Alternating split Bregman method for the bilaterally constrained image deblurring problem
Alternating split Bregman method for the bilaterally constrained image deblurring problem
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DOI：
10.1016/j.amc.2014.11.004
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发表时间：
2015
期刊：
影响因子：
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通讯作者：
Baoli Shi;Z. Pang;Jun Wu
中科院分区：
文献类型：
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作者：
Baoli Shi;Z. Pang;Jun Wu
This paper studies the image deblurring problem based on a bilateral constraint by convexly combining two classes of total-variation-type functionals. The proposed model including two L 1-norm terms leads to some numerical difficulties, so we employ the alternating split Bregman method (ASB) to solve it which can be reinterpreted as Douglas–Rachford splitting applied to the dual problem. We also prove that the alternating split Bregman method owns the convergence rate O 1 M for the iteration M. Experimental results demonstrate the viability and efficiency of the proposed model and algorithm to restore blurring and noisy images.
