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View all- Li GHuang XLi S(2017)Adaptive Bregmanized total variation model for mixed noise removalAEU - International Journal of Electronics and Communications10.1016/j.aeue.2017.06.02380(29-35)Online publication date: Oct-2017
Image Denoising Using Fractional-Order Non-Local TV Model
Authors: 
Ning He, Ke Lu, Jin-Bao WangAuthors Info & Claims
Pages 279 - 282
Abstract
A fractional order non-local denoising algorithm and the implementation of fractional order non-local filter are introduced and discussed in this paper. The proposed regularize image denoising problem using a total variation (TV) prior on a graph, which based on the Riemann-Liouville numerical algorithm of fractional differential. The solution of this model is obtained by solving the minimum of the fractional functional. An efficient numerical method based on the dual theory is introduced to solve the corresponding Euler-Lagrange equation. The relationship between the regularization parameter and fractional-order is analyzed, which provides an important basis for the design of optimal strategy. The experiments demonstrate the validity of this fractional-order non-local TV model. The results of emulation experiments show that our algorithm's performance is prior to the Gaussian smoothing filter.
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Index Terms
- Image Denoising Using Fractional-Order Non-Local TV Model
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Published In
July 2014
430 pages
ISBN:9781450328104
DOI:10.1145/2632856
- General Chairs:
- Hanzi Wang,
- Larry Davis,
- Program Chairs:
- Wenwu Zhu,
- Stephan Kopf,
- Yanyun Qu,
- Publications Chairs:
- Jun Yu,
- Jitao Sang,
- Tao Mei
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In-Cooperation
- NSF of China: National Natural Science Foundation of China
- Beijing ACM SIGMM Chapter
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Association for Computing Machinery
New York, NY, United States
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Published: 10 July 2014
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ICIMCS '14
ICIMCS '14: International Conference on Internet Multimedia Computing and Service
July 10 - 12, 2014
Xiamen, China
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Overall Acceptance Rate 163 of 456 submissions, 36%
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View all- Li GHuang XLi S(2017)Adaptive Bregmanized total variation model for mixed noise removalAEU - International Journal of Electronics and Communications10.1016/j.aeue.2017.06.02380(29-35)Online publication date: Oct-2017
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