DocumentCode :
3363966
Title :
Poisson NL means: Unsupervised non local means for Poisson noise
Author :
Deledalle, Charles-Alban ; Tupin, Florence ; Denis, Loïc
Author_Institution :
Inst. Telecom, Telecom ParisTech, Paris, France
fYear :
2010
fDate :
26-29 Sept. 2010
Firstpage :
801
Lastpage :
804
Abstract :
An extension of the non local (NL) means is proposed for images damaged by Poisson noise. The proposed method is guided by the noisy image and a pre-filtered image and is adapted to the statistics of Poisson noise. The influence of both images can be tuned using two filtering parameters. We propose an automatic setting to select these parameters based on the minimization of the estimated risk (mean square error). This selection uses an estimator of the MSE for NL means with Poisson noise and Newton´s method to find the optimal parameters in few iterations.
Keywords :
Newton method; Poisson distribution; filtering theory; image denoising; mean square error methods; statistical analysis; MSE; Newton method; Poisson NL means; Poisson noise; filtering parameter; mean square error; statistics; unsupervised nonlocal means; Gaussian noise; Noise measurement; Noise reduction; Optimized production technology; Pixel; Probabilistic logic; Newton´s method; Non local means; PURE; Poisson noise; SURE; mean square error;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Image Processing (ICIP), 2010 17th IEEE International Conference on
Conference_Location :
Hong Kong
ISSN :
1522-4880
Print_ISBN :
978-1-4244-7992-4
Electronic_ISBN :
1522-4880
Type :
conf
DOI :
10.1109/ICIP.2010.5653394
Filename :
5653394
Link To Document :
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