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2010

UPRE method for total variation parameter selection

9 years 6 months ago
UPRE method for total variation parameter selection
Total Variation (TV) regularization is a popular method for solving a wide variety of inverse problems in image processing. In order to optimize the reconstructed image, it is important to choose a good regularization parameter. The Unbiased Predictive Risk Estimator (UPRE) has been shown to give a good estimate of this parameter for Tikhonov regularization. In this paper we propose an extension of the UPRE method to the TV problem. Since direct computation of the extended UPRE is impractical in the case of inverse problems such as deblurring, due to the large scale of the associated linear problem, we also propose a method which provides a good approximation of this large scale problem, while significantly reducing computational requirements.
Youzuo Lin, Brendt Wohlberg, Hongbin Guo
Added 30 Jan 2011
Updated 30 Jan 2011
Type Journal
Year 2010
Where SIGPRO
Authors Youzuo Lin, Brendt Wohlberg, Hongbin Guo
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