Institutional Repository
| Blind deblurring from single motion image based on adaptive weighted total variation algorithm | |
| Wen, J; Zhao, JS; Cailing, W; Yan, SX; Wang, W | |
| 2016 | |
| Source | IET SIGNAL PROCESSING
 |
| ISSN | 1751-9675 |
| Volume | 10Issue:6Pages:611-618 |
| English Abstract | Blind image deblurring is an important topic which is widely used in many research fields such as photography, optics, astronomy, medical images, monitoring, military and so on. Although many algorithms have been proposed to improve the deblurring result in the past years, most of them cannot perform perfectly in some challenging cases. This study presents a novel blind deblurring method based on an adaptive weighted total variation (TV) algorithm. The blur kernel estimation is based on the image structure, the sparsity and continuity prior of point spread function is also taken into account. To get better effect of removing the ringing artefacts, adaptive weight calculated according to the property of the higher-order partial derivatives in the local image is proposed in TV algorithm to alleviate the ill-posed inverse problem and stabilise the solution for latent image restoration. The experimental results prove that the proposed algorithm can suppress the ringing artefacts to a great extent in the latent image, and can get much better effect in both vision and theoretical results than traditional algorithms.; Blind image deblurring is an important topic which is widely used in many research fields such as photography, optics, astronomy, medical images, monitoring, military and so on. Although many algorithms have been proposed to improve the deblurring result in the past years, most of them cannot perform perfectly in some challenging cases. This study presents a novel blind deblurring method based on an adaptive weighted total variation (TV) algorithm. The blur kernel estimation is based on the image structure, the sparsity and continuity prior of point spread function is also taken into account. To get better effect of removing the ringing artefacts, adaptive weight calculated according to the property of the higher-order partial derivatives in the local image is proposed in TV algorithm to alleviate the ill-posed inverse problem and stabilise the solution for latent image restoration. The experimental results prove that the proposed algorithm can suppress the ringing artefacts to a great extent in the latent image, and can get much better effect in both vision and theoretical results than traditional algorithms. |
| Indexed Type | SCI |
| Keyword | Image Restoration Image Motion Analysis Inverse Problems Blind Image Deblurring Method Adaptive Weighted Total Variation Algorithm Single Motion Image Structure Blur Kernel Estimation Point Spread Function Ringing Artefact Removal Higher-order Partial Derivative Ill-posed Inverse Problem Latent Image Restoration |
| Department | Tianjin Polytech Univ, Sch Elect & Informat Engn, Tianjin 300387, Peoples R China. Chinese Acad Sci, Inst Software, Sci & Technol Integrated Informat Syst Lab, Beijing 100190, Peoples R China. Xian Shiyou Univ, Coll Comp Sci, Xian 710065, Peoples R China. |
| Language | 英语 |
| WOS ID | WOS:000381223200005 |
| Citation statistics | |
| Content Type | 期刊论文 |
| URI | http://ir.iscas.ac.cn/handle/311060/17314 |
| Collection | 中国科学院软件研究所 |
| Recommended Citation GB/T 7714 | Wen, J,Zhao, JS,Cailing, W,et al. Blind deblurring from single motion image based on adaptive weighted total variation algorithm[J]. IET SIGNAL PROCESSING,2016,10(6):611-618. |
| APA | Wen, J,Zhao, JS,Cailing, W,Yan, SX,&Wang, W.(2016).Blind deblurring from single motion image based on adaptive weighted total variation algorithm.IET SIGNAL PROCESSING,10(6),611-618. |
| MLA | Wen, J,et al."Blind deblurring from single motion image based on adaptive weighted total variation algorithm".IET SIGNAL PROCESSING 10.6(2016):611-618. |
| Files in This Item: | ||||||
| File Name/Size | DocType | Version | Access | License | ||
| 07518546.pdf（1030KB） | 开放获取 | License | Application Full Text | |||
Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.
Edit Comment