An Adaptive Boosting Algorithm for Image Denoising
Joint Authors
Tang, Liming
Fang, Zhuang
Yi, Xuming
Source
Mathematical Problems in Engineering
Issue
Vol. 2019, Issue 2019 (31 Dec. 2019), pp.1-14, 14 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2019-02-18
Country of Publication
Egypt
No. of Pages
14
Main Subjects
Abstract EN
Image denoising is an important problem in many fields of image processing.
Boosting algorithm attracts extensive attention in recent years, which provides a general framework by strengthening the original noisy image.
In such framework, many classical existing denoising algorithms can improve the denoising performance.
However, the boosting step is fixed or nonadaptive; i.e., the noise level in iteration steps is set to be a constant.
In this work, we propose a noise level estimation algorithm by combining the overestimation and underestimation results.
Based on this, we further propose an adaptive boosting algorithm that excludes intricate parameter configuration.
Moreover, we prove the convergence of the proposed algorithm.
Experimental results that are obtained in this paper demonstrate the effectiveness of the proposed adaptive boosting algorithm.
In addition, compared with the classical boosting algorithm, the proposed algorithm can get better performance in terms of visual quality and peak signal-to-noise ratio (PSNR).
American Psychological Association (APA)
Fang, Zhuang& Yi, Xuming& Tang, Liming. 2019. An Adaptive Boosting Algorithm for Image Denoising. Mathematical Problems in Engineering،Vol. 2019, no. 2019, pp.1-14.
https://search.emarefa.net/detail/BIM-1197567
Modern Language Association (MLA)
Fang, Zhuang…[et al.]. An Adaptive Boosting Algorithm for Image Denoising. Mathematical Problems in Engineering No. 2019 (2019), pp.1-14.
https://search.emarefa.net/detail/BIM-1197567
American Medical Association (AMA)
Fang, Zhuang& Yi, Xuming& Tang, Liming. An Adaptive Boosting Algorithm for Image Denoising. Mathematical Problems in Engineering. 2019. Vol. 2019, no. 2019, pp.1-14.
https://search.emarefa.net/detail/BIM-1197567
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1197567