Name
Abstract | ||
|---|---|---|
In this paper, we suggest a general model for the fixed-valued impulse noise and propose a two-stage method for high density noise suppression while preserving the image details. In the first stage, we apply an iterative impulse detector, exploiting the image entropy, to identify the corrupted pixels and then employ an Adaptive Iterative Mean filter to restore them. The filter is adaptive in terms of the number of iterations, which is different for each noisy pixel, according to the Euclidean distance from the nearest uncorrupted pixel. Experimental results show that the proposed filter is fast and outperforms the best existing techniques in both objective and subjective performance measures. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1186/1687-5281-2013-15 | EURASIP J. Image and Video Processing |
Keywords | Field | DocType |
Image denoising, Salt-and-pepper noise, General fixed-valued impulse noise, Image entropy, Adaptive iterative mean filter | Computer vision,Median filter,Pattern recognition,Computer science,Non-local means,Salt-and-pepper noise,Dark-frame subtraction,Image noise,Adaptive filter,Artificial intelligence,Impulse noise,Image restoration | Journal |
Volume | Issue | ISSN |
2013 | 1 | 1687-5281 |
Citations | PageRank | References |
10 | 0.74 | 7 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hossein Hosseini | 1 | 96 | 14.52 |
| Farokh Marvasti | 2 | 573 | 72.71 |