Name
Title | ||
|---|---|---|
A robust regularised restoration algorithm based on Topkis-Veinott optimisation method |
Abstract | ||
|---|---|---|
We present a robust iterative algorithm for restoration of blurred and noisy images. The restoration model is first regularised and then solved iteratively. An optimal regularisation parameter is estimated using the Topkis-Veinott gradient method. This restoration algorithm is compared with other competitive restoration algorithms in the literature. Experimental results are presented to demonstrate the comparative important features of our algorithm, namely, robustness in the presence of noise and high quality restoration results. |
Year | DOI | Venue |
|---|---|---|
2004 | 10.1109/ICPR.2004.1333870 | ICPR (4) |
Keywords | Field | DocType |
optimisation,restoration algorithm,robust iterative algorithm,topkis-veinott gradient method,noisy image restoration,noise,parameter estimation,image restoration,topkis-veinott optimisation method,high quality restoration result,noisy image,comparative important feature,iterative algorithm,gradient methods,restoration model,optimal regularisation parameter,blurred image restoration,stability,robust regularised restoration algorithm,competitive restoration algorithm,gradient method | Gradient method,Mathematical optimization,Pattern recognition,Iterative method,Computer science,Algorithm,Robustness (computer science),Artificial intelligence,Image restoration,Estimation theory | Conference |
Volume | ISSN | ISBN |
4 | 1051-4651 | 0-7695-2128-2 |
Citations | PageRank | References |
0 | 0.34 | 5 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Daan Zhu | 1 | 0 | 0.68 |
| Moe Razaz | 2 | 23 | 5.63 |
| Richard Lee | 3 | 0 | 0.68 |