Name
Abstract | ||
|---|---|---|
This paper describes a fast method for noise level estimation and denoising. Specifically, we address the problem of estimating the standard deviation of additive white Gaussian noise in digital images; the computed value is used to reduce Gaussian noise and eliminate defective pixels in a raw digital image. The method is particularly suitable for implementation in low power mobile devices with imaging capabilities such as camera phones, as well as digital still cameras (DSC). |
Year | DOI | Venue |
|---|---|---|
2005 | 10.1109/TCE.2005.1510518 | Consumer Electronics, IEEE Transactions |
Keywords | Field | DocType |
AWGN,image denoising,image resolution,mobile handsets,additive white Gaussian noise,defective pixels,digital images,integrated noise reduction,low power mobile devices,noise level estimation,standard deviation | Noise reduction,Computer vision,Median filter,Noise measurement,Computer science,Dark-frame subtraction,Electronic engineering,Image noise,Digital image,Artificial intelligence,Additive white Gaussian noise,Gaussian noise | Journal |
Volume | Issue | ISSN |
51 | 3 | 0098-3063 |
Citations | PageRank | References |
9 | 0.88 | 4 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Bosco, A. | 1 | 9 | 0.88 |
| A. Bruna | 2 | 98 | 6.97 |
| Messina, G. | 3 | 159 | 13.42 |
| Giuseppe Spampinato | 4 | 21 | 4.93 |