Name
Abstract | ||
|---|---|---|
Many patch-based image denoising algorithms can be formulated as applying a smoothing filter to the noisy image. Expressed as matrices, the smoothing filters must be row normalized, so that each row sums to unity. Surprisingly, if we apply a column normalization before the row normalization, the performance of the smoothing filter can often be significantly improved. Prior works showed that such p... |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1109/TIP.2017.2731208 | IEEE Transactions on Image Processing |
Keywords | Field | DocType |
Smoothing methods,Noise reduction,Noise measurement,Performance gain,Gaussian mixture model,Symmetric matrices | Normalization (statistics),Matrix (mathematics),Non-local means,Symmetrization,Artificial intelligence,Mathematical optimization,Pattern recognition,Expectation–maximization algorithm,Algorithm,Symmetric matrix,Smoothing,Mixture model,Mathematics | Journal |
Volume | Issue | ISSN |
26 | 11 | 1057-7149 |
Citations | PageRank | References |
1 | 0.35 | 31 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Stanley H. Chan | 1 | 403 | 30.95 |
| Todd Zickler | 2 | 1555 | 71.72 |
| Yue M. Lu | 3 | 677 | 60.17 |