DocumentCode :
11250
Title :
Noise Estimation From Digital Step-Model Signal
Author :
Laligant, Olivier ; Truchetet, F. ; Fauvet, Eric
Author_Institution :
Le2i Lab., Univ. de Bourgogne, Le Creusot, France
Volume :
22
Issue :
12
fYear :
2013
fDate :
Dec. 2013
Firstpage :
5158
Lastpage :
5167
Abstract :
This paper addresses the noise estimation in the digital domain and proposes a noise estimator based on the step signal model. It is efficient for any distribution of noise because it does not rely only on the smallest amplitudes in the signal or image. The proposed approach uses polarized/directional derivatives and a nonlinear combination of these derivatives to estimate the noise distribution (e.g., Gaussian, Poisson, speckle, etc.). The moments of this measured distribution can be computed and are also calculated theoretically on the basis of noise distribution models. The 1D performances are detailed, and as this paper is mostly dedicated to image processing, a 2D extension is proposed. The 2D performances for several noise distributions and noise models are presented and are compared with selected other methods.
Keywords :
CCD image sensors; amplitude estimation; noise; CCD sensors; digital domain; digital step-model signal; noise distribution models; noise estimation; nonlinear combination; polarized/directional derivatives; smallest amplitudes; Estimation; Image edge detection; Noise measurement; Probability density function; Random variables; White noise; CCD sensor; Gaussian white noise; Noise estimation; Poisson noise; digital signal; edge model; impulse noise; multiplicative noise; noise distribution; noise estimator; nonlinear model; salt and pepper noise; step model;
fLanguage :
English
Journal_Title :
Image Processing, IEEE Transactions on
Publisher :
ieee
ISSN :
1057-7149
Type :
jour
DOI :
10.1109/TIP.2013.2282123
Filename :
6600966
Link To Document :
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