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Spatiotemporal Video Denoising Based on Adaptive Thresholding and Clustering
Joint Authors
Su, Benyu
Liu, Kui
Hadi, Ali Naser
Tan, Jieqing
Yahya, Ali Abdullah
Source
Discrete Dynamics in Nature and Society
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-03-14
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Abstract EN
In this paper we propose a novel video denoising method based on adaptive thresholding and K-means clustering.
In the proposed method the adaptive thresholding is applied rather than the conventional hard-thresholding of the VBM3D method.
The adaptive thresholding has a high ability to adapt and change according to the amount of noise.
More specifically, hard-thresholding is applied on the higher noise areas while soft-thresholding is applied on the lower noise areas.
Consequently, we can successfully remove the noise effectively and at the same time preserve the edges of the image, because the clustering approach saves more computation time and is more capable of finding relevant patches than the block-matching approach.
So, the K-means clustering method in the final estimate in this paper is adopted instead of the block-matching method in the VBM3D method in order to restrict the search of the candidate patches within the region of the reference patch and therefore improve the grouping.
Experimental results emphasize the superiority of the new method over the reference methods in terms of visual quality, Peak Signal-to-Noise Ratio (PSNR), and Image Enhancement Factor (IEF).
Execution time of the proposed algorithm consumes less time in denoising than that in the VBM3D algorithm.
American Psychological Association (APA)
Yahya, Ali Abdullah& Tan, Jieqing& Su, Benyu& Liu, Kui& Hadi, Ali Naser. 2017. Spatiotemporal Video Denoising Based on Adaptive Thresholding and Clustering. Discrete Dynamics in Nature and Society،Vol. 2017, no. 2017, pp.1-11.
https://search.emarefa.net/detail/BIM-1151695
Modern Language Association (MLA)
Yahya, Ali Abdullah…[et al.]. Spatiotemporal Video Denoising Based on Adaptive Thresholding and Clustering. Discrete Dynamics in Nature and Society No. 2017 (2017), pp.1-11.
https://search.emarefa.net/detail/BIM-1151695
American Medical Association (AMA)
Yahya, Ali Abdullah& Tan, Jieqing& Su, Benyu& Liu, Kui& Hadi, Ali Naser. Spatiotemporal Video Denoising Based on Adaptive Thresholding and Clustering. Discrete Dynamics in Nature and Society. 2017. Vol. 2017, no. 2017, pp.1-11.
https://search.emarefa.net/detail/BIM-1151695
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1151695