<abstract xmlns="http://www.w3.org/1999/xhtml"><p> In this paper we propose a new approach for image denoising based on the combination of PM model, isotropic diffusion model, and TV model. To emphasize the superiority of the proposed model, we have used the Structural Similarity Index Measure (SSIM) and Peak Signal to Noise Ratio (PSNR) as the subjective criterion. Numerical experiments with different images show that our algorithm has the highest PSNR and SS1M, as well as the best visual quality among the six algorithms. Experimental results confirm the high performance of the proposed model compared with some well-known algorithms. In a word, the new model outperforms the mentioned three well known algorithms in reducing the Gibbs-type artifacts, edges blurring, and the block effect, simultaneously.</p></abstract>

In this paper we propose a new approach for image denoising based on the combination of PM model, isotropic diffusion model, and TV model. To emphasize the superiority of the proposed model, we have used the Structural Similarity Index Measure (SSIM) and Peak Signal to Noise Ratio (PSNR) as the subjective criterion. Numerical experiments with different images show that our algorithm has the highest PSNR and SS1M, as well as the best visual quality among the six algorithms. Experimental results confirm the high performance of the proposed model compared with some well-known algorithms. In a word, the new model outperforms the mentioned three well known algorithms in reducing the Gibbs-type artifacts, edges blurring, and the block effect, simultaneously.

Research on the Image Denoising Method Based on Partial Differential Equations

Media Art College，Chongqing College of Electronic Engineering, Chongqing 401331,

Cybernetics and Information Technologies

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

{"article-title":"Research on the Image Denoising Method Based on Partial Differential Equations"}

In this paper we propose a new approach for image denoising based on the combination of PM model, isotropic diffusion model, and TV model. To emphasize the...

Research on the Image Denoising Method Based on Partial Differential Equations

Online veröffentlicht: 20. Okt. 2016

Seitenbereich: 109 - 118

DOI: https://doi.org/10.1515/cait-2016-0057

Schlüsselwörter
Image denoising method, Partial differential equations, The blending algorithm

© by Xiaolu Xie

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Research on the Image Denoising Method Based on Partial Differential Equations

Online veröffentlicht: 20. Okt. 2016

Seitenbereich: 109 - 118

DOI: https://doi.org/10.1515/cait-2016-0057

SchlüsselwörterImage denoising method, Partial differential equations, The blending algorithm

© by Xiaolu Xie

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Schlüsselwörter
Image denoising method, Partial differential equations, The blending algorithm