Spatio-temporal mean curvature based image sequence restoration

被引:0
|
作者
Ren, Fuquan [1 ,2 ]
Qiu, Tianshuang [2 ]
机构
[1] Yanshan Univ, Sch Sci, Qinhuangdao 066004, Peoples R China
[2] Dalian Univ Technol, Fac Elect Informat & Elect Engn, Dalian 116023, Peoples R China
关键词
AUGMENTED LAGRANGIAN METHOD; REGULARIZATION;
D O I
10.1049/iet-ipr.2015.0246
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In this study, the authors propose a restoration algorithm for blurred and noisy continuous image sequences. The proposed approach treats an image sequence as a space-time volume and employs a spatio-temporal mean curvature regularisation which is a novel regularisation proposed in the study to enhance the smoothness of the solution. An augmented Lagrangian method with splitting techniques is used to handle the problem, iteratively finding solutions to the subproblems. Experiments show that the proposed approach can produce higher quality results and more natural images comparing with other space-time volume based methods on image sequence denoising and deblurring problems.
引用
收藏
页码:359 / 370
页数:12
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