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Image Denoising via Asymptotic Nonlocal Filtering
Joint Authors
Liu, Xiaoyan
Zhang, Xuande
Li, Xiaoping
Luo, Liang
Feng, Xiang-Chu
Source
Mathematical Problems in Engineering
Issue
Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-02-23
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Abstract EN
The nonlocal means algorithm is widely used in image denoising, but this algorithm does not work well for high-intensity noise.
To overcome this shortcoming, we establish a coupled iterative nonlocal means model in this paper.
Considering the computation complexity of the new model, we realize it by using multiscale wavelet transform and propose an asymptotic nonlocal filtering algorithm which can reduce the influence of noise on similarity estimation and computation complexity.
Moreover, we build a new nonlocal weight function based on the structure similarity index.
Simulation results indicate that the proposed approach cannot only remove the noise but also preserve the structure of image and has good visual effects, especially for highly degenerated images.
American Psychological Association (APA)
Liu, Xiaoyan& Feng, Xiang-Chu& Zhang, Xuande& Li, Xiaoping& Luo, Liang. 2015. Image Denoising via Asymptotic Nonlocal Filtering. Mathematical Problems in Engineering،Vol. 2015, no. 2015, pp.1-9.
https://search.emarefa.net/detail/BIM-1073539
Modern Language Association (MLA)
Liu, Xiaoyan…[et al.]. Image Denoising via Asymptotic Nonlocal Filtering. Mathematical Problems in Engineering No. 2015 (2015), pp.1-9.
https://search.emarefa.net/detail/BIM-1073539
American Medical Association (AMA)
Liu, Xiaoyan& Feng, Xiang-Chu& Zhang, Xuande& Li, Xiaoping& Luo, Liang. Image Denoising via Asymptotic Nonlocal Filtering. Mathematical Problems in Engineering. 2015. Vol. 2015, no. 2015, pp.1-9.
https://search.emarefa.net/detail/BIM-1073539
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1073539