Name
Title | ||
|---|---|---|
Two-stage method for salt-and-pepper noise removal using statistical jump regression analysis. |
Abstract | ||
|---|---|---|
This paper proposes a new two-stage method for image denoising under salt-and-pepper noise based on a median-type noise detector and the edge-preserving surface estimation using statistical jump regression analysis. In the first stage, a median-type noise detector is used to detect the pixels that are likely to be corrupted by salt-and-pepper noise. In the second stage, the image is denoised by using edge-preserving statistical jump regression analysis based on the uncorrupted pixels. The experiments show that the proposed approach obtains better tradeoff between denoising performance and computational complexity. © 2011 IEEE. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1109/VCIP.2011.6115957 | VCIP |
Keywords | Field | DocType |
psnr,computational complexity,image restoration,detectors,edge detection,signal processing,estimation,regression analysis | Noise reduction,Computer vision,Value noise,Pattern recognition,Salt-and-pepper noise,Artificial intelligence,Pixel,Image restoration,Jump,Detector,Gaussian noise,Mathematics | Conference |
Volume | Issue | Citations |
null | null | 0 |
PageRank | References | Authors |
0.34 | 7 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Liang Zhang | 1 | 57 | 18.95 |
| Jian-Zhou Zhang | 2 | 22 | 5.38 |