Image noise reduction based on applying adaptive thresholding onto PDEs methods

The Journal of Engineering

Ali Naser Hadi¹  Ali Abdullah Yahya¹  Benyu Su²  Jieqing Tan³  Kui Liu³ 

[1] School of Computer and Information, Anqing Normal University, Anqing 246011, People'School of Computer and Information, Hefei University of Technology, Hefei 230009, People's Republic of China

关键词: noise removal;    image noise reduction;    adaptive thresholding;    optimal noise reduction;    PDE method;    edge preservation;    image denoising method;    partial differential equation;    total variation filter;    sharp edges;    anisotropic diffusion filter;    reference algorithms;   

DOI  :  10.1049/joe.2017.0112

学科分类：工程和技术（综合）

来源: IET

【 摘 要 】

In this study the authors present a novel image denoising method based on applying adaptive thresholding on partial differential (PDEs) methods. In the proposed method the authors utilise the adaptive thresholding to blend the total variation filter with anisotropic diffusion filter. The adaptive thresholding has a high capacity to adapt and change according to the amount of noise. More specifically, applying a hard thresholding on the higher noise areas, whereas, applying soft thresholding on the lower noise areas. Therefore, the authors can successfully remove the noise effectively and maintain the edges of the image simultaneously. Based on the adaptation and stability of the adaptive thresholding we can achieve; optimal noise reduction and sharp edges as well. Experimental results demonstrate that the new algorithm consistently outperforms other reference methods in terms of noise removal and edges preservation, in addition to 4.7 dB gain higher than those in the other reference algorithms.

【 授权许可】

CC BY