Synthetic aperture radar image despeckling via total generalised variation approach
文献类型：期刊论文
| 作者 | Feng, Wensen1; Lei, Hong2; Qiao, Hong1,3
|
| 刊名 | IET IMAGE PROCESSING
 |
| 出版日期 | 2015-03-01 |
| 卷号 | 9期号:3页码:236-248 |
| 关键词 | synthetic aperture radar radar imaging image denoising speckle variational techniques piecewise constant techniques smoothing methods higher order statistics optimisation Monte Carlo methods synthetic aperture radar image despeckling total generalised variation approach speckle reduction total variation regularisation piecewise constant image smooth transition TGV-based model staircasing artefact reduction higher order smoothness numerical scheme Nesterov algorithm TGV-based optimisation problem Monte Carlo method |
| 英文摘要 | Speckle reduction is an important task in synthetic aperture radar. One extensively used approach is based on total variation (TV) regularisation, which can realise significantly sharp edges, but on the other hand brings in the undesirable staircasing artefacts. In essence, the TV-based methods tend to create piecewise-constant images even in regions with smooth transitions. In this study, a new method is proposed for speckle reduction via total generalised variation (TGV) penalty. This is reasonable from the fact that the TGV-based model can reduce the staircasing artefacts of TV by being aware of higher-order smoothness. An efficient numerical scheme based on the Nesterov's algorithm is also developed for solving the TGV-based optimisation problem. Monte Carlo experiments show that the proposed scheme yields state-of-the-art results in terms of both performance and speed. Especially when the image has some higher-order smoothness, the authors' scheme outperforms the TV-based methods. |
| WOS标题词 | Science & Technology ; Technology |
| 类目[WOS] | Engineering, Electrical & Electronic |
| 研究领域[WOS] | Engineering |
| 关键词[WOS] | MULTIPLICATIVE NOISE REMOVAL ; SAR IMAGES ; SPECKLE ; FILTERS ; MODEL ; MINIMIZATION ; RECOVERY ; DOMAIN |
| 收录类别 | SCI |
| 语种 | 英语 |
| WOS记录号 | WOS:000350799900008 |
| 公开日期 | 2015-09-22 |
| 源URL | [http://ir.ia.ac.cn/handle/173211/8087]  |
| 专题 | 自动化研究所_复杂系统管理与控制国家重点实验室_机器人应用与理论组 |
| 作者单位 | 1.Univ Sci & Technol Beijing, Sch Automat & Elect Engn, Beijing 100083, Peoples R China 2.Chinese Acad Sci, Inst Elect, Beijing 100190, Peoples R China 3.Chinese Acad Sci, Inst Automat, Beijing 100190, Peoples R China |
| 推荐引用方式 GB/T 7714 | Feng, Wensen,Lei, Hong,Qiao, Hong. Synthetic aperture radar image despeckling via total generalised variation approach[J]. IET IMAGE PROCESSING,2015,9(3):236-248. |
| APA | Feng, Wensen,Lei, Hong,&Qiao, Hong.(2015).Synthetic aperture radar image despeckling via total generalised variation approach.IET IMAGE PROCESSING,9(3),236-248. |
| MLA | Feng, Wensen,et al."Synthetic aperture radar image despeckling via total generalised variation approach".IET IMAGE PROCESSING 9.3(2015):236-248. |
入库方式： OAI收割
来源：自动化研究所
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