Semi-blind image deblurring by a proximal alternating minimization method with convergence guarantees

作者：

Highlights：

• Our method successfully solves a nonconvex semi-blind image restoration model.

• Our method is validated, both theoretically and numerically.

• The proposed algorithm is efficient and stable.

• Any sequences generated by our algorithm converge to a local minimized point.

摘要

•Our method successfully solves a nonconvex semi-blind image restoration model.•Our method is validated, both theoretically and numerically.•The proposed algorithm is efficient and stable.•Any sequences generated by our algorithm converge to a local minimized point.

论文关键词：Proximal method,Nonconvex optimization problem,Semi-blind image deblurring,Convergence analysis

论文评审过程：Received 10 May 2019, Revised 12 November 2019, Accepted 17 February 2020, Available online 7 March 2020, Version of Record 7 March 2020.

论文官网地址：https://doi.org/10.1016/j.amc.2020.125168