Name
Abstract | ||
|---|---|---|
In this paper an upper bound on the decay rate of the mean-squared error for global image denoising is derived. As image size increases, this upper bound decays to zero; that is, the global denoising is asymptotically optimal. Unlike patch-based methods such as BM3D, this property only holds for global denoising schemes. In practice, and as demonstrated in this work, this performance gap between patch-based and global denoisers can grow rapidly with image size. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1109/ICIP.2014.7025164 | Image Processing |
Keywords | Field | DocType |
image denoising,BM3D,additive noise,decay rate,global denoising schemes,global image denoising,image size,Denoising Bound,Global Denoising | Noise reduction,Mathematical optimization,Pattern recognition,Non-local means,Upper and lower bounds,Computer science,Algorithm,Image denoising,Artificial intelligence,Asymptotically optimal algorithm,Image resolution,Performance gap | Conference |
ISSN | Citations | PageRank |
1522-4880 | 0 | 0.34 |
References | Authors | |
10 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hossein Talebi | 1 | 37 | 3.61 |
| Peyman Milanfar | 2 | 3284 | 155.61 |
| Talebi, H. | 3 | 0 | 0.34 |