Name
Title | ||
|---|---|---|
A Variational Bayesian Approach for Image Restoration - Application to Image Deblurring With Poisson-Gaussian Noise. |
Abstract | ||
|---|---|---|
In this paper, a methodology is investigated for signal recovery in the presence of non-Gaussian noise. In contrast with regularized minimization approaches often adopted in the literature, in our algorithm the regularization parameter is reliably estimated from the observations. As the posterior density of the unknown parameters is analytically intractable, the estimation problem is derived in a ... |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1109/TCI.2017.2700203 | IEEE Transactions on Computational Imaging |
Keywords | Field | DocType |
Bayes methods,Image restoration,Parameter estimation,Minimization,Inverse problems,Degradation | Mathematical optimization,Deblurring,Posterior probability,Regularization (mathematics),Ground truth,Poisson distribution,Image restoration,Gaussian noise,Mathematics,Bayesian probability | Journal |
Volume | Issue | ISSN |
3 | 4 | 2573-0436 |
Citations | PageRank | References |
7 | 0.48 | 60 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Y. Marnissi | 1 | 14 | 2.66 |
| Yuling Zheng | 2 | 15 | 4.34 |
| Emilie Chouzenoux | 3 | 202 | 26.37 |
| Jean-Christophe Pesquet | 4 | 18 | 11.52 |