Blind Deconvolution With Nonlocal Similarity and l(0) Sparsity for Noisy Image
文献类型:期刊论文
作者 | Ren WH(任卫红)![]() ![]() ![]() |
刊名 | IEEE SIGNAL PROCESSING LETTERS
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出版日期 | 2016 |
卷号 | 23期号:4页码:439-443 |
关键词 | Blind image deconvolution low rank l(0) sparsity nonlocal similarity |
ISSN号 | 1070-9908 |
产权排序 | 1 |
通讯作者 | 任卫红 ; 田建东 ; 唐延东 |
中文摘要 | The blind image deconvolution techniques with sparsity prior in gradient domain are sensitive to noise, even a small amount of noise. To address this problem, in this letter, we propose a novel blind deconvolution model that combines low-rank property, nonlocal similarity, and l(0) sparsity prior. Low-rank property makes the proposed deblurring model robust to image noise. The joint utilization of nonlocal similarity and l(0) sparsity prior has improved the accuracy of blur kernel estimation and restores the fine image details. A numerical method is also given to solve the proposed problem. Experimental results on synthetic and real data show that our algorithm performs better against with the state-of-the-art methods for both noise and noise-free images. |
WOS标题词 | Science & Technology ; Technology |
类目[WOS] | Engineering, Electrical & Electronic |
研究领域[WOS] | Engineering |
关键词[WOS] | SINGLE IMAGE ; CAMERA |
收录类别 | SCI ; EI |
语种 | 英语 |
WOS记录号 | WOS:000372401100001 |
源URL | [http://ir.sia.cn/handle/173321/18496] ![]() |
专题 | 沈阳自动化研究所_机器人学研究室 |
推荐引用方式 GB/T 7714 | Ren WH,Tian JD,Tang YD. Blind Deconvolution With Nonlocal Similarity and l(0) Sparsity for Noisy Image[J]. IEEE SIGNAL PROCESSING LETTERS,2016,23(4):439-443. |
APA | Ren WH,Tian JD,&Tang YD.(2016).Blind Deconvolution With Nonlocal Similarity and l(0) Sparsity for Noisy Image.IEEE SIGNAL PROCESSING LETTERS,23(4),439-443. |
MLA | Ren WH,et al."Blind Deconvolution With Nonlocal Similarity and l(0) Sparsity for Noisy Image".IEEE SIGNAL PROCESSING LETTERS 23.4(2016):439-443. |
入库方式: OAI收割
来源:沈阳自动化研究所
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