Name
Abstract | ||
|---|---|---|
It is difficult to precisely detect all impulsive noise in color images due to the nonstationarity caused by edges and fine details. For many pixels, we can not absolutely classify them as noisy or noise-free, but can only describe them using the likelihood that they are corrupted by impulsive noise. Based on this consideration, we present a new filtering solution to removing impulsive noise from color images. The proposed method first utilizes the unit transforms of quaternions to represent the chromaticity difference of two color pixels, and then divides the image into noise-free and possible noisy pixels. Finally it performs adaptive weighted vector median filtering operations on only the possible noisy pixels to suppress noise. The new weighting mechanism is based on a joint spatial/quaternion-chromaticity criterion, which ensures that pixels with different contamination likelihoods have different contributions to the filter's output. The extensive simulation results indicate that the proposed method significantly outperforms some other well-known multichannel filtering techniques. (C) 2010 SPIE and IS&T. [DOI: 10.1117/1.3491498] |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1117/1.3491498 | JOURNAL OF ELECTRONIC IMAGING |
Field | DocType | Volume |
Computer vision,Median filter,Pattern recognition,Color histogram,Computer science,Salt-and-pepper noise,Filter (signal processing),Dark-frame subtraction,Image noise,Impulse noise,Pixel,Artificial intelligence | Journal | 19 |
Issue | ISSN | Citations |
4 | 1017-9909 | 9 |
PageRank | References | Authors |
0.49 | 32 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Lianghai Jin | 1 | 185 | 15.07 |
| Hong Liu | 2 | 96 | 18.53 |
| Xiangyang Xu | 3 | 76 | 10.40 |
| Enmin Song | 4 | 176 | 24.53 |