摘要
In this study, we propose a linearized proximal alternating direction method with variable stepsize for solving total variation image reconstruction problems. Our method uses a linearized technique and the proximal function such that the closed form solutions of the subproblem can be easily derived.In the subproblem, we apply a variable stepsize, that is like Barzilai-Borwein stepsize, to accelerate the algorithm. Numerical results with parallel magnetic resonance imaging demonstrate the efficiency of the proposed algorithm.
In this study, we propose a linearized proximal alternating direction method with variable stepsize for solving total variation image reconstruction problems. Our method uses a linearized technique and the proximal function such that the closed form solutions of the subproblem can be easily derived.In the subproblem, we apply a variable stepsize, that is like Barzilai-Borwein stepsize, to accelerate the algorithm. Numerical results with parallel magnetic resonance imaging demonstrate the efficiency of the proposed algorithm.
基金
supported in part by the National Natural Science Foundation of China(11361018,11461015)
Guangxi Natural Science Foundation(2014GXNSFFA118001)
Guangxi Key Laboratory of Automatic Detecting Technology and Instruments(YQ15112,YQ16112)
Guilin Science and Technology Project(20140127-2)
the Innovation Project of Guangxi Graduate Education and Innovation Project of GUET Graduate Education(YJCXB201502)
Guangxi Key Laboratory of Cryptography and Information Security(GCIS201624)
