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题名: An Adaptive Fractional-Order Variation Method for Multiplicative Noise Removal
作者: Tian D(田丹); Du YK(杜英魁); Chen DL(陈大力)
作者部门: 机器人学研究室
关键词: gamma noise ; image denoising ; fractional differential ; primal-dual algorithm ; adaptive regularization parameter
刊名: JOURNAL OF INFORMATION SCIENCE AND ENGINEERING
ISSN号: 1016-2364
出版日期: 2016
卷号: 32, 期号:3, 页码:747-762
收录类别: SCI ; EI
产权排序: 1
项目资助者: State Key Laboratory of Robotics, China [2015008] ; China National Nature Science Foundation [61503274] ; Liaoning province Nature Science Foundation [2015020158-301]
摘要: This paper aims to develop a convex fractional-order variation model for image multiplicative noise removal, where the regularization parameter can be adjusted adaptively according to balancing principle at each iterations to control the trade-off between the fitness and smoothness of the denoised images. In the light of the saddle-point theory, a primal-dual algorithm has been applied to solve the proposed model, and the convergence of the algorithm is guaranteed. Simulations with comparisons are carried out to demonstrate the details preserving ability and the fast property of our proposed denoising method.
语种: 英语
WOS记录号: WOS:000375523300013
WOS标题词: Science & Technology ; Technology
类目[WOS]: Computer Science, Information Systems
关键词[WOS]: CHOICE ; MODEL
研究领域[WOS]: Computer Science
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内容类型: 期刊论文
URI标识: http://ir.sia.cn/handle/173321/18660
Appears in Collections:机器人学研究室_期刊论文

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Recommended Citation:
Tian D,Du YK,Chen DL. An Adaptive Fractional-Order Variation Method for Multiplicative Noise Removal[J]. JOURNAL OF INFORMATION SCIENCE AND ENGINEERING,2016,32(3):747-762.
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