An alternating proximal approach for blind video deconvolution
作者：
Highlights：
• Versatile regularized formulation for blind video deconvolution.
• Alternating proximal algorithm to solve the underlying minimization problem.
• Convergence guarantees on the produced iterates in the challenging nonconvex setting.
• Extensive numerical comparisons of regularizers on synthetic and real video sequences.
摘要
•Versatile regularized formulation for blind video deconvolution.•Alternating proximal algorithm to solve the underlying minimization problem.•Convergence guarantees on the produced iterates in the challenging nonconvex setting.•Extensive numerical comparisons of regularizers on synthetic and real video sequences.
论文关键词：Blind deconvolution,Video processing,Regularization,Nonconvex optimization,Proximal algorithms
论文评审过程：Received 19 December 2017, Revised 17 August 2018, Accepted 18 August 2018, Available online 23 August 2018, Version of Record 14 September 2018.
论文官网地址：https://doi.org/10.1016/j.image.2018.08.007
