Spatio‐temporal mean curvature based image sequence restoration. Issue 5 (1st May 2016)

• Record Type: Journal Article
• Authors: Ren, Fuquan; Qiu, Tianshuang
• Is Part Of: IET image processing. Volume 10:Issue 5(2016)
• Page Start: 359
• Page End: 370
• Publication Date: 2016-05-01
• Subjects: image sequences -- image restoration -- iterative methods -- image denoising; spatio‐temporal mean curvature based image sequence restoration algorithm -- space‐time volume -- novel regularisation -- augmented Lagrangian method -- splitting techniques -- iterative solutions -- image sequence denoising -- image deblurring problems; Image processing -- Periodicals; 621.36705
• DOI: 10.1049/iet-ipr.2015.0246
• Languages: English
• ISSNs: 1751-9659

Abstract

Abstract : 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.