Efficient primal-dual fixed point algorithm with dynamic stepsize for convex problems with applications to imaging restoration

Meng Wen; Shigang Yue; Yuchao Tang; Jigen Peng

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arXiv · 1604.04852

Efficient primal-dual fixed point algorithm with dynamic stepsize for convex problems with applications to imaging restoration

Meng Wen·Shigang Yue·Yuchao Tang·Jigen Peng

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Abstract

We consider the problem of finding the minimization of the sum of a convex function and the composition of another convex function with a continuous linear operator from the view of fixed point algorithms based on proximity operators. We design a primal-dual fixed point algorithm with dynamic stepsize based on the proximity operator and obtain a scheme with a closed form solution for each iteration. Based on Modified Mann iteration and the firmly nonexpansive properties of the proximity operator, we achieve the convergence of the proposed algorithm.

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BibTeX RIS

Meng Wen, Shigang Yue, Yuchao Tang, Jigen Peng. 2016-04-17. Efficient primal-dual fixed point algorithm with dynamic stepsize for convex problems with applications to imaging restoration. https://arxiv.org/abs/1604.04852

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