fast total-variation image deconvolution with adaptive parameter estimation via split bregman method

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ID: 255105
2014
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Abstract
The total-variation (TV) regularization has been widely used in image restoration domain, due to its attractive edge preservation ability. However, the estimation of the regularization parameter, which balances the TV regularization term and the data-fidelity term, is a difficult problem. In this paper, based on the classical split Bregman method, a new fast algorithm is derived to simultaneously estimate the regularization parameter and to restore the blurred image. In each iteration, the regularization parameter is refreshed conveniently in a closed form according to Morozov’s discrepancy principle. Numerical experiments in image deconvolution show that the proposed algorithm outperforms some state-of-the-art methods both in accuracy and in speed.
Reference Key
he2014mathematicalfast Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors ;Chuan He;Changhua Hu;Wei Zhang;Biao Shi;Xiaoxiang Hu
Journal journal of power sources
Year 2014
DOI
10.1155/2014/617026
URL
http://dx.doi.org/10.1155/2014/617026
Keywords
civil engineering (general)mathematics engineering (general)

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