Name
Abstract | ||
|---|---|---|
Image filtering based on SVD favors the denoising in the line (horizontal) and column (vertical) direction. Based on this property, a novel approach to improving the filtering efficiency of a noisy image is proposed in this paper. The new denoising method adapts shape and size of block to local orientation before performing SVD filtering. Through over-complete representation in overlap regions; the proposed method performs well in denoising and preserving image details. This new technique makes a contrast with some published denoising algorithms. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1109/CSSE.2008.1467 | CSSE (6) |
Keywords | Field | DocType |
noise,svd,filter,adaptive,adaptive filter,matrix decomposition,noise reduction,singular value decomposition,image restoration,filtering | Noise reduction,Singular value decomposition,Computer vision,Pattern recognition,Non-local means,Computer science,Matrix decomposition,Filter (signal processing),Artificial intelligence,Image restoration,Filtering theory,Video denoising | Conference |
Volume | Issue | Citations |
6 | null | 0 |
PageRank | References | Authors |
0.34 | 2 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xiao-Feng Du | 1 | 18 | 6.17 |
| Yang Dunxu | 2 | 0 | 0.34 |
| Cuihua Li | 3 | 169 | 11.67 |
| Jing Li | 4 | 38 | 5.64 |