 \\  & L0 TVPADMM & 38.5640 & 0.9462 & 0.0262 & 38.0270 & 0.9378 & 0.0276 & 37.7320 & 0.9401 & 0.0289 \\  & Lp\_HOGS & **40.6179** & **0.9926** & **0.0077** & **40.1633** & **0.9921** & **0.0088** & **39.0861** & **0.9901** & **0.0119** \\ \hline \multirow{4}{*}{Buildings} & ITV & 30.1056 & 0.8555 & 0.0613 & 29.7495 & 0.8454 & 0.0645 & 29.2963 & 0.8365 & 0.0676 \\  & ATV & 34.8630 & 0.9071 & 0.0374 & 33.1033 & 0.8860 & 0.0443 & 30.4774 & 0.8579 & 0.0585 \\  & HNHOTV-OGS & 36.8107 & 0.9336 & 0.0286 & 34.9021 & 0.9140 & 0.0356 & 32.4871 & 0.8845 & 0.0470 \\  & L0 TVPADMM & 37.0520 & 0.9258 & 0.0276 & 36.1780 & 0.9121 & 0.0305 & 35.5460 & 0.8971 & 0.0328 \\  & Lp\_HOGS & **39.8475** & **0.9606** & **0.0120** & **39.2298** & **0.9589** & **0.0145** & **38.6869** & **0.9531** & **0.0160** \\ \hline \multirow{4}{*}{Car} & ITV & 30.9921 & 0.8883 & 0.0555 & 30.6337 & 0.8809 & 0.0578 & 30.2899 IR image after deblurring obtained a better visual effect, which is conducive to subsequent image analysis and processing.