Nonparametric noise estimation method for raw images
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review
Author(s)
Detail(s)
| Original language | English |
|---|---|
| Pages (from-to) | 863-871 |
| Journal / Publication | Journal of the Optical Society of America A: Optics and Image Science, and Vision |
| Volume | 31 |
| Issue number | 4 |
| Publication status | Published - 1 Apr 2014 |
| Externally published | Yes |
Link(s)
Abstract
Optimal denoising works at best on raw images (the image formed at the output of the focal plane, at the CCD or CMOS detector), which display a white signal-dependent noise. The noise model of the raw image is characterized by a function that given the intensity of a pixel in the noisy image returns the corresponding standard deviation; the plot of this function is the noise curve. This paper develops a nonparametric approach estimating the noise curve directly from a single raw image. An extensive cross-validation procedure is described to compare this new method with state-of-the-art parametric methods and with laboratory calibration methods giving a reliable ground truth, even for nonlinear detectors. © 2014 Optical Society of America.
Bibliographic Note
Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to [email protected].
Citation Format(s)
Nonparametric noise estimation method for raw images. / Colom, Miguel; Buades, Antoni; Morel, Jean-Michel.
In: Journal of the Optical Society of America A: Optics and Image Science, and Vision, Vol. 31, No. 4, 01.04.2014, p. 863-871.
In: Journal of the Optical Society of America A: Optics and Image Science, and Vision, Vol. 31, No. 4, 01.04.2014, p. 863-871.
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review
