Anisotropic Diffusion Model Based on a New Diffusion Coefficient and Fractional Order Differential for Image Denoising

2016 ◽  
Vol 16 (01) ◽  
pp. 1650003 ◽  
Author(s):  
Jianjun Yuan ◽  
Lipei Liu
Keyword(s):  
Diffusion Coefficient ◽  
Image Denoising ◽  
Diffusion Model ◽  
Fractional Order ◽  
Anisotropic Diffusion ◽  
Model Based ◽  
Proposed Model

This paper presents an improved anisotropic diffusion model which is based on a new diffusion coefficient and fractional order differential for image denoising. In the proposed model, the new diffusion coefficient can protect edges and fine characteristics from being over-smoothed. The fractional order differential is applied to weaken the staircasing effect, preserve fine characteristics. Additionally, the automatic set method of diffusion coefficient threshold is developed. Comparative experiments show that the proposed model succeeds in denoising and preserving fine characteristics.

An Improved Anisotropic Diffusion Model Based on Wavelet Transform for Image Denosing

2012 ◽  
Vol 532-533 ◽  
pp. 1205-1208
Author(s):  
Rui Lin Zhang ◽  
Hui Min Liu ◽  
Zhu Hua Hu ◽  
Wei Jie Guo
Keyword(s):  
Wavelet Transform ◽  
Image Denoising ◽  
Diffusion Model ◽  
Anisotropic Diffusion ◽  
New Method ◽  
Gray Level ◽  
Low Contrast ◽  
Model Based ◽  
Image Denosing ◽  
Local Gradient

Preserving meaningful details such as blurred thin edges and low-contrast fine features is important in image de noising. A new method based on improved anisotropic diffusion model and wavelet transform is presented for image denoising. The proposed diffusion model incorporates both local gradient and gray-level variance to preserve edges and fine details while effectively removing noise in low-contrast surface images.

scholarly journals Modified Perona-Malik Equation and Computer Simulation for Image Denoising

2014 ◽  
Vol 8 (1) ◽  
pp. 37-41
Author(s):  
Zheng Jian Feng ◽  
Huang Chengwei ◽  
Zhang Ji
Keyword(s):  
Differential Equation ◽  
Partial Differential Equation ◽  
Computer Simulation ◽  
Image Denoising ◽  
Digital Image ◽  
Gaussian Noise ◽  
Anisotropic Diffusion ◽  
Difficult Problem ◽  
Experimental Results ◽  
Proposed Model

The edges and textures of a digital image may be destroyed by traditional denoising methods, which is a difficult problem in image denoising. In this paper, anisotropic diffusion algorithm based on Partial differential equation is studied. First, image denoising algorithms based on Perona-Malik model are studied. Second, a modified Perona-Malik model is proposed. In the proposed model, the gradient statistic and edge thresholds are embedded into the Perona-Malik equation. Finally, the effects of this model and some other models are compared and analyzed. The experimental results show that the proposed modified Perona-Malik model outperforms the original Perona-Malik model in removing Gaussian noise, and the edges and textures of the image are well preserved.

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