Denoising of Tourist Street Scene Image Based on ROF Model of Second-Order Partial Differential Equation

The noise pollution in tourist street view images is caused by various reasons. A major challenge that researchers have been facing is to find a way to effectively remove noise. Although in the past few decades people have proposed many methods of denoising tourist street scene images, the research...

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Autor principal:	Xiaofeng Yang
Formato:	article
Lenguaje:	EN
Publicado:	Hindawi Limited 2021
Materias:	Physics QC1-999
Acceso en línea:	https://doaj.org/article/14df92b8686e494bace45b5295b3ac96
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id	oai:doaj.org-article:14df92b8686e494bace45b5295b3ac96
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spelling	oai:doaj.org-article:14df92b8686e494bace45b5295b3ac962021-11-08T02:37:28ZDenoising of Tourist Street Scene Image Based on ROF Model of Second-Order Partial Differential Equation1687-913910.1155/2021/6547350https://doaj.org/article/14df92b8686e494bace45b5295b3ac962021-01-01T00:00:00Zhttp://dx.doi.org/10.1155/2021/6547350https://doaj.org/toc/1687-9139The noise pollution in tourist street view images is caused by various reasons. A major challenge that researchers have been facing is to find a way to effectively remove noise. Although in the past few decades people have proposed many methods of denoising tourist street scene images, the research on denoising technology of tourist street scene images is still not outdated. There is no doubt that it has become a basic and important research topic in the field of digital image processing. The evolutionary diffusion method based on partial differential equations is helpful to improve the quality of noisy tourist street scene images. This method can process tourist street scene images according to people’s expected diffusion behavior. The adaptive total variation model proposed in this paper is improved on the basis of the total variation model and the Gaussian thermal diffusion model. We analyze the classic variational PDE-based denoising model and get a unified variational PDE energy functional model. We also give a detailed analysis of the diffusion performance of the total variational model and then propose an adaptive total variational diffusion model. By improving the diffusion coefficient and introducing a curvature operator that can distinguish details such as edges, it can effectively denoise the tourist street scene image, and it also has a good effect on avoiding the step effect. Through the improvement of the ROF model, the loyalty term and regular term of the model are parameterized, the adaptive total variation denoising model of this paper is established, and a detailed analysis is carried out. The experimental results show that compared with some traditional denoising models, the model in this paper can effectively suppress the step effect in the denoising process, while protecting the texture details of the edge area of the tourist street scene image. In addition, the model in this paper is superior to traditional denoising models in terms of denoising performance and texture structure protection.Xiaofeng YangHindawi LimitedarticlePhysicsQC1-999ENAdvances in Mathematical Physics, Vol 2021 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Physics QC1-999
spellingShingle	Physics QC1-999 Xiaofeng Yang Denoising of Tourist Street Scene Image Based on ROF Model of Second-Order Partial Differential Equation
description	The noise pollution in tourist street view images is caused by various reasons. A major challenge that researchers have been facing is to find a way to effectively remove noise. Although in the past few decades people have proposed many methods of denoising tourist street scene images, the research on denoising technology of tourist street scene images is still not outdated. There is no doubt that it has become a basic and important research topic in the field of digital image processing. The evolutionary diffusion method based on partial differential equations is helpful to improve the quality of noisy tourist street scene images. This method can process tourist street scene images according to people’s expected diffusion behavior. The adaptive total variation model proposed in this paper is improved on the basis of the total variation model and the Gaussian thermal diffusion model. We analyze the classic variational PDE-based denoising model and get a unified variational PDE energy functional model. We also give a detailed analysis of the diffusion performance of the total variational model and then propose an adaptive total variational diffusion model. By improving the diffusion coefficient and introducing a curvature operator that can distinguish details such as edges, it can effectively denoise the tourist street scene image, and it also has a good effect on avoiding the step effect. Through the improvement of the ROF model, the loyalty term and regular term of the model are parameterized, the adaptive total variation denoising model of this paper is established, and a detailed analysis is carried out. The experimental results show that compared with some traditional denoising models, the model in this paper can effectively suppress the step effect in the denoising process, while protecting the texture details of the edge area of the tourist street scene image. In addition, the model in this paper is superior to traditional denoising models in terms of denoising performance and texture structure protection.
format	article
author	Xiaofeng Yang
author_facet	Xiaofeng Yang
author_sort	Xiaofeng Yang
title	Denoising of Tourist Street Scene Image Based on ROF Model of Second-Order Partial Differential Equation
title_short	Denoising of Tourist Street Scene Image Based on ROF Model of Second-Order Partial Differential Equation
title_full	Denoising of Tourist Street Scene Image Based on ROF Model of Second-Order Partial Differential Equation
title_fullStr	Denoising of Tourist Street Scene Image Based on ROF Model of Second-Order Partial Differential Equation
title_full_unstemmed	Denoising of Tourist Street Scene Image Based on ROF Model of Second-Order Partial Differential Equation
title_sort	denoising of tourist street scene image based on rof model of second-order partial differential equation
publisher	Hindawi Limited
publishDate	2021
url	https://doaj.org/article/14df92b8686e494bace45b5295b3ac96
work_keys_str_mv	AT xiaofengyang denoisingoftouriststreetsceneimagebasedonrofmodelofsecondorderpartialdifferentialequation
_version_	1718442973506568192

Denoising of Tourist Street Scene Image Based on ROF Model of Second-Order Partial Differential Equation

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