Name
Abstract | ||
|---|---|---|
We introduce a novel aggregation method to efficiently perform image denoising. Preliminary filters are aggregated in a non-linear fashion, using a new metric of pixel proximity based on how the pool of filters reaches a consensus. The numerical performance of the method is illustrated and we show that the aggregate significantly outperforms each of the preliminary filters. |
Year | Venue | DocType |
|---|---|---|
2019 | arXiv: Machine Learning | Journal |
Volume | Citations | PageRank |
abs/1904.00865 | 0 | 0.34 |
References | Authors | |
0 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Benjamin Guedj | 1 | 9 | 8.82 |
| Juliette Rengot | 2 | 0 | 0.34 |