Name
Abstract | ||
|---|---|---|
Old analog television sequences suffer from a number of degradations. Some of them can be modeled through convolution with a kernel and an additive noise term. In this work, we propose a new blind deconvolution algorithm for the restoration of such sequences based on a variational formulation of the problem. Our method accounts for motion between frames, while enforcing some level of temporal continuity through the use of a novel penalty function involving optical flow operators, in addition to an edge-preserving regularization. The optimization process is performed by a proximal alternating minimization scheme benefiting from theoretical convergence guarantees. Simulation results on synthetic and real video sequences confirm the effectiveness of our method. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.5281/zenodo.44117 | Signal Processing Conference |
Keywords | Field | DocType |
deconvolution,image restoration,image sequences,blind deconvolution algorithm,blind video restoration,edge-preserving regularization,hybrid alternating proximal method,optical flow operators,penalty function,temporal continuity,video sequences,Blind deconvolution,convex optimization,optical flow,proximal algorithms,regularization,video processing | Kernel (linear algebra),Computer vision,Video processing,Blind deconvolution,Convolution,Regularization (mathematics),Artificial intelligence,Convex optimization,Optical flow,Mathematics,Penalty method | Conference |
ISSN | Citations | PageRank |
2076-1465 | 3 | 0.38 |
References | Authors | |
13 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Abboud, F. | 1 | 3 | 0.38 |
| Emilie Chouzenoux | 2 | 202 | 26.37 |
| Jean-Christophe Pesquet | 3 | 206 | 22.24 |
| Jean-Hugues Chenot | 4 | 72 | 12.59 |
| Louis Laborelli | 5 | 80 | 11.78 |