Name
Title | ||
|---|---|---|
Removing Turbulence Effect via Hybrid Total Variation and Deformation-Guided Kernel Regression. |
Abstract | ||
|---|---|---|
It remains a challenge to simultaneously remove geometric distortion and space-time-varying blur in frames captured through a turbulent atmospheric medium. To solve, or at least reduce these effects, we propose a new scheme to recover a latent image from observed frames by integrating a new hybrid total variation model and deformation-guided spatial-temporal kernel regression. The proposed scheme ... |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1109/TIP.2016.2598638 | IEEE Transactions on Image Processing |
Keywords | Field | DocType |
Image restoration,Distortion,Kernel,Deconvolution,Optical distortion,Optical imaging,Optical sensors | Convergence (routing),Pattern recognition,Latent image,Blind deconvolution,Turbulence,Regularization (mathematics),Artificial intelligence,Fuse (electrical),Distortion,Kernel regression,Mathematics | Journal |
Volume | Issue | ISSN |
25 | 10 | 1057-7149 |
Citations | PageRank | References |
8 | 0.49 | 27 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yuan Xie | 1 | 407 | 27.48 |
| Wensheng Zhang | 2 | 323 | 28.76 |
| Dacheng Tao | 3 | 19032 | 747.78 |
| Wenrui Hu | 4 | 18 | 1.64 |
| Yanyun Qu | 5 | 216 | 38.66 |
| Hanzi Wang | 6 | 1107 | 92.85 |