Unknown noise removal via sparse representation model | |
Zhang JC(张俊超)1,2,3,4,5![]() ![]() ![]() ![]() ![]() | |
Department | 光电信息技术研究室 |
Source Publication | ISA Transactions
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ISSN | 0019-0578 |
2019 | |
Volume | 94Pages:135-143 |
Indexed By | SCI ; EI |
EI Accession number | 20191306706345 |
WOS ID | WOS:000501655900013 |
Contribution Rank | 1 |
Funding Organization | China Scholarship Council (CSC) (grant numbers 201704910730) |
Keyword | Image denoising Mixed noise Sparse representation Dictionary learning |
Abstract | To remove more complex or unknown noise, we propose a new dictionary learning model by assuming noise as Mixture of Gaussian (MoG) distributions. Since MoG is able to approximate any continuous distributions universally, the proposed method can effectively recover the original image from the corrupted one with various forms of noise. Meanwhile, to solve weighted 2−0 minimization problems, we further propose modified orthogonal matching pursuit method in sparse coding and extend alternating proximal algorithm to update dictionaries. Experimental results demonstrate that our proposed method is superior to several previous denoising methods in terms of quantitative measures and visual quality. |
Language | 英语 |
WOS Subject | Automation & Control Systems ; Engineering, Multidisciplinary ; Instruments & Instrumentation |
WOS Keyword | IMPULSE NOISE ; THRESHOLDING ALGORITHM ; IMAGE ; WAVELET ; DECOMPOSITION ; DOMAIN ; FILTER |
WOS Research Area | Automation & Control Systems ; Engineering ; Instruments & Instrumentation |
Funding Project | China Scholarship Council (CSC)[201704910730] |
Citation statistics | |
Document Type | 期刊论文 |
Identifier | http://ir.sia.cn/handle/173321/24470 |
Collection | 光电信息技术研究室 |
Corresponding Author | Zhang JC(张俊超) |
Affiliation | 1.Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China 2.Institutes of Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang 110169, China 3.University of Chinese Academy of Sciences, Beijing 100049, China 4.Key Laboratory of Opto-Electronic Information Processing, CAS, Shenyang 110016, China 5.The Key Lab of Image Understanding and Computer Vision, Liaoning Province, Shenyang 110016, China |
Recommended Citation GB/T 7714 | Zhang JC,Luo HB,Hui B,et al. Unknown noise removal via sparse representation model[J]. ISA Transactions,2019,94:135-143. |
APA | Zhang JC,Luo HB,Hui B,Chang Z,&Zhang XY.(2019).Unknown noise removal via sparse representation model.ISA Transactions,94,135-143. |
MLA | Zhang JC,et al."Unknown noise removal via sparse representation model".ISA Transactions 94(2019):135-143. |
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Unknown noise remova(2995KB) | 期刊论文 | 作者接受稿 | 开放获取 | CC BY-NC-SA | View Application Full Text |
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