Name
Abstract | ||
|---|---|---|
This article deals with an original method to estimate the noise introduced by optical imaging systems, such as CCD cameras. The power of the signal-dependent photon noise is decoupled from the power of the signal-independent electronic noise. The method relies on the multivariate regression of sample mean and variance. Statistically similar image pixels, not necessarily connected, produce scatterpoints that are clustered along a straight line, whose slope and intercept measure the signal-dependent and signal-independent components of the noise power, respectively. Experimental results carried out on a simulated noisy image and on true data from a commercial CCD camera highlight the accuracy of the proposed method and its applicability to separate R–G–B components that have been corrected for the nonlinear effects of the camera response function, but not yet interpolated to the the full size of the mosaiced R–G–B image. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1186/1687-6180-2012-231 | EURASIP J. Adv. Sig. Proc. |
Keywords | Field | DocType |
Noise Model, Image Space, Noisy Image, Noise Estimation, Gravity Center | Line (geometry),Computer vision,Value noise,Noise power,Computer science,Interpolation,Noise (electronics),Dark-frame subtraction,Image noise,Artificial intelligence,Pixel | Journal |
Volume | Issue | ISSN |
2012 | 1 | 1687-6180 |
Citations | PageRank | References |
9 | 0.54 | 12 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Bruno Aiazzi | 1 | 275 | 27.84 |
| Luciano Alparone | 2 | 901 | 80.27 |
| Stefano Baronti | 3 | 559 | 50.87 |
| Massimo Selva | 4 | 87 | 7.92 |
| Lorenzo Stefani | 5 | 10 | 1.58 |