scholarly journals A Hybrid Model for Image Denoising Combining Modified Isotropic Diffusion Model and Modified Perona-Malik Model

IEEE Access ◽  
2018 ◽  
Vol 6 ◽  
pp. 33568-33582 ◽  
Author(s):  
Na Wang ◽  
Yu Shang ◽  
Yang Chen ◽  
Min Yang ◽  
Quan Zhang ◽  
...  
Keyword(s):  
Image Denoising ◽  
Diffusion Model ◽  
Hybrid Model ◽  
Isotropic Diffusion

A compensating total variation image denoising model combining L1 and L2 norm

2020 ◽  
pp. 002072092092330
Author(s):  
Liqiong Zhang ◽  
Min Li ◽  
Xiaohua Qiu
Keyword(s):  
Image Denoising ◽  
Total Variation ◽  
Structural Information ◽  
Signal To Noise Ratio ◽  
Similarity Index ◽  
Structural Similarity ◽  
Isotropic Diffusion ◽  
Model Combining ◽  
L2 Norm ◽  
Staircase Effect

To overcome the “staircase effect” while preserving the structural information such as image edges and textures quickly and effectively, we propose a compensating total variation image denoising model combining L1 and L2 norm. A new compensating regular term is designed, which can perform anisotropic and isotropic diffusion in image denoising, thus making up for insufficient diffusion in the total variation model. The algorithm first uses local standard deviation to distinguish neighborhood types. Then, the anisotropic diffusion based on L1 norm plays the role of edge protection in the strong edge region. The anisotropic and the isotropic diffusion simultaneously exist in the smooth region, so that the weak textures can be protected while overcoming the “staircase effect” effectively. The simulation experiments show that this method can effectively improve the peak signal-to-noise ratio and obtain the higher structural similarity index and the shorter running time.

An Anisotropic Convection-Diffusion Model Using Tailored Finite Point Method for Image Denoising and Compression

2016 ◽  
Vol 19 (5) ◽  
pp. 1357-1374
Author(s):  
Yu-Tuan Lin ◽  
Yin-Tzer Shih ◽  
Chih-Ching Tsai
Keyword(s):  
Image Denoising ◽  
Diffusion Model ◽  
Point Method ◽  
Grid Structure ◽  
Finite Point ◽  
Convection Diffusion ◽  
Finite Point Method ◽  
Tailored Finite Point Method ◽  
Tailored Finite Point ◽  
Salt And Pepper

AbstractIn this paper we consider an anisotropic convection-diffusion (ACD) filter for image denoising and compression simultaneously. The ACD filter is discretized by a tailored finite point method (TFPM), which can tailor some particular properties of the image in an irregular grid structure. A quadtree structure is implemented for the storage in multi-levels for the compression. We compare the performance of the proposed scheme with several well-known filters. The numerical results show that the proposed method is effective for removing a mixture of white Gaussian and salt-and-pepper noises.

Nonlinear Diffusion Model for Fabric Image Denoising

2012 ◽  
Vol 627 ◽  
pp. 484-488
Author(s):  
Da Li Chen ◽  
Ding Yu Xue ◽  
Yang Quan Chen
Keyword(s):  
Image Denoising ◽  
Diffusion Model ◽  
Nonlinear Diffusion ◽  
Diffusion Models ◽  
Perceptual Comparison

In this paper, five nonlinear diffusion models for fabric image denoising are introduced. The advantages and drawbacks of these five models are described through describing their implementation methods. Quantitative and perceptual comparison experiments are given to verify the performance of these methods. Finally some valuable conclusions about denoising performance of these five models are present which is helpful for choosing and using these models in fabric image denoising.

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