Name
Abstract | ||
|---|---|---|
Alternating direction method of multiplier (ADMM) is a widely used algorithm for solving constrained optimization problems in image restoration. Among many useful features, one critical feature of the ADMM algorithm is its modular structure, which allows one to plug in any off-the-shelf image denoising algorithm for a subproblem in the ADMM algorithm. Because of the plug-in nature, this type of AD... |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1109/TCI.2016.2629286 | IEEE Transactions on Computational Imaging |
Keywords | Field | DocType |
Convergence,Image restoration,Optimization,Noise reduction,Image resolution,Approximation algorithms | Convergence (routing),Noise reduction,Mathematical optimization,Computer science,Continuation,Multiplier (economics),Gaussian,Image restoration,Fixed point,Bounded function | Journal |
Volume | Issue | ISSN |
3 | 1 | 2573-0436 |
Citations | PageRank | References |
49 | 1.25 | 34 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Stanley H. Chan | 1 | 403 | 30.95 |
| Xiran Wang | 2 | 51 | 1.63 |
| Omar A. Elgendy | 3 | 64 | 4.68 |